diff --git a/.github/workflows/lantern.yaml b/.github/workflows/lantern.yaml index 6492e3d884..0cc46f9500 100644 --- a/.github/workflows/lantern.yaml +++ b/.github/workflows/lantern.yaml @@ -19,7 +19,6 @@ jobs: - {os: macOS, version: cpu-m1, runner: [self-hosted, m1]} - {os: ubuntu, version: cpu, runner: ubuntu-latest} - - {os: ubuntu, version: cu11.6, runner: [self-hosted, gce, disk]} - {os: ubuntu, version: cu11.7, runner: [self-hosted, gce, disk]} - {os: windows, version: cpu, runner: windows-2019} @@ -33,12 +32,9 @@ jobs: # specify the CUDA patch for each major/minor version. # required for cuda installation - - config: {version: cu11.6} - cuda: 11.6 - cuda_patch: 1 - config: {version: cu11.7} cuda: 11.7 - cuda_patch: 0 + cuda_patch: 1 exclude: - config: {os: macOS} diff --git a/.github/workflows/main.yaml b/.github/workflows/main.yaml index 02b7ae9062..d4aca3747c 100644 --- a/.github/workflows/main.yaml +++ b/.github/workflows/main.yaml @@ -33,8 +33,7 @@ jobs: - {os: ubuntu, r_version: release, version: cpu, runner: ubuntu-20.04} # the precxx11abi R version is whichever is specified in the selected container. - {os: centos, r_version: '', version: cpu, runner: ubuntu-20.04, precxx11abi: 1} - - {os: ubuntu, r_version: release, version: cu11.6, runner: [self-hosted, gce, gpu]} - - {os: ubuntu, r_version: release, version: cu11.7, runner: [self-hosted, gce, gpu]} + - {os: ubuntu, r_version: release, version: cu11.7, runner: [self-hosted, gpu-local]} - {os: windows, r_version: release, version: cpu, runner: windows-latest} - {os: windows, r_version: 3.6, version: cpu, runner: windows-latest} @@ -43,12 +42,9 @@ jobs: - config: {os: centos, precxx11abi: 1} container: rstudio/r-base:4.2-centos7 - - - config: {os: ubuntu, version: cu11.6} - container: {image: 'nvidia/cuda:11.6.0-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} - config: {os: ubuntu, version: cu11.7} - container: {image: 'nvidia/cuda:11.7.0-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} + container: {image: 'nvidia/cuda:11.7.1-cudnn8-devel-ubuntu18.04', options: '--gpus all --runtime=nvidia'} runs-on: ${{ matrix.config.runner }} container: ${{ matrix.container }} diff --git a/NAMESPACE b/NAMESPACE index 91e2a0f015..4a849c6b1c 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -801,7 +801,6 @@ export(torch_sub) export(torch_subtract) export(torch_sum) export(torch_svd) -export(torch_symeig) export(torch_t) export(torch_take) export(torch_tan) diff --git a/R/RcppExports.R b/R/RcppExports.R index c88cb4d3bf..5c296e2802 100644 --- a/R/RcppExports.R +++ b/R/RcppExports.R @@ -545,6 +545,14 @@ cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor <- function(self, vec .Call(`_torch_cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor`, self, vec1, vec2, beta, alpha) } +cpp_torch_method__is_all_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_method__is_all_true_self_Tensor`, self) +} + +cpp_torch_method__is_any_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_method__is_any_true_self_Tensor`, self) +} + cpp_torch_method_all_self_Tensor_dim_int64_t <- function(self, dim, keepdim) { .Call(`_torch_cpp_torch_method_all_self_Tensor_dim_int64_t`, self, dim, keepdim) } @@ -1681,10 +1689,6 @@ cpp_torch_method_prelu_self_Tensor_weight_Tensor <- function(self, weight) { .Call(`_torch_cpp_torch_method_prelu_self_Tensor_weight_Tensor`, self, weight) } -cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor <- function(grad_output, self, weight) { - .Call(`_torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor`, grad_output, self, weight) -} - cpp_torch_method_hardshrink_self_Tensor <- function(self, lambd) { .Call(`_torch_cpp_torch_method_hardshrink_self_Tensor`, self, lambd) } @@ -1849,6 +1853,10 @@ cpp_torch_method_squeeze_self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_method_squeeze_self_Tensor_dim_Dimname`, self, dim) } +cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_method_squeeze__self_Tensor <- function(self) { .Call(`_torch_cpp_torch_method_squeeze__self_Tensor`, self) } @@ -1857,6 +1865,10 @@ cpp_torch_method_squeeze__self_Tensor_dim_int64_t <- function(self, dim) { .Call(`_torch_cpp_torch_method_squeeze__self_Tensor_dim_int64_t`, self, dim) } +cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_method_squeeze__self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname`, self, dim) } @@ -1925,18 +1937,10 @@ cpp_torch_method_std_self_Tensor_dim_IntArrayRef <- function(self, dim, unbiased .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_std_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_prod_self_Tensor <- function(self, dtype) { .Call(`_torch_cpp_torch_method_prod_self_Tensor`, self, dtype) } @@ -2057,18 +2061,10 @@ cpp_torch_method_var_self_Tensor_dim_IntArrayRef <- function(self, dim, unbiased .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_var_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_method_view_as_self_Tensor_other_Tensor <- function(self, other) { .Call(`_torch_cpp_torch_method_view_as_self_Tensor_other_Tensor`, self, other) } @@ -2077,6 +2073,10 @@ cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor <- function(con .Call(`_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor`, condition, self, other) } +cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar <- function(condition, self, other) { + .Call(`_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar`, condition, self, other) +} + cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType <- function(self, p, dtype) { .Call(`_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType`, self, p, dtype) } @@ -2273,24 +2273,24 @@ cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t <- function(self, spar .Call(`_torch_cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t`, self, sparse_dim) } -cpp_torch_method_to_sparse_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_method_to_sparse_self_Tensor`, self) +cpp_torch_method_to_sparse_self_Tensor <- function(self, layout, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_self_Tensor`, self, layout, blocksize, dense_dim) } -cpp_torch_method_to_sparse_csr_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_method_to_sparse_csr_self_Tensor`, self) +cpp_torch_method_to_sparse_csr_self_Tensor <- function(self, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_csr_self_Tensor`, self, dense_dim) } -cpp_torch_method_to_sparse_csc_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_method_to_sparse_csc_self_Tensor`, self) +cpp_torch_method_to_sparse_csc_self_Tensor <- function(self, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_csc_self_Tensor`, self, dense_dim) } -cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize) { - .Call(`_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef`, self, blocksize) +cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef`, self, blocksize, dense_dim) } -cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize) { - .Call(`_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef`, self, blocksize) +cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef <- function(self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef`, self, blocksize, dense_dim) } cpp_torch_method_to_mkldnn_self_Tensor <- function(self, dtype) { @@ -3009,10 +3009,6 @@ cpp_torch_method_triangular_solve_self_Tensor_A_Tensor <- function(self, A, uppe .Call(`_torch_cpp_torch_method_triangular_solve_self_Tensor_A_Tensor`, self, A, upper, transpose, unitriangular) } -cpp_torch_method_symeig_self_Tensor <- function(self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_method_symeig_self_Tensor`, self, eigenvectors, upper) -} - cpp_torch_method_svd_self_Tensor <- function(self, some, compute_uv) { .Call(`_torch_cpp_torch_method_svd_self_Tensor`, self, some, compute_uv) } @@ -3417,10 +3413,6 @@ cpp_torch_method_to_padded_tensor_self_Tensor_padding_double <- function(self, p .Call(`_torch_cpp_torch_method_to_padded_tensor_self_Tensor_padding_double`, self, padding, output_size) } -cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double <- function(self, weight, bias, eps) { - .Call(`_torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double`, self, weight, bias, eps) -} - cpp_torch_namespace__cast_Byte_self_Tensor <- function(self, non_blocking) { .Call(`_torch_cpp_torch_namespace__cast_Byte_self_Tensor`, self, non_blocking) } @@ -3773,6 +3765,18 @@ cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_ .Call(`_torch_cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_align_corners_bool`, grad, size, align_corners) } +cpp_torch_namespace__is_all_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_namespace__is_all_true_self_Tensor`, self) +} + +cpp_torch_namespace__is_any_true_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_namespace__is_any_true_self_Tensor`, self) +} + +cpp_torch_namespace__test_check_tensor_self_Tensor <- function(self) { + .Call(`_torch_cpp_torch_namespace__test_check_tensor_self_Tensor`, self) +} + cpp_torch_namespace_all_self_Tensor_dim_int64_t <- function(self, dim, keepdim) { .Call(`_torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t`, self, dim, keepdim) } @@ -5729,12 +5733,8 @@ cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef <- function(s .Call(`_torch_cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef`, self, kernel_size, stride, padding, dilation, ceil_mode) } -cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef <- function(self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef`, self, kernel_size, stride, padding, dilation, ceil_mode) -} - -cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) +cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { + .Call(`_torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) } cpp_torch_namespace_mkldnn_max_pool2d_self_Tensor_kernel_size_IntArrayRef <- function(self, kernel_size, stride, padding, dilation, ceil_mode) { @@ -5869,6 +5869,14 @@ cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_pad .Call(`_torch_cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t`, self, weight, bias, padding, stride, dilation, groups) } +cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool <- function(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool`, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) +} + +cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor <- function(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor`, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) +} + cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double <- function(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) { .Call(`_torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double`, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) } @@ -5917,12 +5925,12 @@ cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor <- function(sparse, de .Call(`_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor`, sparse, dense) } -cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor <- function(self, other) { - .Call(`_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor`, self, other) +cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view <- function(sparse, dense, reduce) { + .Call(`_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view`, sparse, dense, reduce) } -cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor <- function(t, mask_indices) { - .Call(`_torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor`, t, mask_indices) +cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor`, self, other) } cpp_torch_namespace_mode_self_Tensor_dim_int64_t <- function(self, dim, keepdim) { @@ -6005,6 +6013,22 @@ cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invst .Call(`_torch_cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) } +cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, input, weight, bias, running_mean, running_var, training, momentum, eps) +} + +cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double <- function(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) +} + +cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double <- function(input, weight, bias, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double`, input, weight, bias, training, momentum, eps) +} + +cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double <- function(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double`, out, save_mean, save_invstd, input, weight, bias, training, momentum, eps) +} + cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double <- function(input, eps) { .Call(`_torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double`, input, eps) } @@ -6353,6 +6377,10 @@ cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef <- function(self, shap .Call(`_torch_cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef`, self, shape) } +cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef <- function(self, size) { + .Call(`_torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef`, self, size) +} + cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(self, size, stride) { .Call(`_torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, self, size, stride) } @@ -6413,8 +6441,12 @@ cpp_torch_namespace_prelu_self_Tensor_weight_Tensor <- function(self, weight) { .Call(`_torch_cpp_torch_namespace_prelu_self_Tensor_weight_Tensor`, self, weight) } -cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor <- function(grad_output, self, weight) { - .Call(`_torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor`, grad_output, self, weight) +cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor <- function(self, weight) { + .Call(`_torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor`, self, weight) +} + +cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor <- function(grad_output, self, weight) { + .Call(`_torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor`, grad_output, self, weight) } cpp_torch_namespace_gelu_out_out_Tensor_self_Tensor <- function(out, self, approximate) { @@ -6725,6 +6757,10 @@ cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname`, self, dim) } +cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor <- function(self, mat1, mat2, beta, alpha) { .Call(`_torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor`, self, mat1, mat2, beta, alpha) } @@ -6853,10 +6889,6 @@ cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef <- function(self, dim, unbia .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_mean_self_Tensor <- function(self, unbiased) { .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor`, self, unbiased) } @@ -6865,26 +6897,14 @@ cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef <- function(self, dim, .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef <- function(out, self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_std_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } @@ -6893,14 +6913,6 @@ cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList <- function(o .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - -cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_prod_self_Tensor <- function(self, dtype) { .Call(`_torch_cpp_torch_namespace_prod_self_Tensor`, self, dtype) } @@ -7141,18 +7153,10 @@ cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef <- function(self, dim, unbia .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef <- function(out, self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } @@ -7161,14 +7165,6 @@ cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList <- function(o .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList`, out, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - -cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t <- function(out, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t`, out, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_mean_self_Tensor <- function(self, unbiased) { .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor`, self, unbiased) } @@ -7177,18 +7173,10 @@ cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef <- function(self, dim, .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList <- function(self, dim, unbiased, keepdim) { .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList`, self, dim, unbiased, keepdim) } -cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t <- function(self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t`, self, dim, correction, keepdim) -} - cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor <- function(condition, self, other) { .Call(`_torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor`, condition, self, other) } @@ -7397,10 +7385,6 @@ cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor <- fun .Call(`_torch_cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor`, mantissa, exponent, self) } -cpp_torch_namespace_frobenius_norm_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_namespace_frobenius_norm_self_Tensor`, self) -} - cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef <- function(self, dim, keepdim) { .Call(`_torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef`, self, dim, keepdim) } @@ -7497,6 +7481,14 @@ cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor <- .Call(`_torch_cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor`, self, mat1, mat2, beta, alpha) } +cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view <- function(self, other, reduce) { + .Call(`_torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view`, self, other, reduce) +} + +cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2 <- function(self, grad_out, weight, reduce, arg_out, output_mask) { + .Call(`_torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2`, self, grad_out, weight, reduce, arg_out, output_mask) +} + cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor <- function(out, self, mat1, mat2, beta, alpha) { .Call(`_torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor`, out, self, mat1, mat2, beta, alpha) } @@ -7653,8 +7645,8 @@ cpp_torch_namespace_unbind_self_Tensor_dim_Dimname <- function(self, dim) { .Call(`_torch_cpp_torch_namespace_unbind_self_Tensor_dim_Dimname`, self, dim) } -cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor <- function(self, padding, stride, dilation, groups) { - .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor`, self, padding, stride, dilation, groups) +cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor <- function(self, padding, stride, dilation, groups, input_size) { + .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor`, self, padding, stride, dilation, groups, input_size) } cpp_torch_namespace_mkldnn_reorder_conv3d_weight_self_Tensor <- function(self, padding, stride, dilation, groups) { @@ -7845,8 +7837,8 @@ cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_b .Call(`_torch_cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) } -cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - .Call(`_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) +cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + .Call(`_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) } cpp_torch_namespace__thnn_fused_lstm_cell_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor <- function(input_gates, hidden_gates, cx, input_bias, hidden_bias) { @@ -8241,10 +8233,6 @@ cpp_torch_namespace_diag_self_Tensor <- function(self, diagonal) { .Call(`_torch_cpp_torch_namespace_diag_self_Tensor`, self, diagonal) } -cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t <- function(grad, input_sizes, diagonal) { - .Call(`_torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t`, grad, input_sizes, diagonal) -} - cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor <- function(out, self, other, dim) { .Call(`_torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor`, out, self, other, dim) } @@ -8593,18 +8581,6 @@ cpp_torch_namespace_linalg_vander_x_Tensor <- function(x, False) { .Call(`_torch_cpp_torch_namespace_linalg_vander_x_Tensor`, x, False) } -cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor <- function(e, V, self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor`, e, V, self, eigenvectors, upper) -} - -cpp_torch_namespace_symeig_self_Tensor <- function(self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace_symeig_self_Tensor`, self, eigenvectors, upper) -} - -cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool <- function(self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool`, self, eigenvectors, upper) -} - cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor <- function(U, S, V, self, some, compute_uv) { .Call(`_torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor`, U, S, V, self, some, compute_uv) } @@ -8957,6 +8933,10 @@ cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor <- function(out, .Call(`_torch_cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor`, out, self, other) } +cpp_torch_namespace_max_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor`, out, self) +} + cpp_torch_namespace_minimum_self_Tensor_other_Tensor <- function(self, other) { .Call(`_torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor`, self, other) } @@ -9209,6 +9189,38 @@ cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar <- function(self invisible(.Call(`_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar`, self, scalar)) } +cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar`, self, scalar)) +} + +cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar`, self, scalar)) +} + +cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar`, self, scalar)) +} + +cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar <- function(self, scalar) { + .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar`, self, scalar) +} + +cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar <- function(self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar`, self, scalar)) +} + cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList <- function(self, other, alpha) { .Call(`_torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList`, self, other, alpha) } @@ -9241,6 +9253,38 @@ cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList <- function(s invisible(.Call(`_torch_cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList`, self, other)) } +cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList`, self, other)) +} + +cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList`, self, other)) +} + +cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList`, self, other)) +} + +cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList <- function(self, other) { + .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList`, self, other) +} + +cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList <- function(self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList`, self, other)) +} + cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { .Call(`_torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar`, self, scalars) } @@ -9273,6 +9317,38 @@ cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar <- func invisible(.Call(`_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) } +cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + +cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + +cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + +cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar`, self, scalars) +} + +cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar <- function(self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar`, self, scalars)) +} + cpp_torch_namespace__foreach_exp_self_TensorList <- function(self) { .Call(`_torch_cpp_torch_namespace__foreach_exp_self_TensorList`, self) } @@ -9513,10 +9589,18 @@ cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2 invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars)) } +cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars)) +} + cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(self, tensor1, tensor2, scalars) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars)) } +cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars)) +} + cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList <- function(self, tensor1, tensor2, value) { .Call(`_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList`, self, tensor1, tensor2, value) } @@ -9529,28 +9613,36 @@ cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_ .Call(`_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars) } +cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars) +} + cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(self, tensor1, tensor2, scalars) { .Call(`_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, self, tensor1, tensor2, scalars) } -cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList <- function(self, other) { - .Call(`_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList`, self, other) +cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(self, tensor1, tensor2, scalars) { + .Call(`_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, self, tensor1, tensor2, scalars) } -cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList <- function(self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList`, self, other)) +cpp_torch_namespace__foreach_norm_self_TensorList <- function(self, ord) { + .Call(`_torch_cpp_torch_namespace__foreach_norm_self_TensorList`, self, ord) } -cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList <- function(self, other) { - .Call(`_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList`, self, other) +cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList <- function(self, tensors1, weights) { + .Call(`_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList`, self, tensors1, weights) } -cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList <- function(self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList`, self, other)) +cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList <- function(self, tensors1, weights) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList`, self, tensors1, weights)) } -cpp_torch_namespace__foreach_norm_self_TensorList <- function(self, ord) { - .Call(`_torch_cpp_torch_namespace__foreach_norm_self_TensorList`, self, ord) +cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar <- function(self, tensors1, weight) { + .Call(`_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar`, self, tensors1, weight) +} + +cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar <- function(self, tensors1, weight) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar`, self, tensors1, weight)) } cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor <- function(self, boundaries, out_int32, right) { @@ -9569,10 +9661,6 @@ cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor <- function( .Call(`_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor`, sorted_sequence, self, out_int32, right, side, sorter) } -cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor <- function(self) { - .Call(`_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor`, self) -} - cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor <- function(out, sorted_sequence, self, out_int32, right, side, sorter) { .Call(`_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor`, out, sorted_sequence, self, out_int32, right, side, sorter) } @@ -10253,50 +10341,26 @@ cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align .Call(`_torch_cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(input, output_size, align_corners, scale_factors) { .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, input, output_size, align_corners, scale_factors) } -cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, align_corners, scale_factors) -} - cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(input, output_size, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } @@ -10305,14 +10369,6 @@ cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayR .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } -cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - -cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(input, output_size, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } @@ -10321,14 +10377,6 @@ cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayR .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } -cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - -cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(input, output_size, scale_factors) { .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } @@ -10337,14 +10385,6 @@ cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayR .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, input, output_size, scale_factors) } -cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - -cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, grad_output, output_size, input_size, scale_factors) -} - cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool <- function(out, self, output_size, align_corners, scales) { .Call(`_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool`, out, self, output_size, align_corners, scales) } @@ -11753,6 +11793,10 @@ cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t <- function(self, dim) .Call(`_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t`, self, dim) } +cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef <- function(self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef`, self, dim) +} + cpp_torch_namespace_t_copy_self_Tensor <- function(self) { .Call(`_torch_cpp_torch_namespace_t_copy_self_Tensor`, self) } @@ -11801,6 +11845,18 @@ cpp_torch_namespace_unbind_copy_self_Tensor <- function(self, dim) { .Call(`_torch_cpp_torch_namespace_unbind_copy_self_Tensor`, self, dim) } +cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor <- function(out, self, dim) { + invisible(.Call(`_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor`, out, self, dim)) +} + +cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t <- function(out, self, split_size, dim) { + invisible(.Call(`_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t`, out, self, split_size, dim)) +} + +cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef <- function(out, self, split_sizes, dim) { + invisible(.Call(`_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef`, out, self, split_sizes, dim)) +} + cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef <- function(self, size) { .Call(`_torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef`, self, size) } @@ -11817,164 +11873,72 @@ cpp_torch_namespace_alias_copy_self_Tensor <- function(self) { .Call(`_torch_cpp_torch_namespace_alias_copy_self_Tensor`, self) } -cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t <- function(out, self, level) { - .Call(`_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t`, out, self, level) +cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor <- function(self, query) { + .Call(`_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor`, self, query) } -cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t <- function(out, primal, tangent, level) { - .Call(`_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t`, out, primal, tangent, level) +cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) { + .Call(`_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor`, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) } -cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor <- function(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) { + .Call(`_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor`, query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) } -cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, is_causal) { + .Call(`_torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, is_causal) } -cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) } -cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, is_causal) { + .Call(`_torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, is_causal) } -cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride, storage_offset) { - .Call(`_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride, storage_offset) +cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, is_causal, dropout_mask) } -cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { - .Call(`_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) +cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, dropout_p, is_causal, return_debug_mask) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, dropout_p, is_causal, return_debug_mask) } -cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor <- function(out, self, offset, dim1, dim2) { - .Call(`_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor`, out, self, offset, dim1, dim2) +cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t`, grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) } -cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size, implicit) { - .Call(`_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size, implicit) +cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool <- function(query, key, value, compute_log_sumexp, is_causal) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool`, query, key, value, compute_log_sumexp, is_causal) } -cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef <- function(out, self, dims) { - .Call(`_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef`, out, self, dims) +cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor <- function(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) { + .Call(`_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor`, grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) } -cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride) { - .Call(`_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride) +cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, is_causal) { + .Call(`_torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, is_causal) } -cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t <- function(out, self, dim, index) { - .Call(`_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t`, out, self, dim, index) +cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask) { + .Call(`_torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool`, query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask) } -cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + .Call(`_torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t`, grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) } -cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor <- function(out, self, dim, start, end, step) { - .Call(`_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor`, out, self, dim, start, end, step) +cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t <- function(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal) { + .Call(`_torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t`, query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal) } -cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t <- function(out, self, split_size, dim) { - invisible(.Call(`_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t`, out, self, split_size, dim)) +cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor <- function(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) { + .Call(`_torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor`, grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs) } -cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef <- function(out, self, split_sizes, dim) { - invisible(.Call(`_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef`, out, self, split_sizes, dim)) -} - -cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { - .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) -} - -cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t <- function(out, self, dim0, dim1) { - .Call(`_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t`, out, self, dim0, dim1) -} - -cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { - .Call(`_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) -} - -cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor <- function(out, self, dim) { - invisible(.Call(`_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor`, out, self, dim)) -} - -cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { - .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) -} - -cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType <- function(out, self, dtype) { - .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType`, out, self, dtype) -} - -cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t <- function(out, self, dimension, size, step) { - .Call(`_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t`, out, self, dimension, size, step) -} - -cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor`, out, self) -} - -cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor <- function(self, query) { - .Call(`_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor`, self, query) -} - -cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) { - .Call(`_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor`, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) -} - -cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor <- function(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) { - .Call(`_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor`, query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type) -} - -cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { - .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) -} - -cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { - .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) -} - -cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor <- function(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) { - .Call(`_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor`, query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal) -} - -cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor <- function(q, k, v, dropout_p) { - .Call(`_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor`, q, k, v, dropout_p) +cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor <- function(q, k, v, dropout_p) { + .Call(`_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor`, q, k, v, dropout_p) } cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor <- function(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask) { @@ -11989,10 +11953,6 @@ cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor <- function(out, x) .Call(`_torch_cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor`, out, x) } -cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal) { - .Call(`_torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool`, query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal) -} - cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value) { .Call(`_torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor`, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value) } @@ -12385,6 +12345,10 @@ cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_Tenso invisible(.Call(`_torch_cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)) } +cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) { + invisible(.Call(`_torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)) +} + cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor <- function(out, self, other, self_num_batch_dims) { .Call(`_torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor`, out, self, other, self_num_batch_dims) } @@ -12585,6 +12549,10 @@ cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targe .Call(`_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef`, out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity) } +cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor <- function(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity) { + .Call(`_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor`, out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity) +} + cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t <- function(out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity) { .Call(`_torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t`, out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity) } @@ -12837,12 +12805,8 @@ cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t .Call(`_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t`, out0, out1, self, dim, keepdim) } -cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef`, out, self, kernel_size, stride, padding, dilation, ceil_mode) -} - -cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { - .Call(`_torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) +cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) { + .Call(`_torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef`, out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode) } cpp_torch_namespace_mkldnn_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef <- function(out, self, kernel_size, stride, padding, dilation, ceil_mode) { @@ -12889,6 +12853,14 @@ cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_ .Call(`_torch_cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t`, out, self, weight, bias, padding, stride, dilation, groups) } +cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool <- function(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool`, out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) +} + +cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor <- function(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + .Call(`_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor`, out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) +} + cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double <- function(out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) { .Call(`_torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double`, out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon) } @@ -12921,14 +12893,14 @@ cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tenso .Call(`_torch_cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tensor`, out, self, other) } -cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor <- function(out, t, mask_indices) { - .Call(`_torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor`, out, t, mask_indices) -} - cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar <- function(out, self, other) { .Call(`_torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar`, out, self, other) } +cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + .Call(`_torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double`, input, weight, bias, running_mean, running_var, training, momentum, eps) +} + cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double <- function(out0, out1, input, eps) { .Call(`_torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double`, out0, out1, input, eps) } @@ -13057,14 +13029,6 @@ cpp_torch_namespace_relu_out_out_Tensor_self_Tensor <- function(out, self) { .Call(`_torch_cpp_torch_namespace_relu_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor <- function(out, self, weight) { - .Call(`_torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor`, out, self, weight) -} - -cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor <- function(out0, out1, grad_output, self, weight) { - .Call(`_torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor`, out0, out1, grad_output, self, weight) -} - cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t <- function(out, grad_output, input_sizes, dim, index) { .Call(`_torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t`, out, grad_output, input_sizes, dim, index) } @@ -13105,10 +13069,6 @@ cpp_torch_namespace_sum_out_out_Tensor_self_Tensor <- function(out, self, dtype) .Call(`_torch_cpp_torch_namespace_sum_out_out_Tensor_self_Tensor`, out, self, dtype) } -cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out0, out1, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out0, out1, self, dim, correction, keepdim) -} - cpp_torch_namespace_prod_out_out_Tensor_self_Tensor <- function(out, self, dtype) { .Call(`_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor`, out, self, dtype) } @@ -13185,10 +13145,6 @@ cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef <- .Call(`_torch_cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) } -cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t <- function(out0, out1, self, dim, correction, keepdim) { - .Call(`_torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t`, out0, out1, self, dim, correction, keepdim) -} - cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor <- function(out0, out1, v, g, dim) { .Call(`_torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor`, out0, out1, v, g, dim) } @@ -13389,32 +13345,32 @@ cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t <- f .Call(`_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t`, out, self, sparse_dim) } -cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor <- function(out, self, layout, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor`, out, self, layout, blocksize, dense_dim) } -cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor <- function(out, self, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor`, out, self, dense_dim) } -cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor <- function(out, self, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor`, out, self, dense_dim) } -cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize) { - .Call(`_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize) +cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize, dense_dim) } -cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize) { - .Call(`_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize) +cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef <- function(out, self, blocksize, dense_dim) { + .Call(`_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef`, out, self, blocksize, dense_dim) } cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor <- function(out, self, dtype) { .Call(`_torch_cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor`, out, self, dtype) } -cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor <- function(out, self, padding, stride, dilation, groups) { - .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor`, out, self, padding, stride, dilation, groups) +cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor <- function(out, self, padding, stride, dilation, groups, input_size) { + .Call(`_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor`, out, self, padding, stride, dilation, groups, input_size) } cpp_torch_namespace_mkldnn_reorder_conv3d_weight_out_out_Tensor_self_Tensor <- function(out, self, padding, stride, dilation, groups) { @@ -13501,12 +13457,12 @@ cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor <- function(out, self, n .Call(`_torch_cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor`, out, self, non_blocking, memory_format) } -cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - .Call(`_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) +cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + .Call(`_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) } -cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - invisible(.Call(`_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)) +cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + invisible(.Call(`_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool`, out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)) } cpp_torch_namespace__thnn_fused_lstm_cell_out_out0_Tensor_out1_Tensor_out2_Tensor_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor <- function(out0, out1, out2, input_gates, hidden_gates, cx, input_bias, hidden_bias) { @@ -13713,10 +13669,6 @@ cpp_torch_namespace_trace_out_out_Tensor_self_Tensor <- function(out, self) { .Call(`_torch_cpp_torch_namespace_trace_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool <- function(out0, out1, self, eigenvectors, upper) { - .Call(`_torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool`, out0, out1, self, eigenvectors, upper) -} - cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool <- function(out, self, A, upper) { .Call(`_torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool`, out, self, A, upper) } @@ -13785,6 +13737,22 @@ cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scala invisible(.Call(`_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) } +cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + +cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + +cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + +cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar <- function(out, self, scalar) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar`, out, self, scalar)) +} + cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other, alpha) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other, alpha)) } @@ -13801,6 +13769,22 @@ cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_Tensor invisible(.Call(`_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) } +cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + +cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + +cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + +cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +} + cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) } @@ -13817,6 +13801,22 @@ cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_Arra invisible(.Call(`_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) } +cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + +cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + +cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + +cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar <- function(out, self, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar`, out, self, scalars)) +} + cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList <- function(out, self) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList`, out, self)) } @@ -13949,28 +13949,32 @@ cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_ invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, out, self, tensor1, tensor2, scalars)) } -cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(out, self, tensor1, tensor2, scalars) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, out, self, tensor1, tensor2, scalars)) +cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(out, self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, out, self, tensor1, tensor2, scalars)) } -cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar <- function(out, self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar`, out, self, tensor1, tensor2, scalars)) } -cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList <- function(out, self, other) { - invisible(.Call(`_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList`, out, self, other)) +cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor <- function(out, self, tensor1, tensor2, scalars) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor`, out, self, tensor1, tensor2, scalars)) } cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList <- function(out, self, ord) { invisible(.Call(`_torch_cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList`, out, self, ord)) } -cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor <- function(out, self, boundaries, out_int32, right) { - .Call(`_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor`, out, self, boundaries, out_int32, right) +cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList <- function(out, self, tensors1, weights) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList`, out, self, tensors1, weights)) +} + +cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar <- function(out, self, tensors1, weight) { + invisible(.Call(`_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar`, out, self, tensors1, weight)) } -cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor <- function(out, self, boundaries, out_int32, right) { + .Call(`_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor`, out, self, boundaries, out_int32, right) } cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar <- function(out, sorted_sequence, self, out_int32, right, side, sorter) { @@ -14013,160 +14017,172 @@ cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Ten .Call(`_torch_cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor`, out, grad_output, self) } -cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 <- function(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) { + .Call(`_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3`, out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) } -cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { + .Call(`_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) } -cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { + .Call(`_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) } -cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { + .Call(`_torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) } -cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { + .Call(`_torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) } -cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { + .Call(`_torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) } -cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble <- function(out, values, addends) { + .Call(`_torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble`, out, values, addends) } -cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, input, output_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, input, output_size, align_corners, scale_factors) +cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, align_corners, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, align_corners, scale_factors) +cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view <- function(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) { + .Call(`_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view`, out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) } -cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view <- function(out, grad, output, data, reduce, lengths, offsets, axis, initial) { + .Call(`_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view`, out, grad, output, data, reduce, lengths, offsets, axis, initial) } -cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList <- function(out, list, dtype, layout, device, pin_memory) { + .Call(`_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList`, out, list, dtype, layout, device, pin_memory) } -cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t <- function(out, self, level) { + .Call(`_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t`, out, self, level) } -cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t <- function(out, primal, tangent, level) { + .Call(`_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t`, out, primal, tangent, level) } -cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, input, output_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, input, output_size, scale_factors) +cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride, storage_offset) { + .Call(`_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride, storage_offset) } -cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { + .Call(`_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) } -cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble <- function(out, grad_output, output_size, input_size, scale_factors) { - .Call(`_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble`, out, grad_output, output_size, input_size, scale_factors) +cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor <- function(out, self, offset, dim1, dim2) { + .Call(`_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor`, out, self, offset, dim1, dim2) } -cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 <- function(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) { - .Call(`_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3`, out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask) +cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size, implicit) { + .Call(`_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size, implicit) } -cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { - .Call(`_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) +cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef <- function(out, self, dims) { + .Call(`_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef`, out, self, dims) } -cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { - .Call(`_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) +cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef <- function(out, self, size, stride) { + .Call(`_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef`, out, self, size, stride) } -cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef <- function(out, self, weight, kernel_size, bias, stride, padding, dilation) { - .Call(`_torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef`, out, self, weight, kernel_size, bias, stride, padding, dilation) +cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t <- function(out, self, dim, index) { + .Call(`_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t`, out, self, dim, index) } -cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor <- function(out, self, dim, start, end, step) { + .Call(`_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor`, out, self, dim, start, end, step) } -cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { - .Call(`_torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) +cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef <- function(out, values, addends) { - .Call(`_torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef`, out, values, addends) +cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) } -cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble <- function(out, values, addends) { - .Call(`_torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble`, out, values, addends) +cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef <- function(out, self, dim) { + .Call(`_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef`, out, self, dim) } -cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t <- function(out, self, dim0, dim1) { + .Call(`_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t`, out, self, dim0, dim1) } -cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor <- function(out, self) { - .Call(`_torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor`, out, self) +cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t <- function(out, self, dim) { + .Call(`_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t`, out, self, dim) } -cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view <- function(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) { - .Call(`_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view`, out, data, reduce, lengths, indices, offsets, axis, unsafe, initial) +cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view <- function(out, grad, output, data, reduce, lengths, offsets, axis, initial) { - .Call(`_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view`, out, grad, output, data, reduce, lengths, offsets, axis, initial) +cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList <- function(out, list, dtype, layout, device, pin_memory) { - .Call(`_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList`, out, list, dtype, layout, device, pin_memory) +cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor`, out, self) } cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor <- function(out, self) { @@ -14177,12 +14193,24 @@ cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor <- function(out, .Call(`_torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor`, out, self) } -cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double <- function(out, self, padding, output_size) { - .Call(`_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double`, out, self, padding, output_size) +cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef <- function(out, self, size) { + .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef`, out, self, size) } -cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double <- function(out, self, weight, bias, eps) { - .Call(`_torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double`, out, self, weight, bias, eps) +cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType <- function(out, self, dtype) { + .Call(`_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType`, out, self, dtype) +} + +cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t <- function(out, self, dimension, size, step) { + .Call(`_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t`, out, self, dimension, size, step) +} + +cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor <- function(out, self) { + .Call(`_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor`, out, self) +} + +cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double <- function(out, self, padding, output_size) { + .Call(`_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double`, out, self, padding, output_size) } cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor <- function(out, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type) { @@ -14221,6 +14249,14 @@ cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_Tensor .Call(`_torch_cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) } +cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool <- function(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) { + invisible(.Call(`_torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)) +} + +cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) { + .Call(`_torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool`, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf) +} + cpp_torch_generator <- function() { .Call(`_torch_cpp_torch_generator`) } diff --git a/R/distributions-multivariate_normal.R b/R/distributions-multivariate_normal.R index 7b715e5733..15e9d0a6d5 100644 --- a/R/distributions-multivariate_normal.R +++ b/R/distributions-multivariate_normal.R @@ -57,12 +57,8 @@ # Ref: https://nbviewer.jupyter.org/gist/fehiepsi/5ef8e09e61604f10607380467eb82006#Precision-to-scale_tril Lf <- linalg_cholesky(torch_flip(P, c(-2, -1))) L_inv <- torch_transpose(torch_flip(Lf, c(-2, -1)), -2, -1) - torch_linalg_solve_triangular( - L_inv, - torch_eye(head2(P$shape, -1), - upper = FALSE, - dtype = P$dtype, device = P$device), - ) + Id <- torch_eye(head2(P$shape, -1), dtype=P$dtype, device=P$device) + torch_linalg_solve_triangular(L_inv, Id, upper = FALSE) } MultivariateNormal <- R6::R6Class( diff --git a/R/gen-method.R b/R/gen-method.R index 064a0f424c..2f06516c1d 100644 --- a/R/gen-method.R +++ b/R/gen-method.R @@ -277,39 +277,52 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "_is_zerotensor", function() { args <- list() +Tensor$set("public", "_is_all_true", function() { args <- list() args <- c(list(self = self), args) expected_types <- list(self = "Tensor") nd_args <- "self" -return_types <- list(list('bool')) +return_types <- list(list('Tensor')) call_c_function( - fun_name = '_is_zerotensor', + fun_name = '_is_all_true', args = args, expected_types = expected_types, nd_args = nd_args, return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "_neg_view", function() { args <- list() +Tensor$set("public", "_is_any_true", function() { args <- list() args <- c(list(self = self), args) expected_types <- list(self = "Tensor") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( - fun_name = '_neg_view', + fun_name = '_is_any_true', args = args, expected_types = expected_types, nd_args = nd_args, return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "_nested_tensor_layer_norm", function(weight, bias, eps) { args <- mget(x = c("weight", "bias", "eps")) +Tensor$set("public", "_is_zerotensor", function() { args <- list() args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", weight = "Tensor", bias = "Tensor", eps = "double") -nd_args <- c("self", "weight", "bias", "eps") +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('bool')) +call_c_function( + fun_name = '_is_zerotensor', + args = args, + expected_types = expected_types, + nd_args = nd_args, + return_types = return_types, + fun_type = 'method' +)}) +Tensor$set("public", "_neg_view", function() { args <- list() +args <- c(list(self = self), args) +expected_types <- list(self = "Tensor") +nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( - fun_name = '_nested_tensor_layer_norm', + fun_name = '_neg_view', args = args, expected_types = expected_types, nd_args = nd_args, @@ -5269,19 +5282,6 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "prelu_backward", function(grad_output, weight) { args <- mget(x = c("grad_output", "weight")) -args <- c(list(self = self), args) -expected_types <- list(grad_output = "Tensor", self = "Tensor", weight = "Tensor") -nd_args <- c("grad_output", "self", "weight") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( - fun_name = 'prelu_backward', - args = args, - expected_types = expected_types, - nd_args = nd_args, - return_types = return_types, - fun_type = 'method' -)}) Tensor$set("public", "prod", function(dim, keepdim = FALSE, dtype = NULL) { args <- mget(x = c("dim", "keepdim", "dtype")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname"), keepdim = "bool", @@ -6417,7 +6417,8 @@ call_c_function( )}) Tensor$set("public", "squeeze", function(dim) { args <- mget(x = c("dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname")) +expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname", "IntArrayRef" +)) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -6430,7 +6431,8 @@ call_c_function( )}) Tensor$set("public", "squeeze_", function(dim) { args <- mget(x = c("dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname")) +expected_types <- list(self = "Tensor", dim = c("int64_t", "IntArrayRef", "Dimname" +)) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -6455,11 +6457,11 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "std", function(dim, correction, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) +Tensor$set("public", "std", function(dim, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "unbiased", "keepdim")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") + unbiased = "bool", keepdim = "bool") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'std', @@ -6642,19 +6644,6 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "symeig", function(eigenvectors = FALSE, upper = TRUE) { args <- mget(x = c("eigenvectors", "upper")) -args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", eigenvectors = "bool", upper = "bool") -nd_args <- "self" -return_types <- list(list("Tensor", "Tensor")) -call_c_function( - fun_name = 'symeig', - args = args, - expected_types = expected_types, - nd_args = nd_args, - return_types = return_types, - fun_type = 'method' -)}) Tensor$set("public", "t", function() { args <- list() args <- c(list(self = self), args) expected_types <- list(self = "Tensor") @@ -6841,9 +6830,10 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse", function(sparse_dim) { args <- mget(x = c("sparse_dim")) +Tensor$set("public", "to_sparse", function(layout = NULL, sparse_dim, blocksize = NULL, dense_dim = NULL) { args <- mget(x = c("layout", "sparse_dim", "blocksize", "dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", sparse_dim = "int64_t") +expected_types <- list(self = "Tensor", layout = "Layout", sparse_dim = "int64_t", + blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("self", "sparse_dim") return_types <- list(list('Tensor')) call_c_function( @@ -6854,9 +6844,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_bsc", function(blocksize) { args <- mget(x = c("blocksize")) +Tensor$set("public", "to_sparse_bsc", function(blocksize, dense_dim = NULL) { args <- mget(x = c("blocksize", "dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", blocksize = "IntArrayRef") +expected_types <- list(self = "Tensor", blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -6867,9 +6857,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_bsr", function(blocksize) { args <- mget(x = c("blocksize")) +Tensor$set("public", "to_sparse_bsr", function(blocksize, dense_dim = NULL) { args <- mget(x = c("blocksize", "dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor", blocksize = "IntArrayRef") +expected_types <- list(self = "Tensor", blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -6880,9 +6870,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_csc", function() { args <- list() +Tensor$set("public", "to_sparse_csc", function(dense_dim = NULL) { args <- mget(x = c("dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor") +expected_types <- list(self = "Tensor", dense_dim = "int64_t") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( @@ -6893,9 +6883,9 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "to_sparse_csr", function() { args <- list() +Tensor$set("public", "to_sparse_csr", function(dense_dim = NULL) { args <- mget(x = c("dense_dim")) args <- c(list(self = self), args) -expected_types <- list(self = "Tensor") +expected_types <- list(self = "Tensor", dense_dim = "int64_t") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( @@ -7223,11 +7213,11 @@ call_c_function( return_types = return_types, fun_type = 'method' )}) -Tensor$set("public", "var", function(dim, correction, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "correction", "unbiased", "keepdim")) +Tensor$set("public", "var", function(dim, unbiased = TRUE, keepdim = FALSE) { args <- mget(x = c("dim", "unbiased", "keepdim")) args <- c(list(self = self), args) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") + unbiased = "bool", keepdim = "bool") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'var', @@ -7291,7 +7281,8 @@ call_c_function( )}) Tensor$set("public", "where", function(condition, other) { args <- mget(x = c("condition", "other")) args <- c(list(self = self), args) -expected_types <- list(condition = "Tensor", self = "Tensor", other = "Tensor") +expected_types <- list(condition = "Tensor", self = "Tensor", other = c("Tensor", +"Scalar")) nd_args <- c("condition", "self", "other") return_types <- list(list('Tensor')) call_c_function( diff --git a/R/gen-namespace-docs.R b/R/gen-namespace-docs.R index 5e1ea9a307..a866808754 100644 --- a/R/gen-namespace-docs.R +++ b/R/gen-namespace-docs.R @@ -5161,59 +5161,11 @@ NULL #' @export NULL - -#' Symeig -#' -#' @section symeig(input, eigenvectors=False, upper=TRUE) -> (Tensor, Tensor) : -#' -#' This function returns eigenvalues and eigenvectors -#' of a real symmetric matrix `input` or a batch of real symmetric matrices, -#' represented by a namedtuple (eigenvalues, eigenvectors). -#' -#' This function calculates all eigenvalues (and vectors) of `input` -#' such that \eqn{\mbox{input} = V \mbox{diag}(e) V^T}. -#' -#' The boolean argument `eigenvectors` defines computation of -#' both eigenvectors and eigenvalues or eigenvalues only. -#' -#' If it is `FALSE`, only eigenvalues are computed. If it is `TRUE`, -#' both eigenvalues and eigenvectors are computed. -#' -#' Since the input matrix `input` is supposed to be symmetric, -#' only the upper triangular portion is used by default. -#' -#' If `upper` is `FALSE`, then lower triangular portion is used. -#' -#' @note The eigenvalues are returned in ascending order. If `input` is a batch of matrices, -#' then the eigenvalues of each matrix in the batch is returned in ascending order. -#' -#' @note Irrespective of the original strides, the returned matrix `V` will -#' be transposed, i.e. with strides `V.contiguous().transpose(-1, -2).stride()`. -#' -#' @note Extra care needs to be taken when backward through outputs. Such -#' operation is really only stable when all eigenvalues are distinct. -#' Otherwise, `NaN` can appear as the gradients are not properly defined. -#' -#' -#' @param self (Tensor) the input tensor of size \eqn{(*, n, n)} where `*` is zero or more batch dimensions consisting of symmetric matrices. -#' @param eigenvectors (boolean, optional) controls whether eigenvectors have to be computed -#' @param upper (boolean, optional) controls whether to consider upper-triangular or lower-triangular region -#' -#' @name torch_symeig -#' -#' @export -NULL - - #' Eig #' #' @section eig(input, eigenvectors=False, out=NULL) -> (Tensor, Tensor) : #' #' Computes the eigenvalues and eigenvectors of a real square matrix. -#' -#' @note -#' Since eigenvalues and eigenvectors might be complex, backward pass is supported only -#' for [`torch_symeig`] #' #' #' @param self (Tensor) the square matrix of shape \eqn{(n \times n)} for which the eigenvalues and eigenvectors will be computed diff --git a/R/gen-namespace-examples.R b/R/gen-namespace-examples.R index 058a03bc41..bcb7ae4d83 100644 --- a/R/gen-namespace-examples.R +++ b/R/gen-namespace-examples.R @@ -2393,29 +2393,6 @@ NULL NULL # -> triangular_solve <- -# -> symeig: 27bc25d51797de06954ef84fde11f765 <- -#' -#' @name torch_symeig -#' -#' @examples -#' -#' a = torch_randn(c(5, 5)) -#' a = a + a$t() # To make a symmetric -#' a -#' o = torch_symeig(a, eigenvectors=TRUE) -#' e = o[[1]] -#' v = o[[2]] -#' e -#' v -#' a_big = torch_randn(c(5, 2, 2)) -#' a_big = a_big + a_big$transpose(-2, -1) # To make a_big symmetric -#' o = a_big$symeig(eigenvectors=TRUE) -#' e = o[[1]] -#' v = o[[2]] -#' torch_allclose(torch_matmul(v, torch_matmul(e$diag_embed(), v$transpose(-2, -1))), a_big) -NULL -# -> symeig <- - # -> eig: 94b4710518b0b3d3bf08c75dda217258 <- #' #' @name torch_eig diff --git a/R/gen-namespace.R b/R/gen-namespace.R index 23596123a5..9a80fd6f11 100644 --- a/R/gen-namespace.R +++ b/R/gen-namespace.R @@ -844,6 +844,23 @@ fun_type = 'namespace' } +#' @rdname torch__chunk_grad_outputs_efficient_attention +torch__chunk_grad_outputs_efficient_attention <- function(query, key, value, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", is_causal = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list('bool')) +call_c_function( +fun_name = '_chunk_grad_outputs_efficient_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__coalesce torch__coalesce <- function(self) { args <- mget(x = c("self")) @@ -1360,8 +1377,9 @@ fun_type = 'namespace' torch__ctc_loss_out <- function(out0, out1, log_probs, targets, input_lengths, target_lengths, blank = 0L, zero_infinity = FALSE) { args <- mget(x = c("out0", "out1", "log_probs", "targets", "input_lengths", "target_lengths", "blank", "zero_infinity")) expected_types <- list(out0 = "Tensor", out1 = "Tensor", log_probs = "Tensor", - targets = "Tensor", input_lengths = "IntArrayRef", target_lengths = "IntArrayRef", - blank = "int64_t", zero_infinity = "bool") + targets = "Tensor", input_lengths = c("IntArrayRef", "Tensor" + ), target_lengths = c("IntArrayRef", "Tensor"), blank = "int64_t", + zero_infinity = "bool") nd_args <- c("out0", "out1", "log_probs", "targets", "input_lengths", "target_lengths" ) return_types <- list(list("Tensor", "Tensor")) @@ -1770,6 +1788,45 @@ fun_type = 'namespace' } +#' @rdname torch__efficient_attention_backward +torch__efficient_attention_backward <- function(grad_out_, query, key, value, out, logsumexp, is_causal = FALSE, chunk_grad_outputs = FALSE) { + args <- mget(x = c("grad_out_", "query", "key", "value", "out", "logsumexp", "is_causal", "chunk_grad_outputs")) +expected_types <- list(grad_out_ = "Tensor", query = "Tensor", key = "Tensor", + value = "Tensor", out = "Tensor", logsumexp = "Tensor", is_causal = "bool", + chunk_grad_outputs = "bool") +nd_args <- c("grad_out_", "query", "key", "value", "out", "logsumexp") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_efficient_attention_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__efficient_attention_forward +torch__efficient_attention_forward <- function(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp = FALSE, causal = FALSE) { + args <- mget(x = c("query", "key", "value", "cu_seqlens_q", "cu_seqlens_k", "max_seqlen_q", "compute_log_sumexp", "causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", cu_seqlens_q = "Tensor", + cu_seqlens_k = "Tensor", max_seqlen_q = "int64_t", compute_log_sumexp = "bool", + causal = "bool") +nd_args <- c("query", "key", "value", "cu_seqlens_q", "cu_seqlens_k", "max_seqlen_q" +) +return_types <- list(list("Tensor", "Tensor")) +call_c_function( +fun_name = '_efficient_attention_forward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__efficientzerotensor torch__efficientzerotensor <- function(size, options = list()) { args <- mget(x = c("size", "options")) @@ -2384,17 +2441,40 @@ fun_type = 'namespace' } -#' @rdname torch__flash_scaled_dot_product_attention -torch__flash_scaled_dot_product_attention <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal) { - args <- mget(x = c("query", "key", "value", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal")) +#' @rdname torch__flash_attention_backward +torch__flash_attention_backward <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + args <- mget(x = c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", "philox_offset")) +expected_types <- list(grad_out = "Tensor", query = "Tensor", key = "Tensor", value = "Tensor", + out = "Tensor", logsumexp = "Tensor", cum_seq_q = "Tensor", + cum_seq_k = "Tensor", max_q = "int64_t", max_k = "int64_t", + dropout_p = "double", is_causal = "bool", philox_seed = "int64_t", + philox_offset = "int64_t") +nd_args <- c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", +"cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", +"philox_offset") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_flash_attention_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__flash_attention_forward +torch__flash_attention_forward <- function(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask) { + args <- mget(x = c("query", "key", "value", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "return_debug_mask")) expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", cum_seq_q = "Tensor", cum_seq_k = "Tensor", max_q = "int64_t", max_k = "int64_t", - dropout_p = "double", is_causal = "bool") + dropout_p = "double", is_causal = "bool", return_debug_mask = "bool") nd_args <- c("query", "key", "value", "cum_seq_q", "cum_seq_k", "max_q", -"max_k", "dropout_p", "is_causal") -return_types <- list(list('Tensor')) +"max_k", "dropout_p", "is_causal", "return_debug_mask") +return_types <- list(list("Tensor", "Tensor", "int64_t", "int64_t", "Tensor")) call_c_function( -fun_name = '_flash_scaled_dot_product_attention', +fun_name = '_flash_attention_forward', args = args, expected_types = expected_types, nd_args = nd_args, @@ -2599,7 +2679,7 @@ fun_type = 'namespace' torch__foreach_addcdiv <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list('TensorList')) call_c_function( @@ -2617,7 +2697,7 @@ fun_type = 'namespace' torch__foreach_addcdiv_ <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2635,7 +2715,8 @@ fun_type = 'namespace' torch__foreach_addcdiv_out <- function(out, self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("out", "self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(out = "TensorList", self = "TensorList", tensor1 = "TensorList", - tensor2 = "TensorList", scalars = "ArrayRef", value = "Scalar") + tensor2 = "TensorList", scalars = c("ArrayRef", "Tensor" + ), value = "Scalar") nd_args <- c("out", "self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2653,7 +2734,7 @@ fun_type = 'namespace' torch__foreach_addcmul <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list('TensorList')) call_c_function( @@ -2671,7 +2752,7 @@ fun_type = 'namespace' torch__foreach_addcmul_ <- function(self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(self = "TensorList", tensor1 = "TensorList", tensor2 = "TensorList", - scalars = "ArrayRef", value = "Scalar") + scalars = c("ArrayRef", "Tensor"), value = "Scalar") nd_args <- c("self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2689,7 +2770,8 @@ fun_type = 'namespace' torch__foreach_addcmul_out <- function(out, self, tensor1, tensor2, scalars, value = 1L) { args <- mget(x = c("out", "self", "tensor1", "tensor2", "scalars", "value")) expected_types <- list(out = "TensorList", self = "TensorList", tensor1 = "TensorList", - tensor2 = "TensorList", scalars = "ArrayRef", value = "Scalar") + tensor2 = "TensorList", scalars = c("ArrayRef", "Tensor" + ), value = "Scalar") nd_args <- c("out", "self", "tensor1", "tensor2", "scalars") return_types <- list(list("void")) call_c_function( @@ -2856,6 +2938,114 @@ fun_type = 'namespace' } +#' @rdname torch__foreach_clamp_max +torch__foreach_clamp_max <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list('TensorList')) +call_c_function( +fun_name = '_foreach_clamp_max', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_max_ +torch__foreach_clamp_max_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_max_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_max_out +torch__foreach_clamp_max_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_max_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_min +torch__foreach_clamp_min <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list('TensorList')) +call_c_function( +fun_name = '_foreach_clamp_min', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_min_ +torch__foreach_clamp_min_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_min_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_clamp_min_out +torch__foreach_clamp_min_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_clamp_min_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__foreach_cos torch__foreach_cos <- function(self) { args <- mget(x = c("self")) @@ -3318,6 +3508,60 @@ fun_type = 'namespace' } +#' @rdname torch__foreach_lerp +torch__foreach_lerp <- function(self, tensors1, weight, weights) { + args <- mget(x = c("self", "tensors1", "weight", "weights")) +expected_types <- list(self = "TensorList", tensors1 = "TensorList", weight = "Scalar", + weights = "TensorList") +nd_args <- c("self", "tensors1", "weight", "weights") +return_types <- list(list('TensorList')) +call_c_function( +fun_name = '_foreach_lerp', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_lerp_ +torch__foreach_lerp_ <- function(self, tensors1, weight, weights) { + args <- mget(x = c("self", "tensors1", "weight", "weights")) +expected_types <- list(self = "TensorList", tensors1 = "TensorList", weight = "Scalar", + weights = "TensorList") +nd_args <- c("self", "tensors1", "weight", "weights") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_lerp_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__foreach_lerp_out +torch__foreach_lerp_out <- function(out, self, tensors1, weight, weights) { + args <- mget(x = c("out", "self", "tensors1", "weight", "weights")) +expected_types <- list(out = "TensorList", self = "TensorList", tensors1 = "TensorList", + weight = "Scalar", weights = "TensorList") +nd_args <- c("out", "self", "tensors1", "weight", "weights") +return_types <- list(list("void")) +call_c_function( +fun_name = '_foreach_lerp_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__foreach_lgamma torch__foreach_lgamma <- function(self) { args <- mget(x = c("self")) @@ -3574,10 +3818,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_maximum -torch__foreach_maximum <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_maximum <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list('TensorList')) call_c_function( fun_name = '_foreach_maximum', @@ -3591,10 +3836,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_maximum_ -torch__foreach_maximum_ <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_maximum_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_maximum_', @@ -3608,10 +3854,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_maximum_out -torch__foreach_maximum_out <- function(out, self, other) { - args <- mget(x = c("out", "self", "other")) -expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList") -nd_args <- c("out", "self", "other") +torch__foreach_maximum_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_maximum_out', @@ -3625,10 +3872,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_minimum -torch__foreach_minimum <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_minimum <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list('TensorList')) call_c_function( fun_name = '_foreach_minimum', @@ -3642,10 +3890,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_minimum_ -torch__foreach_minimum_ <- function(self, other) { - args <- mget(x = c("self", "other")) -expected_types <- list(self = "TensorList", other = "TensorList") -nd_args <- c("self", "other") +torch__foreach_minimum_ <- function(self, other, scalar, scalars) { + args <- mget(x = c("self", "other", "scalar", "scalars")) +expected_types <- list(self = "TensorList", other = "TensorList", scalar = "Scalar", + scalars = "ArrayRef") +nd_args <- c("self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_minimum_', @@ -3659,10 +3908,11 @@ fun_type = 'namespace' #' @rdname torch__foreach_minimum_out -torch__foreach_minimum_out <- function(out, self, other) { - args <- mget(x = c("out", "self", "other")) -expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList") -nd_args <- c("out", "self", "other") +torch__foreach_minimum_out <- function(out, self, other, scalar, scalars) { + args <- mget(x = c("out", "self", "other", "scalar", "scalars")) +expected_types <- list(out = "TensorList", self = "TensorList", other = "TensorList", + scalar = "Scalar", scalars = "ArrayRef") +nd_args <- c("out", "self", "other", "scalar", "scalars") return_types <- list(list("void")) call_c_function( fun_name = '_foreach_minimum_out', @@ -4450,6 +4700,78 @@ fun_type = 'namespace' } +#' @rdname torch__fused_adamw +torch__fused_adamw <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale = list(), found_inf = list()) { + args <- mget(x = c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", "state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", "amsgrad", "maximize", "grad_scale", "found_inf")) +expected_types <- list(self = "TensorList", grads = "TensorList", exp_avgs = "TensorList", + exp_avg_sqs = "TensorList", max_exp_avg_sqs = "TensorList", + state_steps = "TensorList", lr = "double", beta1 = "double", + beta2 = "double", weight_decay = "double", eps = "double", + amsgrad = "bool", maximize = "bool", grad_scale = "Tensor", + found_inf = "Tensor") +nd_args <- c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", +"state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", +"amsgrad", "maximize") +return_types <- list(list("TensorList", "TensorList", "TensorList", "TensorList", "TensorList")) +call_c_function( +fun_name = '_fused_adamw', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__fused_adamw_ +torch__fused_adamw_ <- function(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale = list(), found_inf = list()) { + args <- mget(x = c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", "state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", "amsgrad", "maximize", "grad_scale", "found_inf")) +expected_types <- list(self = "TensorList", grads = "TensorList", exp_avgs = "TensorList", + exp_avg_sqs = "TensorList", max_exp_avg_sqs = "TensorList", + state_steps = "TensorList", lr = "double", beta1 = "double", + beta2 = "double", weight_decay = "double", eps = "double", + amsgrad = "bool", maximize = "bool", grad_scale = "Tensor", + found_inf = "Tensor") +nd_args <- c("self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", +"state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", +"amsgrad", "maximize") +return_types <- list(list("void")) +call_c_function( +fun_name = '_fused_adamw_', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__fused_adamw_out +torch__fused_adamw_out <- function(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale = list(), found_inf = list()) { + args <- mget(x = c("out", "self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", "state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", "amsgrad", "maximize", "grad_scale", "found_inf")) +expected_types <- list(out = "TensorList", self = "TensorList", grads = "TensorList", + exp_avgs = "TensorList", exp_avg_sqs = "TensorList", max_exp_avg_sqs = "TensorList", + state_steps = "TensorList", lr = "double", beta1 = "double", + beta2 = "double", weight_decay = "double", eps = "double", + amsgrad = "bool", maximize = "bool", grad_scale = "Tensor", + found_inf = "Tensor") +nd_args <- c("out", "self", "grads", "exp_avgs", "exp_avg_sqs", "max_exp_avg_sqs", +"state_steps", "lr", "beta1", "beta2", "weight_decay", "eps", +"amsgrad", "maximize") +return_types <- list(list("void")) +call_c_function( +fun_name = '_fused_adamw_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__fused_dropout torch__fused_dropout <- function(self, p, generator = NULL) { args <- mget(x = c("self", "p", "generator")) @@ -4554,6 +4876,24 @@ fun_type = 'namespace' } +#' @rdname torch__fused_sdp_choice +torch__fused_sdp_choice <- function(query, key, value, attn_mask = list(), dropout_p = 0L, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", + dropout_p = "double", is_causal = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list('int64_t')) +call_c_function( +fun_name = '_fused_sdp_choice', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__fw_primal_copy torch__fw_primal_copy <- function(self, level) { args <- mget(x = c("self", "level")) @@ -4893,6 +5233,40 @@ fun_type = 'namespace' } +#' @rdname torch__is_all_true +torch__is_all_true <- function(self) { + args <- mget(x = c("self")) +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_is_all_true', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__is_any_true +torch__is_any_true <- function(self) { + args <- mget(x = c("self")) +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_is_any_true', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__is_zerotensor torch__is_zerotensor <- function(self) { args <- mget(x = c("self")) @@ -5231,7 +5605,7 @@ expected_types <- list(input = "Tensor", hx = "TensorList", params = "TensorList train = "bool", bidirectional = "bool", batch_first = "bool") nd_args <- c("input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first") -return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) call_c_function( fun_name = '_lstm_mps', args = args, @@ -5244,16 +5618,17 @@ fun_type = 'namespace' #' @rdname torch__lstm_mps_out -torch__lstm_mps_out <- function(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - args <- mget(x = c("out0", "out1", "out2", "out3", "out4", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) +torch__lstm_mps_out <- function(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + args <- mget(x = c("out0", "out1", "out2", "out3", "out4", "out5", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) expected_types <- list(out0 = "Tensor", out1 = "Tensor", out2 = "Tensor", out3 = "Tensor", - out4 = "Tensor", input = "Tensor", hx = "TensorList", params = "TensorList", - has_biases = "bool", num_layers = "int64_t", dropout = "double", - train = "bool", bidirectional = "bool", batch_first = "bool") -nd_args <- c("out0", "out1", "out2", "out3", "out4", "input", "hx", "params", -"has_biases", "num_layers", "dropout", "train", "bidirectional", + out4 = "Tensor", out5 = "Tensor", input = "Tensor", hx = "TensorList", + params = "TensorList", has_biases = "bool", num_layers = "int64_t", + dropout = "double", train = "bool", bidirectional = "bool", + batch_first = "bool") +nd_args <- c("out0", "out1", "out2", "out3", "out4", "out5", "input", "hx", +"params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first") -return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) call_c_function( fun_name = '_lstm_mps_out', args = args, @@ -5672,15 +6047,17 @@ fun_type = 'namespace' } -#' @rdname torch__mps_max_pool2d -torch__mps_max_pool2d <- function(self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(self = "Tensor", kernel_size = "IntArrayRef", stride = "IntArrayRef", - padding = "IntArrayRef", dilation = "IntArrayRef", ceil_mode = "bool") -nd_args <- c("self", "kernel_size") -return_types <- list(list('Tensor')) +#' @rdname torch__native_batch_norm_legit +torch__native_batch_norm_legit <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + args <- mget(x = c("input", "weight", "bias", "running_mean", "running_var", "training", "momentum", "eps")) +expected_types <- list(input = "Tensor", weight = "Tensor", bias = "Tensor", running_mean = "Tensor", + running_var = "Tensor", training = "bool", momentum = "double", + eps = "double") +nd_args <- c("input", "weight", "bias", "running_mean", "running_var", "training", +"momentum", "eps") +return_types <- list(list("Tensor", "Tensor", "Tensor")) call_c_function( -fun_name = '_mps_max_pool2d', +fun_name = '_native_batch_norm_legit', args = args, expected_types = expected_types, nd_args = nd_args, @@ -5690,16 +6067,38 @@ fun_type = 'namespace' } -#' @rdname torch__mps_max_pool2d_out -torch__mps_max_pool2d_out <- function(out, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("out", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(out = "Tensor", self = "Tensor", kernel_size = "IntArrayRef", - stride = "IntArrayRef", padding = "IntArrayRef", dilation = "IntArrayRef", - ceil_mode = "bool") -nd_args <- c("out", "self", "kernel_size") -return_types <- list(list('Tensor')) +#' @rdname torch__native_batch_norm_legit_functional +torch__native_batch_norm_legit_functional <- function(input, weight, bias, running_mean, running_var, training, momentum, eps) { + args <- mget(x = c("input", "weight", "bias", "running_mean", "running_var", "training", "momentum", "eps")) +expected_types <- list(input = "Tensor", weight = "Tensor", bias = "Tensor", running_mean = "Tensor", + running_var = "Tensor", training = "bool", momentum = "double", + eps = "double") +nd_args <- c("input", "weight", "bias", "running_mean", "running_var", "training", +"momentum", "eps") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) call_c_function( -fun_name = '_mps_max_pool2d_out', +fun_name = '_native_batch_norm_legit_functional', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__native_batch_norm_legit_out +torch__native_batch_norm_legit_out <- function(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps) { + args <- mget(x = c("out", "save_mean", "save_invstd", "input", "weight", "bias", "running_mean", "running_var", "training", "momentum", "eps")) +expected_types <- list(out = "Tensor", save_mean = "Tensor", save_invstd = "Tensor", + input = "Tensor", weight = "Tensor", bias = "Tensor", running_mean = "Tensor", + running_var = "Tensor", training = "bool", momentum = "double", + eps = "double") +nd_args <- c("out", "save_mean", "save_invstd", "input", "weight", "bias", +"running_mean", "running_var", "training", "momentum", "eps") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_native_batch_norm_legit_out', args = args, expected_types = expected_types, nd_args = nd_args, @@ -6041,24 +6440,6 @@ fun_type = 'namespace' } -#' @rdname torch__nested_tensor_layer_norm_out -torch__nested_tensor_layer_norm_out <- function(out, self, weight, bias, eps) { - args <- mget(x = c("out", "self", "weight", "bias", "eps")) -expected_types <- list(out = "Tensor", self = "Tensor", weight = "Tensor", bias = "Tensor", - eps = "double") -nd_args <- c("out", "self", "weight", "bias", "eps") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = '_nested_tensor_layer_norm_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch__nested_tensor_size_out torch__nested_tensor_size_out <- function(out, self) { args <- mget(x = c("out", "self")) @@ -6444,6 +6825,40 @@ fun_type = 'namespace' } +#' @rdname torch__prelu_kernel +torch__prelu_kernel <- function(self, weight) { + args <- mget(x = c("self", "weight")) +expected_types <- list(self = "Tensor", weight = "Tensor") +nd_args <- c("self", "weight") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_prelu_kernel', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__prelu_kernel_backward +torch__prelu_kernel_backward <- function(grad_output, self, weight) { + args <- mget(x = c("grad_output", "self", "weight")) +expected_types <- list(grad_output = "Tensor", self = "Tensor", weight = "Tensor") +nd_args <- c("grad_output", "self", "weight") +return_types <- list(list("Tensor", "Tensor")) +call_c_function( +fun_name = '_prelu_kernel_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__remove_batch_dim torch__remove_batch_dim <- function(self, level, batch_size, out_dim) { args <- mget(x = c("self", "level", "batch_size", "out_dim")) @@ -6513,6 +6928,23 @@ fun_type = 'namespace' } +#' @rdname torch__reshape_copy +torch__reshape_copy <- function(self, size) { + args <- mget(x = c("self", "size")) +expected_types <- list(self = "Tensor", size = "IntArrayRef") +nd_args <- c("self", "size") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_reshape_copy', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__reshape_from_tensor torch__reshape_from_tensor <- function(self, shape) { args <- mget(x = c("self", "shape")) @@ -6667,15 +7099,15 @@ fun_type = 'namespace' } -#' @rdname torch__scaled_dot_product_attention_forward -torch__scaled_dot_product_attention_forward <- function(query, key, value, attn_mask = list(), dropout_p = 0L, need_attn_weights = FALSE, is_causal = FALSE) { - args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "need_attn_weights", "is_causal")) +#' @rdname torch__scaled_dot_product_attention_math +torch__scaled_dot_product_attention_math <- function(query, key, value, attn_mask = list(), dropout_p = 0L, is_causal = FALSE, dropout_mask = list()) { + args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "is_causal", "dropout_mask")) expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", - dropout_p = "double", need_attn_weights = "bool", is_causal = "bool") + dropout_p = "double", is_causal = "bool", dropout_mask = "Tensor") nd_args <- c("query", "key", "value") return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_scaled_dot_product_attention_forward', +fun_name = '_scaled_dot_product_attention_math', args = args, expected_types = expected_types, nd_args = nd_args, @@ -6685,15 +7117,75 @@ fun_type = 'namespace' } -#' @rdname torch__scaled_dot_product_attention_math -torch__scaled_dot_product_attention_math <- function(query, key, value, attn_mask = list(), dropout_p = 0L, need_attn_weights = FALSE, is_causal = FALSE) { - args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "need_attn_weights", "is_causal")) -expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", - dropout_p = "double", need_attn_weights = "bool", is_causal = "bool") -nd_args <- c("query", "key", "value") +#' @rdname torch__scaled_dot_product_efficient_attention +torch__scaled_dot_product_efficient_attention <- function(query, key, value, compute_log_sumexp, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "compute_log_sumexp", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", compute_log_sumexp = "bool", + is_causal = "bool") +nd_args <- c("query", "key", "value", "compute_log_sumexp") return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_scaled_dot_product_attention_math', +fun_name = '_scaled_dot_product_efficient_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__scaled_dot_product_efficient_attention_backward +torch__scaled_dot_product_efficient_attention_backward <- function(grad_out_, query, key, value, out, logsumexp, is_causal = FALSE, chunk_grad_outputs = FALSE) { + args <- mget(x = c("grad_out_", "query", "key", "value", "out", "logsumexp", "is_causal", "chunk_grad_outputs")) +expected_types <- list(grad_out_ = "Tensor", query = "Tensor", key = "Tensor", + value = "Tensor", out = "Tensor", logsumexp = "Tensor", is_causal = "bool", + chunk_grad_outputs = "bool") +nd_args <- c("grad_out_", "query", "key", "value", "out", "logsumexp") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_scaled_dot_product_efficient_attention_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__scaled_dot_product_flash_attention +torch__scaled_dot_product_flash_attention <- function(query, key, value, dropout_p = 0L, is_causal = FALSE, return_debug_mask = FALSE) { + args <- mget(x = c("query", "key", "value", "dropout_p", "is_causal", "return_debug_mask")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", dropout_p = "double", + is_causal = "bool", return_debug_mask = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "int64_t", "int64_t", "int64_t", "int64_t", "Tensor")) +call_c_function( +fun_name = '_scaled_dot_product_flash_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch__scaled_dot_product_flash_attention_backward +torch__scaled_dot_product_flash_attention_backward <- function(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset) { + args <- mget(x = c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", "cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", "philox_offset")) +expected_types <- list(grad_out = "Tensor", query = "Tensor", key = "Tensor", value = "Tensor", + out = "Tensor", logsumexp = "Tensor", cum_seq_q = "Tensor", + cum_seq_k = "Tensor", max_q = "int64_t", max_k = "int64_t", + dropout_p = "double", is_causal = "bool", philox_seed = "int64_t", + philox_offset = "int64_t") +nd_args <- c("grad_out", "query", "key", "value", "out", "logsumexp", "cum_seq_q", +"cum_seq_k", "max_q", "max_k", "dropout_p", "is_causal", "philox_seed", +"philox_offset") +return_types <- list(list("Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = '_scaled_dot_product_flash_attention_backward', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7392,14 +7884,14 @@ fun_type = 'namespace' } -#' @rdname torch__sparse_mask_helper -torch__sparse_mask_helper <- function(t, mask_indices) { - args <- mget(x = c("t", "mask_indices")) -expected_types <- list(t = "Tensor", mask_indices = "Tensor") -nd_args <- c("t", "mask_indices") +#' @rdname torch__sparse_mm +torch__sparse_mm <- function(sparse, dense, reduce) { + args <- mget(x = c("sparse", "dense", "reduce")) +expected_types <- list(sparse = "Tensor", dense = "Tensor", reduce = "c10::string_view") +nd_args <- c("sparse", "dense", "reduce") return_types <- list(list('Tensor')) call_c_function( -fun_name = '_sparse_mask_helper', +fun_name = '_sparse_mm', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7409,14 +7901,14 @@ fun_type = 'namespace' } -#' @rdname torch__sparse_mask_helper_out -torch__sparse_mask_helper_out <- function(out, t, mask_indices) { - args <- mget(x = c("out", "t", "mask_indices")) -expected_types <- list(out = "Tensor", t = "Tensor", mask_indices = "Tensor") -nd_args <- c("out", "t", "mask_indices") -return_types <- list(list('Tensor')) +#' @rdname torch__sparse_mm_reduce_impl +torch__sparse_mm_reduce_impl <- function(self, other, reduce) { + args <- mget(x = c("self", "other", "reduce")) +expected_types <- list(self = "Tensor", other = "Tensor", reduce = "c10::string_view") +nd_args <- c("self", "other", "reduce") +return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_sparse_mask_helper_out', +fun_name = '_sparse_mm_reduce_impl', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7426,14 +7918,16 @@ fun_type = 'namespace' } -#' @rdname torch__sparse_mm -torch__sparse_mm <- function(sparse, dense) { - args <- mget(x = c("sparse", "dense")) -expected_types <- list(sparse = "Tensor", dense = "Tensor") -nd_args <- c("sparse", "dense") -return_types <- list(list('Tensor')) +#' @rdname torch__sparse_mm_reduce_impl_backward +torch__sparse_mm_reduce_impl_backward <- function(self, grad_out, weight, reduce, arg_out, output_mask) { + args <- mget(x = c("self", "grad_out", "weight", "reduce", "arg_out", "output_mask")) +expected_types <- list(self = "Tensor", grad_out = "Tensor", weight = "Tensor", + reduce = "c10::string_view", arg_out = "Tensor", output_mask = "::std::array") +nd_args <- c("self", "grad_out", "weight", "reduce", "arg_out", "output_mask" +) +return_types <- list(list("Tensor", "Tensor")) call_c_function( -fun_name = '_sparse_mm', +fun_name = '_sparse_mm_reduce_impl_backward', args = args, expected_types = expected_types, nd_args = nd_args, @@ -7754,41 +8248,6 @@ fun_type = 'namespace' } -#' @rdname torch__symeig_helper -torch__symeig_helper <- function(self, eigenvectors, upper) { - args <- mget(x = c("self", "eigenvectors", "upper")) -expected_types <- list(self = "Tensor", eigenvectors = "bool", upper = "bool") -nd_args <- c("self", "eigenvectors", "upper") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = '_symeig_helper', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch__symeig_helper_out -torch__symeig_helper_out <- function(out0, out1, self, eigenvectors, upper) { - args <- mget(x = c("out0", "out1", "self", "eigenvectors", "upper")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", eigenvectors = "bool", - upper = "bool") -nd_args <- c("out0", "out1", "self", "eigenvectors", "upper") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = '_symeig_helper_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch__test_autograd_multiple_dispatch torch__test_autograd_multiple_dispatch <- function(self, b) { args <- mget(x = c("self", "b")) @@ -7874,6 +8333,23 @@ fun_type = 'namespace' } +#' @rdname torch__test_check_tensor +torch__test_check_tensor <- function(self) { + args <- mget(x = c("self")) +expected_types <- list(self = "Tensor") +nd_args <- "self" +return_types <- list(list('Tensor')) +call_c_function( +fun_name = '_test_check_tensor', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch__test_optional_filled_intlist torch__test_optional_filled_intlist <- function(values, addends) { args <- mget(x = c("values", "addends")) @@ -8304,40 +8780,6 @@ fun_type = 'namespace' } -#' @rdname torch__torch_cuda_cu_linker_symbol_op -torch__torch_cuda_cu_linker_symbol_op <- function(self) { - args <- mget(x = c("self")) -expected_types <- list(self = "Tensor") -nd_args <- "self" -return_types <- list(list('Tensor')) -call_c_function( -fun_name = '_torch_cuda_cu_linker_symbol_op', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch__torch_cuda_cu_linker_symbol_op_out -torch__torch_cuda_cu_linker_symbol_op_out <- function(out, self) { - args <- mget(x = c("out", "self")) -expected_types <- list(out = "Tensor", self = "Tensor") -nd_args <- c("out", "self") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = '_torch_cuda_cu_linker_symbol_op_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch__transform_bias_rescale_qkv torch__transform_bias_rescale_qkv <- function(qkv, qkv_bias, num_heads) { args <- mget(x = c("qkv", "qkv_bias", "num_heads")) @@ -8737,13 +9179,12 @@ fun_type = 'namespace' #' @rdname torch__upsample_bicubic2d_aa_backward -torch__upsample_bicubic2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch__upsample_bicubic2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bicubic2d_aa_backward', @@ -8757,14 +9198,13 @@ fun_type = 'namespace' #' @rdname torch__upsample_bicubic2d_aa_backward_out -torch__upsample_bicubic2d_aa_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch__upsample_bicubic2d_aa_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bicubic2d_aa_backward_out', @@ -8778,13 +9218,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_bicubic2d_aa_out -torch__upsample_bicubic2d_aa_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch__upsample_bicubic2d_aa_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bicubic2d_aa_out', @@ -8818,13 +9256,12 @@ fun_type = 'namespace' #' @rdname torch__upsample_bilinear2d_aa_backward -torch__upsample_bilinear2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch__upsample_bilinear2d_aa_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bilinear2d_aa_backward', @@ -8838,14 +9275,13 @@ fun_type = 'namespace' #' @rdname torch__upsample_bilinear2d_aa_backward_out -torch__upsample_bilinear2d_aa_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch__upsample_bilinear2d_aa_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bilinear2d_aa_backward_out', @@ -8859,13 +9295,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_bilinear2d_aa_out -torch__upsample_bilinear2d_aa_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch__upsample_bilinear2d_aa_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_bilinear2d_aa_out', @@ -8897,12 +9331,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact1d_backward -torch__upsample_nearest_exact1d_backward <- function(grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales")) +torch__upsample_nearest_exact1d_backward <- function(grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact1d_backward', @@ -8916,13 +9349,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact1d_backward_out -torch__upsample_nearest_exact1d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch__upsample_nearest_exact1d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact1d_backward_out', @@ -8936,11 +9367,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact1d_out -torch__upsample_nearest_exact1d_out <- function(out, input, self, output_size, scale_factors, scales = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch__upsample_nearest_exact1d_out <- function(out, self, output_size, scales = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact1d_out', @@ -8973,13 +9404,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact2d_backward -torch__upsample_nearest_exact2d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) +torch__upsample_nearest_exact2d_backward <- function(grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact2d_backward', @@ -8993,14 +9422,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact2d_backward_out -torch__upsample_nearest_exact2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch__upsample_nearest_exact2d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_h = "double", scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact2d_backward_out', @@ -9014,12 +9440,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact2d_out -torch__upsample_nearest_exact2d_out <- function(out, input, self, output_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch__upsample_nearest_exact2d_out <- function(out, self, output_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact2d_out', @@ -9052,13 +9477,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact3d_backward -torch__upsample_nearest_exact3d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) +torch__upsample_nearest_exact3d_backward <- function(grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact3d_backward', @@ -9072,14 +9495,12 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact3d_backward_out -torch__upsample_nearest_exact3d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch__upsample_nearest_exact3d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact3d_backward_out', @@ -9093,12 +9514,11 @@ fun_type = 'namespace' #' @rdname torch__upsample_nearest_exact3d_out -torch__upsample_nearest_exact3d_out <- function(out, input, self, output_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch__upsample_nearest_exact3d_out <- function(out, self, output_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = '_upsample_nearest_exact3d_out', @@ -15173,23 +15593,6 @@ fun_type = 'namespace' } -#' @rdname torch_diag_backward -torch_diag_backward <- function(grad, input_sizes, diagonal) { - args <- mget(x = c("grad", "input_sizes", "diagonal")) -expected_types <- list(grad = "Tensor", input_sizes = "IntArrayRef", diagonal = "int64_t") -nd_args <- c("grad", "input_sizes", "diagonal") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'diag_backward', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_diag_embed torch_diag_embed <- function(self, offset = 0L, dim1 = -2L, dim2 = -1L) { args <- mget(x = c("self", "offset", "dim1", "dim2")) @@ -23991,16 +24394,16 @@ fun_type = 'namespace' #' @rdname torch_lstm_mps_backward -torch_lstm_mps_backward <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - args <- mget(x = c("grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) +torch_lstm_mps_backward <- function(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + args <- mget(x = c("grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "layersOutputs", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) expected_types <- list(grad_y = "Tensor", grad_hy = "Tensor", grad_cy = "Tensor", z_state = "Tensor", cell_state_fwd = "Tensor", input = "Tensor", - hx = "TensorList", params = "TensorList", has_biases = "bool", - num_layers = "int64_t", dropout = "double", train = "bool", - bidirectional = "bool", batch_first = "bool") + layersOutputs = "Tensor", hx = "TensorList", params = "TensorList", + has_biases = "bool", num_layers = "int64_t", dropout = "double", + train = "bool", bidirectional = "bool", batch_first = "bool") nd_args <- c("grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", -"input", "hx", "params", "has_biases", "num_layers", "dropout", -"train", "bidirectional", "batch_first") +"input", "layersOutputs", "hx", "params", "has_biases", "num_layers", +"dropout", "train", "bidirectional", "batch_first") return_types <- list(list("Tensor", "TensorList", "TensorList")) call_c_function( fun_name = 'lstm_mps_backward', @@ -24014,17 +24417,18 @@ fun_type = 'namespace' #' @rdname torch_lstm_mps_backward_out -torch_lstm_mps_backward_out <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { - args <- mget(x = c("out0", "out1", "out2", "grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) +torch_lstm_mps_backward_out <- function(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first) { + args <- mget(x = c("out0", "out1", "out2", "grad_y", "grad_hy", "grad_cy", "z_state", "cell_state_fwd", "input", "layersOutputs", "hx", "params", "has_biases", "num_layers", "dropout", "train", "bidirectional", "batch_first")) expected_types <- list(out0 = "Tensor", out1 = "TensorList", out2 = "TensorList", grad_y = "Tensor", grad_hy = "Tensor", grad_cy = "Tensor", z_state = "Tensor", cell_state_fwd = "Tensor", input = "Tensor", - hx = "TensorList", params = "TensorList", has_biases = "bool", - num_layers = "int64_t", dropout = "double", train = "bool", - bidirectional = "bool", batch_first = "bool") + layersOutputs = "Tensor", hx = "TensorList", params = "TensorList", + has_biases = "bool", num_layers = "int64_t", dropout = "double", + train = "bool", bidirectional = "bool", batch_first = "bool") nd_args <- c("out0", "out1", "out2", "grad_y", "grad_hy", "grad_cy", "z_state", -"cell_state_fwd", "input", "hx", "params", "has_biases", "num_layers", -"dropout", "train", "bidirectional", "batch_first") +"cell_state_fwd", "input", "layersOutputs", "hx", "params", "has_biases", +"num_layers", "dropout", "train", "bidirectional", "batch_first" +) return_types <- list(list("void")) call_c_function( fun_name = 'lstm_mps_backward_out', @@ -24508,6 +24912,44 @@ fun_type = 'namespace' } +#' @rdname torch_max_pool2d_backward +torch_max_pool2d_backward <- function(grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { + args <- mget(x = c("grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) +expected_types <- list(grad_output = "Tensor", self = "Tensor", kernel_size = "IntArrayRef", + stride = "IntArrayRef", padding = "IntArrayRef", dilation = "IntArrayRef", + ceil_mode = "bool") +nd_args <- c("grad_output", "self", "kernel_size") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = 'max_pool2d_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_max_pool2d_backward_out +torch_max_pool2d_backward_out <- function(out, grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { + args <- mget(x = c("out", "grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) +expected_types <- list(out = "Tensor", grad_output = "Tensor", self = "Tensor", + kernel_size = "IntArrayRef", stride = "IntArrayRef", padding = "IntArrayRef", + dilation = "IntArrayRef", ceil_mode = "bool") +nd_args <- c("out", "grad_output", "self", "kernel_size") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = 'max_pool2d_backward_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname .torch_max_pool2d_with_indices .torch_max_pool2d_with_indices <- function(self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { args <- mget(x = c("self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) @@ -25758,10 +26200,10 @@ fun_type = 'namespace' #' @rdname torch_mkldnn_reorder_conv2d_weight -torch_mkldnn_reorder_conv2d_weight <- function(self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L) { - args <- mget(x = c("self", "padding", "stride", "dilation", "groups")) +torch_mkldnn_reorder_conv2d_weight <- function(self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L, input_size = NULL) { + args <- mget(x = c("self", "padding", "stride", "dilation", "groups", "input_size")) expected_types <- list(self = "Tensor", padding = "IntArrayRef", stride = "IntArrayRef", - dilation = "IntArrayRef", groups = "int64_t") + dilation = "IntArrayRef", groups = "int64_t", input_size = "IntArrayRef") nd_args <- "self" return_types <- list(list('Tensor')) call_c_function( @@ -25776,10 +26218,11 @@ fun_type = 'namespace' #' @rdname torch_mkldnn_reorder_conv2d_weight_out -torch_mkldnn_reorder_conv2d_weight_out <- function(out, self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L) { - args <- mget(x = c("out", "self", "padding", "stride", "dilation", "groups")) +torch_mkldnn_reorder_conv2d_weight_out <- function(out, self, padding = 0L, stride = 1L, dilation = 1L, groups = 1L, input_size = NULL) { + args <- mget(x = c("out", "self", "padding", "stride", "dilation", "groups", "input_size")) expected_types <- list(out = "Tensor", self = "Tensor", padding = "IntArrayRef", - stride = "IntArrayRef", dilation = "IntArrayRef", groups = "int64_t") + stride = "IntArrayRef", dilation = "IntArrayRef", groups = "int64_t", + input_size = "IntArrayRef") nd_args <- c("out", "self") return_types <- list(list('Tensor')) call_c_function( @@ -25829,6 +26272,111 @@ fun_type = 'namespace' } +#' @rdname torch_mkldnn_rnn_layer +torch_mkldnn_rnn_layer <- function(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + args <- mget(x = c("input", "weight0", "weight1", "weight2", "weight3", "hx_", "cx_", "reverse", "batch_sizes", "mode", "hidden_size", "num_layers", "has_biases", "bidirectional", "batch_first", "train")) +expected_types <- list(input = "Tensor", weight0 = "Tensor", weight1 = "Tensor", + weight2 = "Tensor", weight3 = "Tensor", hx_ = "Tensor", cx_ = "Tensor", + reverse = "bool", batch_sizes = "IntArrayRef", mode = "int64_t", + hidden_size = "int64_t", num_layers = "int64_t", has_biases = "bool", + bidirectional = "bool", batch_first = "bool", train = "bool") +nd_args <- c("input", "weight0", "weight1", "weight2", "weight3", "hx_", +"cx_", "reverse", "batch_sizes", "mode", "hidden_size", "num_layers", +"has_biases", "bidirectional", "batch_first", "train") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_mkldnn_rnn_layer_backward +torch_mkldnn_rnn_layer_backward <- function(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + args <- mget(x = c("input", "weight1", "weight2", "weight3", "weight4", "hx_", "cx_tmp", "output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", "reverse", "mode", "hidden_size", "num_layers", "has_biases", "train", "bidirectional", "batch_sizes", "batch_first", "workspace")) +expected_types <- list(input = "Tensor", weight1 = "Tensor", weight2 = "Tensor", + weight3 = "Tensor", weight4 = "Tensor", hx_ = "Tensor", cx_tmp = "Tensor", + output = "Tensor", hy_ = "Tensor", cy_ = "Tensor", grad_output = "Tensor", + grad_hy = "Tensor", grad_cy = "Tensor", reverse = "bool", + mode = "int64_t", hidden_size = "int64_t", num_layers = "int64_t", + has_biases = "bool", train = "bool", bidirectional = "bool", + batch_sizes = "IntArrayRef", batch_first = "bool", workspace = "Tensor") +nd_args <- c("input", "weight1", "weight2", "weight3", "weight4", "hx_", +"cx_tmp", "output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", +"reverse", "mode", "hidden_size", "num_layers", "has_biases", +"train", "bidirectional", "batch_sizes", "batch_first", "workspace" +) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer_backward', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_mkldnn_rnn_layer_backward_out +torch_mkldnn_rnn_layer_backward_out <- function(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace) { + args <- mget(x = c("out0", "out1", "out2", "out3", "out4", "out5", "out6", "input", "weight1", "weight2", "weight3", "weight4", "hx_", "cx_tmp", "output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", "reverse", "mode", "hidden_size", "num_layers", "has_biases", "train", "bidirectional", "batch_sizes", "batch_first", "workspace")) +expected_types <- list(out0 = "Tensor", out1 = "Tensor", out2 = "Tensor", out3 = "Tensor", + out4 = "Tensor", out5 = "Tensor", out6 = "Tensor", input = "Tensor", + weight1 = "Tensor", weight2 = "Tensor", weight3 = "Tensor", + weight4 = "Tensor", hx_ = "Tensor", cx_tmp = "Tensor", output = "Tensor", + hy_ = "Tensor", cy_ = "Tensor", grad_output = "Tensor", grad_hy = "Tensor", + grad_cy = "Tensor", reverse = "bool", mode = "int64_t", hidden_size = "int64_t", + num_layers = "int64_t", has_biases = "bool", train = "bool", + bidirectional = "bool", batch_sizes = "IntArrayRef", batch_first = "bool", + workspace = "Tensor") +nd_args <- c("out0", "out1", "out2", "out3", "out4", "out5", "out6", "input", +"weight1", "weight2", "weight3", "weight4", "hx_", "cx_tmp", +"output", "hy_", "cy_", "grad_output", "grad_hy", "grad_cy", +"reverse", "mode", "hidden_size", "num_layers", "has_biases", +"train", "bidirectional", "batch_sizes", "batch_first", "workspace" +) +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer_backward_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + +#' @rdname torch_mkldnn_rnn_layer_out +torch_mkldnn_rnn_layer_out <- function(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train) { + args <- mget(x = c("out0", "out1", "out2", "out3", "input", "weight0", "weight1", "weight2", "weight3", "hx_", "cx_", "reverse", "batch_sizes", "mode", "hidden_size", "num_layers", "has_biases", "bidirectional", "batch_first", "train")) +expected_types <- list(out0 = "Tensor", out1 = "Tensor", out2 = "Tensor", out3 = "Tensor", + input = "Tensor", weight0 = "Tensor", weight1 = "Tensor", + weight2 = "Tensor", weight3 = "Tensor", hx_ = "Tensor", cx_ = "Tensor", + reverse = "bool", batch_sizes = "IntArrayRef", mode = "int64_t", + hidden_size = "int64_t", num_layers = "int64_t", has_biases = "bool", + bidirectional = "bool", batch_first = "bool", train = "bool") +nd_args <- c("out0", "out1", "out2", "out3", "input", "weight0", "weight1", +"weight2", "weight3", "hx_", "cx_", "reverse", "batch_sizes", +"mode", "hidden_size", "num_layers", "has_biases", "bidirectional", +"batch_first", "train") +return_types <- list(list("Tensor", "Tensor", "Tensor", "Tensor")) +call_c_function( +fun_name = 'mkldnn_rnn_layer_out', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch_mm torch_mm <- function(self, mat2) { args <- mget(x = c("self", "mat2")) @@ -26018,44 +26566,6 @@ fun_type = 'namespace' } -#' @rdname torch_mps_max_pool2d_backward -torch_mps_max_pool2d_backward <- function(grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(grad_output = "Tensor", self = "Tensor", kernel_size = "IntArrayRef", - stride = "IntArrayRef", padding = "IntArrayRef", dilation = "IntArrayRef", - ceil_mode = "bool") -nd_args <- c("grad_output", "self", "kernel_size") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'mps_max_pool2d_backward', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_mps_max_pool2d_backward_out -torch_mps_max_pool2d_backward_out <- function(out, grad_output, self, kernel_size, stride = list(), padding = 0L, dilation = 1L, ceil_mode = FALSE) { - args <- mget(x = c("out", "grad_output", "self", "kernel_size", "stride", "padding", "dilation", "ceil_mode")) -expected_types <- list(out = "Tensor", grad_output = "Tensor", self = "Tensor", - kernel_size = "IntArrayRef", stride = "IntArrayRef", padding = "IntArrayRef", - dilation = "IntArrayRef", ceil_mode = "bool") -nd_args <- c("out", "grad_output", "self", "kernel_size") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'mps_max_pool2d_backward_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_mse_loss torch_mse_loss <- function(self, target, reduction = torch_reduction_mean()) { args <- mget(x = c("self", "target", "reduction")) @@ -28438,58 +28948,6 @@ fun_type = 'namespace' } -#' @rdname torch_prelu_backward -torch_prelu_backward <- function(grad_output, self, weight) { - args <- mget(x = c("grad_output", "self", "weight")) -expected_types <- list(grad_output = "Tensor", self = "Tensor", weight = "Tensor") -nd_args <- c("grad_output", "self", "weight") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'prelu_backward', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_prelu_backward_out -torch_prelu_backward_out <- function(out0, out1, grad_output, self, weight) { - args <- mget(x = c("out0", "out1", "grad_output", "self", "weight")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", grad_output = "Tensor", - self = "Tensor", weight = "Tensor") -nd_args <- c("out0", "out1", "grad_output", "self", "weight") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'prelu_backward_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_prelu_out -torch_prelu_out <- function(out, self, weight) { - args <- mget(x = c("out", "self", "weight")) -expected_types <- list(out = "Tensor", self = "Tensor", weight = "Tensor") -nd_args <- c("out", "self", "weight") -return_types <- list(list('Tensor')) -call_c_function( -fun_name = 'prelu_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_prod torch_prod <- function(self, dim, keepdim = FALSE, dtype = NULL) { args <- mget(x = c("self", "dim", "keepdim", "dtype")) @@ -30875,6 +31333,24 @@ fun_type = 'namespace' } +#' @rdname torch_scaled_dot_product_attention +torch_scaled_dot_product_attention <- function(query, key, value, attn_mask = list(), dropout_p = 0L, is_causal = FALSE) { + args <- mget(x = c("query", "key", "value", "attn_mask", "dropout_p", "is_causal")) +expected_types <- list(query = "Tensor", key = "Tensor", value = "Tensor", attn_mask = "Tensor", + dropout_p = "double", is_causal = "bool") +nd_args <- c("query", "key", "value") +return_types <- list(list('Tensor')) +call_c_function( +fun_name = 'scaled_dot_product_attention', +args = args, +expected_types = expected_types, +nd_args = nd_args, +return_types = return_types, +fun_type = 'namespace' +) +} + + #' @rdname torch_scatter torch_scatter <- function(self, dim, index, src, value, reduce) { args <- mget(x = c("self", "dim", "index", "src", "value", "reduce")) @@ -34782,7 +35258,8 @@ fun_type = 'namespace' #' @rdname torch_squeeze torch_squeeze <- function(self, dim) { args <- mget(x = c("self", "dim")) -expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname")) +expected_types <- list(self = "Tensor", dim = c("int64_t", "Dimname", "IntArrayRef" +)) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -34799,7 +35276,7 @@ fun_type = 'namespace' #' @rdname torch_squeeze_copy torch_squeeze_copy <- function(self, dim) { args <- mget(x = c("self", "dim")) -expected_types <- list(self = "Tensor", dim = "int64_t") +expected_types <- list(self = "Tensor", dim = c("int64_t", "IntArrayRef")) nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -34816,7 +35293,8 @@ fun_type = 'namespace' #' @rdname torch_squeeze_copy_out torch_squeeze_copy_out <- function(out, self, dim) { args <- mget(x = c("out", "self", "dim")) -expected_types <- list(out = "Tensor", self = "Tensor", dim = "int64_t") +expected_types <- list(out = "Tensor", self = "Tensor", dim = c("int64_t", "IntArrayRef" +)) nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( @@ -34901,11 +35379,11 @@ fun_type = 'namespace' #' @rdname torch_std -torch_std <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_std <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") + unbiased = "bool", keepdim = "bool") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'std', @@ -34919,11 +35397,11 @@ fun_type = 'namespace' #' @rdname torch_std_mean -torch_std_mean <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_std_mean <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") + unbiased = "bool", keepdim = "bool") +nd_args <- c("self", "dim") return_types <- list(list("Tensor", "Tensor")) call_c_function( fun_name = 'std_mean', @@ -34936,30 +35414,12 @@ fun_type = 'namespace' } -#' @rdname torch_std_mean_out -torch_std_mean_out <- function(out0, out1, self, dim, correction, keepdim = FALSE) { - args <- mget(x = c("out0", "out1", "self", "dim", "correction", "keepdim")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", dim = "IntArrayRef", - correction = "int64_t", keepdim = "bool") -nd_args <- c("out0", "out1", "self", "dim", "correction") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'std_mean_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_std_out -torch_std_out <- function(out, self, dim, correction, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("out", "self", "dim", "correction", "unbiased", "keepdim")) +torch_std_out <- function(out, self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("out", "self", "dim", "unbiased", "keepdim")) expected_types <- list(out = "Tensor", self = "Tensor", dim = c("IntArrayRef", -"DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("out", "self", "dim", "correction") +"DimnameList"), unbiased = "bool", keepdim = "bool") +nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'std_out', @@ -35183,41 +35643,6 @@ fun_type = 'namespace' } -#' @rdname torch_symeig -torch_symeig <- function(self, eigenvectors = FALSE, upper = TRUE) { - args <- mget(x = c("self", "eigenvectors", "upper")) -expected_types <- list(self = "Tensor", eigenvectors = "bool", upper = "bool") -nd_args <- "self" -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'symeig', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - -#' @rdname torch_symeig_out -torch_symeig_out <- function(e, V, self, eigenvectors = FALSE, upper = TRUE) { - args <- mget(x = c("e", "V", "self", "eigenvectors", "upper")) -expected_types <- list(e = "Tensor", V = "Tensor", self = "Tensor", eigenvectors = "bool", - upper = "bool") -nd_args <- c("e", "V", "self") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'symeig_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_t torch_t <- function(self) { args <- mget(x = c("self")) @@ -35736,9 +36161,10 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_bsc_out -torch_to_sparse_bsc_out <- function(out, self, blocksize) { - args <- mget(x = c("out", "self", "blocksize")) -expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef") +torch_to_sparse_bsc_out <- function(out, self, blocksize, dense_dim = NULL) { + args <- mget(x = c("out", "self", "blocksize", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef", + dense_dim = "int64_t") nd_args <- c("out", "self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -35753,9 +36179,10 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_bsr_out -torch_to_sparse_bsr_out <- function(out, self, blocksize) { - args <- mget(x = c("out", "self", "blocksize")) -expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef") +torch_to_sparse_bsr_out <- function(out, self, blocksize, dense_dim = NULL) { + args <- mget(x = c("out", "self", "blocksize", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", blocksize = "IntArrayRef", + dense_dim = "int64_t") nd_args <- c("out", "self", "blocksize") return_types <- list(list('Tensor')) call_c_function( @@ -35770,9 +36197,9 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_csc_out -torch_to_sparse_csc_out <- function(out, self) { - args <- mget(x = c("out", "self")) -expected_types <- list(out = "Tensor", self = "Tensor") +torch_to_sparse_csc_out <- function(out, self, dense_dim = NULL) { + args <- mget(x = c("out", "self", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", dense_dim = "int64_t") nd_args <- c("out", "self") return_types <- list(list('Tensor')) call_c_function( @@ -35787,9 +36214,9 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_csr_out -torch_to_sparse_csr_out <- function(out, self) { - args <- mget(x = c("out", "self")) -expected_types <- list(out = "Tensor", self = "Tensor") +torch_to_sparse_csr_out <- function(out, self, dense_dim = NULL) { + args <- mget(x = c("out", "self", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", dense_dim = "int64_t") nd_args <- c("out", "self") return_types <- list(list('Tensor')) call_c_function( @@ -35804,9 +36231,10 @@ fun_type = 'namespace' #' @rdname torch_to_sparse_out -torch_to_sparse_out <- function(out, self, sparse_dim) { - args <- mget(x = c("out", "self", "sparse_dim")) -expected_types <- list(out = "Tensor", self = "Tensor", sparse_dim = "int64_t") +torch_to_sparse_out <- function(out, self, layout = NULL, sparse_dim, blocksize = NULL, dense_dim = NULL) { + args <- mget(x = c("out", "self", "layout", "sparse_dim", "blocksize", "dense_dim")) +expected_types <- list(out = "Tensor", self = "Tensor", layout = "Layout", sparse_dim = "int64_t", + blocksize = "IntArrayRef", dense_dim = "int64_t") nd_args <- c("out", "self", "sparse_dim") return_types <- list(list('Tensor')) call_c_function( @@ -36730,13 +37158,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_bicubic2d_backward -torch_upsample_bicubic2d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch_upsample_bicubic2d_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bicubic2d_backward', @@ -36750,14 +37177,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_bicubic2d_backward_out -torch_upsample_bicubic2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_bicubic2d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bicubic2d_backward_out', @@ -36771,13 +37197,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_bicubic2d_out -torch_upsample_bicubic2d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_bicubic2d_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bicubic2d_out', @@ -36811,13 +37235,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_bilinear2d_backward -torch_upsample_bilinear2d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) +torch_upsample_bilinear2d_backward <- function(grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bilinear2d_backward', @@ -36831,14 +37254,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_bilinear2d_backward_out -torch_upsample_bilinear2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_bilinear2d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bilinear2d_backward_out', @@ -36852,13 +37274,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_bilinear2d_out -torch_upsample_bilinear2d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_bilinear2d_out <- function(out, self, output_size, align_corners, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_bilinear2d_out', @@ -36892,13 +37312,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_linear1d_backward -torch_upsample_linear1d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales")) +torch_upsample_linear1d_backward <- function(grad_output, output_size, input_size, align_corners, scales = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_linear1d_backward', @@ -36912,14 +37331,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_linear1d_backward_out -torch_upsample_linear1d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_linear1d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_linear1d_backward_out', @@ -36933,13 +37350,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_linear1d_out -torch_upsample_linear1d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_linear1d_out <- function(out, self, output_size, align_corners, scales = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_linear1d_out', @@ -36971,12 +37386,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest1d_backward -torch_upsample_nearest1d_backward <- function(grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales")) +torch_upsample_nearest1d_backward <- function(grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest1d_backward', @@ -36990,13 +37404,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest1d_backward_out -torch_upsample_nearest1d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch_upsample_nearest1d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest1d_backward_out', @@ -37010,11 +37422,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest1d_out -torch_upsample_nearest1d_out <- function(out, input, self, output_size, scale_factors, scales = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch_upsample_nearest1d_out <- function(out, self, output_size, scales = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest1d_out', @@ -37047,13 +37459,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest2d_backward -torch_upsample_nearest2d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) +torch_upsample_nearest2d_backward <- function(grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest2d_backward', @@ -37067,14 +37477,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest2d_backward_out -torch_upsample_nearest2d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch_upsample_nearest2d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_h = "double", scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest2d_backward_out', @@ -37088,12 +37495,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest2d_out -torch_upsample_nearest2d_out <- function(out, input, self, output_size, scale_factors, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_h = "double", - scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch_upsample_nearest2d_out <- function(out, self, output_size, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest2d_out', @@ -37126,13 +37532,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest3d_backward -torch_upsample_nearest3d_backward <- function(grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) +torch_upsample_nearest3d_backward <- function(grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "scale_factors" -) + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest3d_backward', @@ -37146,14 +37550,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest3d_backward_out -torch_upsample_nearest3d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"scale_factors") +torch_upsample_nearest3d_backward_out <- function(grad_input, grad_output, output_size, input_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest3d_backward_out', @@ -37167,12 +37569,11 @@ fun_type = 'namespace' #' @rdname torch_upsample_nearest3d_out -torch_upsample_nearest3d_out <- function(out, input, self, output_size, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - scale_factors = "ArrayRef", scales_d = "double", - scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "scale_factors") +torch_upsample_nearest3d_out <- function(out, self, output_size, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "scales_d", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + scales_d = "double", scales_h = "double", scales_w = "double") +nd_args <- c("out", "self", "output_size") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_nearest3d_out', @@ -37206,13 +37607,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_trilinear3d_backward -torch_upsample_trilinear3d_backward <- function(grad_output, output_size, input_size, align_corners, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_d", "scales_h", "scales_w")) +torch_upsample_trilinear3d_backward <- function(grad_output, output_size, input_size, align_corners, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_output", "output_size", "input_size", "align_corners", "scales_d", "scales_h", "scales_w")) expected_types <- list(grad_output = "Tensor", output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_d = "double", scales_h = "double", scales_w = "double") -nd_args <- c("grad_output", "output_size", "input_size", "align_corners", -"scale_factors") + align_corners = "bool", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_trilinear3d_backward', @@ -37226,14 +37627,13 @@ fun_type = 'namespace' #' @rdname torch_upsample_trilinear3d_backward_out -torch_upsample_trilinear3d_backward_out <- function(grad_input, out, grad_output, output_size, input_size, align_corners, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("grad_input", "out", "grad_output", "output_size", "input_size", "align_corners", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(grad_input = "Tensor", out = "Tensor", grad_output = "Tensor", - output_size = "IntArrayRef", input_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_d = "double", scales_h = "double", scales_w = "double") -nd_args <- c("grad_input", "out", "grad_output", "output_size", "input_size", -"align_corners", "scale_factors") +torch_upsample_trilinear3d_backward_out <- function(grad_input, grad_output, output_size, input_size, align_corners, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("grad_input", "grad_output", "output_size", "input_size", "align_corners", "scales_d", "scales_h", "scales_w")) +expected_types <- list(grad_input = "Tensor", grad_output = "Tensor", output_size = "IntArrayRef", + input_size = "IntArrayRef", align_corners = "bool", scales_d = "double", + scales_h = "double", scales_w = "double") +nd_args <- c("grad_input", "grad_output", "output_size", "input_size", "align_corners" +) return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_trilinear3d_backward_out', @@ -37247,13 +37647,12 @@ fun_type = 'namespace' #' @rdname torch_upsample_trilinear3d_out -torch_upsample_trilinear3d_out <- function(out, input, self, output_size, align_corners, scale_factors, scales_d = NULL, scales_h = NULL, scales_w = NULL) { - args <- mget(x = c("out", "input", "self", "output_size", "align_corners", "scale_factors", "scales_d", "scales_h", "scales_w")) -expected_types <- list(out = "Tensor", input = "Tensor", self = "Tensor", output_size = "IntArrayRef", - align_corners = "bool", scale_factors = "ArrayRef", - scales_d = "double", scales_h = "double", scales_w = "double") -nd_args <- c("out", "input", "self", "output_size", "align_corners", "scale_factors" -) +torch_upsample_trilinear3d_out <- function(out, self, output_size, align_corners, scales_d = NULL, scales_h = NULL, scales_w = NULL) { + args <- mget(x = c("out", "self", "output_size", "align_corners", "scales_d", "scales_h", "scales_w")) +expected_types <- list(out = "Tensor", self = "Tensor", output_size = "IntArrayRef", + align_corners = "bool", scales_d = "double", scales_h = "double", + scales_w = "double") +nd_args <- c("out", "self", "output_size", "align_corners") return_types <- list(list('Tensor')) call_c_function( fun_name = 'upsample_trilinear3d_out', @@ -37336,11 +37735,11 @@ fun_type = 'namespace' #' @rdname torch_var -torch_var <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_var <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") + unbiased = "bool", keepdim = "bool") +nd_args <- c("self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'var', @@ -37354,11 +37753,11 @@ fun_type = 'namespace' #' @rdname torch_var_mean -torch_var_mean <- function(self, dim, correction, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("self", "dim", "correction", "unbiased", "keepdim")) +torch_var_mean <- function(self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("self", "dim", "unbiased", "keepdim")) expected_types <- list(self = "Tensor", dim = c("IntArrayRef", "DimnameList"), - correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("self", "dim", "correction") + unbiased = "bool", keepdim = "bool") +nd_args <- c("self", "dim") return_types <- list(list("Tensor", "Tensor")) call_c_function( fun_name = 'var_mean', @@ -37371,30 +37770,12 @@ fun_type = 'namespace' } -#' @rdname torch_var_mean_out -torch_var_mean_out <- function(out0, out1, self, dim, correction, keepdim = FALSE) { - args <- mget(x = c("out0", "out1", "self", "dim", "correction", "keepdim")) -expected_types <- list(out0 = "Tensor", out1 = "Tensor", self = "Tensor", dim = "IntArrayRef", - correction = "int64_t", keepdim = "bool") -nd_args <- c("out0", "out1", "self", "dim", "correction") -return_types <- list(list("Tensor", "Tensor")) -call_c_function( -fun_name = 'var_mean_out', -args = args, -expected_types = expected_types, -nd_args = nd_args, -return_types = return_types, -fun_type = 'namespace' -) -} - - #' @rdname torch_var_out -torch_var_out <- function(out, self, dim, correction, unbiased = TRUE, keepdim = FALSE) { - args <- mget(x = c("out", "self", "dim", "correction", "unbiased", "keepdim")) +torch_var_out <- function(out, self, dim, unbiased = TRUE, keepdim = FALSE) { + args <- mget(x = c("out", "self", "dim", "unbiased", "keepdim")) expected_types <- list(out = "Tensor", self = "Tensor", dim = c("IntArrayRef", -"DimnameList"), correction = "int64_t", unbiased = "bool", keepdim = "bool") -nd_args <- c("out", "self", "dim", "correction") +"DimnameList"), unbiased = "bool", keepdim = "bool") +nd_args <- c("out", "self", "dim") return_types <- list(list('Tensor')) call_c_function( fun_name = 'var_out', diff --git a/R/install.R b/R/install.R index 60a022ac3e..76f5ae873a 100644 --- a/R/install.R +++ b/R/install.R @@ -1,5 +1,5 @@ branch <- "main" -torch_version <- "1.13.1" +torch_version <- "2.0.1" #' Install Torch #' diff --git a/R/save.R b/R/save.R index 798d52459f..bcb3708adc 100644 --- a/R/save.R +++ b/R/save.R @@ -251,6 +251,10 @@ torch_load <- function(path, device = "cpu") { if (is_rds(path)) { return(legacy_torch_load(path, device)) } + + if (is.null(device)) { + cli::cli_abort("Unexpected device {.val NULL}") + } con <- create_read_con(path) @@ -285,7 +289,7 @@ torch_load <- function(path, device = "cpu") { return(safe[[1]]) } - object <- unserialize(buffer_from_torch_tensor(safe[[r_obj]])) + object <- unserialize(buffer_from_torch_tensor(safe[[r_obj]]$cpu())) safe[r_obj] <- NULL if (meta$type == "list") { diff --git a/inst/include/lantern/lantern.h b/inst/include/lantern/lantern.h index 7a3706a453..4224b2ee4a 100644 --- a/inst/include/lantern/lantern.h +++ b/inst/include/lantern/lantern.h @@ -2865,6 +2865,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_affine_grid_generator_tensor_intarrayref_bool(void* theta, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_tensor_intarrayref_bool(theta, size, align_corners); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_affine_grid_generator_backward_tensor_intarrayref_bool)(void* grad, void* size, void* align_corners); HOST_API void* lantern_affine_grid_generator_backward_tensor_intarrayref_bool(void* grad, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_backward_tensor_intarrayref_bool(grad, size, align_corners); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_all_true_tensor)(void* self); + HOST_API void* lantern__is_all_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_all_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_all_true_tensor(void* self) { void* ret = _lantern_Tensor__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_any_true_tensor)(void* self); + HOST_API void* lantern__is_any_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_any_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_any_true_tensor(void* self) { void* ret = _lantern_Tensor__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__test_check_tensor_tensor)(void* self); + HOST_API void* lantern__test_check_tensor_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__test_check_tensor_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_all_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_all_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4279,10 +4289,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -4375,6 +4383,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -4401,10 +4413,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mm_out_tensor_tensor_tensor(void* out, void* self, void* mat2) { LANTERN_CHECK_LOADED void* ret = _lantern_mm_out_tensor_tensor_tensor(out, self, mat2); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor)(void* sparse, void* dense); HOST_API void* lantern__sparse_mm_tensor_tensor(void* sparse, void* dense) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor(sparse, dense); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor_cstringview)(void* sparse, void* dense, void* reduce); + HOST_API void* lantern__sparse_mm_tensor_tensor_cstringview(void* sparse, void* dense, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor_cstringview(sparse, dense, reduce); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_tensor_tensor)(void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_tensor_tensor)(void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_tensor_tensor(void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_tensor_tensor(t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_mode_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_mode_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4477,6 +4489,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); HOST_API void* lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_tensor_double)(void* input, void* eps); HOST_API void* lantern_batch_norm_stats_tensor_double(void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_tensor_double(input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* weight, void* bias, void* mean, void* invstd, void* eps); @@ -4715,6 +4735,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_reshape_tensor_intarrayref(void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_reshape_tensor_intarrayref)(void* self, void* shape); HOST_API void* lantern_Tensor_reshape_tensor_intarrayref(void* self, void* shape) { void* ret = _lantern_Tensor_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_copy_tensor_intarrayref)(void* self, void* size); + HOST_API void* lantern__reshape_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); HOST_API void* lantern__reshape_alias_tensor_intarrayref_intarrayref(void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_tensor_intarrayref_intarrayref(self, size, stride); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); @@ -4763,10 +4785,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_prelu_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_tensor_tensor)(void* self, void* weight); HOST_API void* lantern_Tensor_prelu_tensor_tensor(void* self, void* weight) { void* ret = _lantern_Tensor_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_Tensor_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { void* ret = _lantern_Tensor_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_tensor_tensor)(void* self, void* weight); + HOST_API void* lantern__prelu_kernel_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); + HOST_API void* lantern__prelu_kernel_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu_out_tensor_tensor_cstringview)(void* out, void* self, void* approximate); HOST_API void* lantern_gelu_out_tensor_tensor_cstringview(void* out, void* self, void* approximate) { LANTERN_CHECK_LOADED void* ret = _lantern_gelu_out_tensor_tensor_cstringview(out, self, approximate); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu__tensor_cstringview)(void* self, void* approximate); @@ -5003,10 +5025,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_tensor_dimname(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze_tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor)(void* self); HOST_API void* lantern_Tensor_squeeze__tensor(void* self) { void* ret = _lantern_Tensor_squeeze__tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intt)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_intt(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze__tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5361,6 +5389,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_where_tensor_scalar_tensor(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_tensor(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_tensor_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_tensor_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_where_tensor_tensor_scalar)(void* condition, void* self, void* other); + HOST_API void* lantern_Tensor_where_tensor_tensor_scalar(void* condition, void* self, void* other) { void* ret = _lantern_Tensor_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_scalar_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_scalar_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor)(void* condition); @@ -5471,8 +5501,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_frexp_tensor(void* self) { void* ret = _lantern_Tensor_frexp_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frexp_out_tensor_tensor_tensor)(void* mantissa, void* exponent, void* self); HOST_API void* lantern_frexp_out_tensor_tensor_tensor(void* mantissa, void* exponent, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frexp_out_tensor_tensor_tensor(mantissa, exponent, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor)(void* self); - HOST_API void* lantern_frobenius_norm_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor_intarrayref_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_frobenius_norm_tensor_intarrayref_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor_intarrayref_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* dim, void* keepdim); @@ -5551,6 +5579,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview)(void* self, void* other, void* reduce); + HOST_API void* lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(void* self, void* other, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(self, other, reduce); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool)(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask); + HOST_API void* lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(self, grad_out, weight, reduce, arg_out, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar)(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5683,20 +5715,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_unbind_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_unbind_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_intt)(void* self, void* sparse_dim); HOST_API void* lantern_Tensor_to_sparse_tensor_intt(void* self, void* sparse_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_intt(self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csr_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csr_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csc_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csc_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt)(void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(void* self, void* layout, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csr_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csr_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csc_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csc_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_mkldnn_tensor_scalartype)(void* self, void* dtype); HOST_API void* lantern_Tensor_to_mkldnn_tensor_scalartype(void* self, void* dtype) { void* ret = _lantern_Tensor_to_mkldnn_tensor_scalartype(self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_backward_tensor_tensor)(void* grad, void* input); @@ -5821,8 +5853,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__local_scalar_dense_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__local_scalar_dense_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); HOST_API void* lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor)(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool)(void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -6223,8 +6255,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_diag_tensor_intt(void* self, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_diag_tensor_intt)(void* self, void* diagonal); HOST_API void* lantern_Tensor_diag_tensor_intt(void* self, void* diagonal) { void* ret = _lantern_Tensor_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diag_backward_tensor_intarrayref_intt)(void* grad, void* input_sizes, void* diagonal); - HOST_API void* lantern_diag_backward_tensor_intarrayref_intt(void* grad, void* input_sizes, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_backward_tensor_intarrayref_intt(grad, input_sizes, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* dim); HOST_API void* lantern_cross_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_cross_out_tensor_tensor_tensor_intt(out, self, other, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_tensor_tensor_intt)(void* self, void* other, void* dim); @@ -6521,14 +6551,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(void* self, void* B, void* upper, void* left, void* unitriangular) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(self, B, upper, left, unitriangular); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_linalg_vander_tensor_intt)(void* x, void* N); HOST_API void* lantern_linalg_vander_tensor_intt(void* x, void* N) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_vander_tensor_intt(x, N); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_out_tensor_tensor_tensor_bool_bool)(void* e, void* V, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_out_tensor_tensor_tensor_bool_bool(void* e, void* V, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_out_tensor_tensor_tensor_bool_bool(e, V, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_Tensor_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { void* ret = _lantern_Tensor_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool)(void* U, void* S, void* V, void* self, void* some, void* compute_uv); HOST_API void* lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(void* U, void* S, void* V, void* self, void* some, void* compute_uv) { LANTERN_CHECK_LOADED void* ret = _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(U, S, V, self, some, compute_uv); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_tensor_bool_bool)(void* self, void* some, void* compute_uv); @@ -6819,6 +6841,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_max_tensor_tensor(void* self, void* other) { void* ret = _lantern_Tensor_max_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern_max_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_max_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_minimum_tensor_tensor)(void* self, void* other); HOST_API void* lantern_minimum_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_minimum_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_minimum_tensor_tensor)(void* self, void* other); @@ -7007,6 +7031,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_scalar)(void* self, void* scalar); HOST_API void* lantern__foreach_div__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_tensorlist_scalar(self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); @@ -7023,6 +7063,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_tensorlist)(void* self, void* other); HOST_API void* lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_arrayrefscalar)(void* self, void* scalars); @@ -7039,6 +7095,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul__tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_tensorlist)(void* self); HOST_API void* lantern__foreach_exp_tensorlist(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_tensorlist(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero__tensorlist)(void* self); @@ -7159,26 +7231,34 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_tensorlist_scalar)(void* self, void* ord); HOST_API void* lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_tensorlist_scalar(self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_tensor_tensor_bool_bool)(void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_tensor_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_tensor_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_tensor_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); @@ -7187,8 +7267,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_bucketize_scalar_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_scalar_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_tensor)(void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); @@ -7529,52 +7607,28 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_pad_tensor_intarrayref_cstringview_double(void* self, void* pad, void* mode, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern_pad_tensor_intarrayref_cstringview_double(self, pad, mode, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double)(void* out, void* self, void* output_size, void* align_corners, void* scales); HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(void* out, void* self, void* output_size, void* align_corners, void* scales) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(out, self, output_size, align_corners, scales); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_double)(void* self, void* output_size, void* align_corners, void* scales); @@ -8309,6 +8363,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_squeeze_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_copy_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_t_copy_tensor)(void* self); HOST_API void* lantern_t_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_tensor_intt_intt)(void* self, void* dim0, void* dim1); @@ -8333,6 +8389,12 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_row_indices_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_unbind_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); + HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); + HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_intarrayref)(void* self, void* size); HOST_API void* lantern_view_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_scalartype)(void* self, void* dtype); @@ -8341,88 +8403,40 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_unfold_copy_tensor_intt_intt_intt(void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_tensor_intt_intt_intt(self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_tensor)(void* self); HOST_API void* lantern_alias_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); - HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); - HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); - HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); - HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); - HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); - HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); - HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); - HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); - HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); - HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); - HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); - HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); - HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); - HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref)(void* self, void* padding, void* output_size); HOST_API void* lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) { void* ret = _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(self, padding, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_softmax_with_shape_tensor_tensor)(void* self, void* query); HOST_API void* lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_softmax_with_shape_tensor_tensor(self, query); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double)(void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(void* self, void* weight, void* bias, void* eps) { void* ret = _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); HOST_API void* lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); HOST_API void* lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask); + HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(query, key, value, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal); + HOST_API void* lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(query, key, value, compute_log_sumexp, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool)(void* query, void* key, void* value, void* is_causal); + HOST_API void* lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(void* query, void* key, void* value, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(query, key, value, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool)(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal); + HOST_API void* lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double)(void* q, void* k, void* v, void* dropout_p); HOST_API void* lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) { LANTERN_CHECK_LOADED void* ret = _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q, k, v, dropout_p); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask); @@ -8431,8 +8445,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_special_airy_ai_tensor(void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_tensor(x); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_special_airy_ai_out_tensor_tensor)(void* out, void* x); HOST_API void* lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_out_tensor_tensor(out, x); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal); - HOST_API void* lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value); HOST_API void* lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights); @@ -8629,6 +8641,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foobar_tensor_bool_bool_bool(void* self, void* arg1, void* arg2, void* arg3) { LANTERN_CHECK_LOADED void* ret = _lantern__foobar_tensor_bool_bool_bool(self, arg1, arg2, arg3); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* self_num_batch_dims); HOST_API void* lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* self_num_batch_dims) { LANTERN_CHECK_LOADED void* ret = _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(out, self, other, self_num_batch_dims); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* deterministic, void* zero_infinity); @@ -8729,6 +8743,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* self, void* grid, void* grad_output) { LANTERN_CHECK_LOADED void* ret = _lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, self, grid, grad_output); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); + HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool)(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_diag_embed_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); @@ -8855,10 +8871,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__aminmax_out_tensor_tensor_tensor(void* out0, void* out1, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor(out0, out1, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__aminmax_out_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* self, void* dim, void* keepdim); HOST_API void* lantern__aminmax_out_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor_intt_bool(out0, out1, self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -8881,6 +8895,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* out0, void* out1, void* out2, void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(out0, out1, out2, self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* out0, void* out1, void* out2, void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -8897,10 +8915,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight, void* weight_stride0, void* weight_buf, void* hx, void* cx, void* output, void* grad_output, void* grad_hy, void* grad_cy, void* mode, void* hidden_size, void* num_layers, void* batch_first, void* dropout, void* train, void* bidirectional, void* batch_sizes, void* dropout_state, void* reserve, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(out0, out1, out2, out3, input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_out_tensor_tensor_tensor)(void* out, void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_out_tensor_tensor_tensor(void* out, void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_out_tensor_tensor_tensor(out, t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mul_out_tensor_tensor_scalar)(void* out, void* self, void* other); HOST_API void* lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_mul_out_tensor_tensor_scalar(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_out_tensor_tensor_tensor_double)(void* out0, void* out1, void* input, void* eps); HOST_API void* lantern_batch_norm_stats_out_tensor_tensor_tensor_double(void* out0, void* out1, void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_out_tensor_tensor_tensor_double(out0, out1, input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt)(void* out0, void* out1, void* input, void* mean, void* invstd, void* running_mean, void* running_var, void* momentum, void* eps, void* count); @@ -8965,10 +8983,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(void* out, void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(out, self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_relu_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_relu_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_relu_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_out_tensor_tensor_tensor)(void* out, void* self, void* weight); - HOST_API void* lantern_prelu_out_tensor_tensor_tensor(void* out, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_out_tensor_tensor_tensor(out, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt)(void* out, void* grad_output, void* input_sizes, void* dim, void* index); HOST_API void* lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(void* out, void* grad_output, void* input_sizes, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(out, grad_output, input_sizes, dim, index); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_celu_out_tensor_tensor_scalar)(void* out, void* self, void* alpha); @@ -9131,20 +9145,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_copy_sparse_to_sparse_tensor_tensor_bool(void* self, void* src, void* non_blocking) { LANTERN_CHECK_LOADED void* ret = _lantern_copy_sparse_to_sparse_tensor_tensor_bool(self, src, non_blocking); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_intt)(void* out, void* self, void* sparse_dim); HOST_API void* lantern_to_sparse_out_tensor_tensor_intt(void* out, void* self, void* sparse_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_intt(out, self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csr_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csc_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt)(void* out, void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(void* out, void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(out, self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csr_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csc_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); HOST_API void* lantern_to_mkldnn_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_to_mkldnn_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(out, self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool)(void* out, void* self, void* dtype, void* reduce_range); @@ -9187,10 +9201,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(void* self, void* observer_on, void* fake_quant_on, void* running_min, void* running_max, void* scale, void* zero_point, void* averaging_const, void* quant_min, void* quant_max, void* ch_axis, void* per_row_fake_quant, void* symmetric_quant) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__to_copy_out_tensor_tensor_bool_memoryformat)(void* out, void* self, void* non_blocking, void* memory_format); HOST_API void* lantern__to_copy_out_tensor_tensor_bool_memoryformat(void* out, void* self, void* non_blocking, void* memory_format) { LANTERN_CHECK_LOADED void* ret = _lantern__to_copy_out_tensor_tensor_bool_memoryformat(out, self, non_blocking, memory_format); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(out0, out1, out2, input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool)(void* out0, void* out1, void* out2, void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -9293,8 +9307,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_triu_indices_out_tensor_intt_intt_intt(void* out, void* row, void* col, void* offset) { LANTERN_CHECK_LOADED void* ret = _lantern_triu_indices_out_tensor_intt_intt_intt(out, row, col, offset); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_trace_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_trace_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_trace_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool)(void* out0, void* out1, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(void* out0, void* out1, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(out0, out1, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool)(void* out, void* self, void* A, void* upper); HOST_API void* lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(void* out, void* self, void* A, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(out, self, A, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_dist_out_tensor_tensor_tensor_scalar)(void* out, void* self, void* other, void* p); @@ -9329,6 +9341,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(out, self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); @@ -9337,6 +9357,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); @@ -9345,6 +9373,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_out_tensorlist_tensorlist)(void* out, void* self); HOST_API void* lantern__foreach_exp_out_tensorlist_tensorlist(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_out_tensorlist_tensorlist(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero_out_tensorlist_tensorlist)(void* out, void* self); @@ -9411,18 +9447,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(out, self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* ord); HOST_API void* lantern__foreach_norm_out_tensorlist_tensorlist_scalar(void* out, void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_out_tensorlist_tensorlist_scalar(out, self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(void* out, void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(out, self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(out, self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_scalar_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out, self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt)(void* out, void* glu, void* x, void* dx, void* dim); @@ -9443,54 +9481,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(void* out, void* self, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(out, self, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor)(void* out, void* grad_output, void* self); HOST_API void* lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(void* out, void* grad_output, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(out, grad_output, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool)(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask); HOST_API void* lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref)(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation); @@ -9521,14 +9511,74 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) { LANTERN_CHECK_LOADED void* ret = _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out, grad, output, data, reduce, lengths, offsets, axis, initial); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool)(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory); HOST_API void* lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out, list, dtype, layout, device, pin_memory); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); + HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); + HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); + HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); + HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); + HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); + HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); + HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); + HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); + HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intarrayref(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); + HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_ccol_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_ccol_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_ccol_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_row_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_row_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); + HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); + HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref)(void* out, void* self, void* padding, void* output_size); HOST_API void* lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out, self, padding, output_size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double)(void* out, void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(void* out, void* self, void* weight, void* bias, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(out, self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(out, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* out0, void* out1, void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); @@ -9547,6 +9597,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } /* Autogen Headers -- End */ #ifdef __cplusplus @@ -10309,6 +10363,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_addr_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_affine_grid_generator_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_affine_grid_generator_backward_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern__is_all_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_all_true_tensor) + LOAD_SYMBOL(_lantern__is_any_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_any_true_tensor) + LOAD_SYMBOL(_lantern__test_check_tensor_tensor) LOAD_SYMBOL(_lantern_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_all_out_tensor_tensor_intt_bool) @@ -11016,8 +11075,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_pool1d_with_indices_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -11064,6 +11122,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -11077,8 +11137,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_mm_tensor_tensor) LOAD_SYMBOL(_lantern_mm_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor) + LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_tensor_tensor) LOAD_SYMBOL(_lantern_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_mode_out_tensor_tensor_tensor_intt_bool) @@ -11115,6 +11175,10 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_narrow_tensor_intt_tensor_intt) LOAD_SYMBOL(_lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_out_tensor_tensor_tensor_tensor_tensor_tensor_double) @@ -11234,6 +11298,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_repeat_interleave_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_reshape_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_reshape_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern__mkldnn_reshape_tensor_intarrayref) @@ -11258,8 +11323,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_relu6__tensor) LOAD_SYMBOL(_lantern_prelu_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_prelu_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor_prelu_backward_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_backward_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_gelu_out_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern_gelu__tensor_cstringview) LOAD_SYMBOL(_lantern_gelu_tensor_cstringview) @@ -11378,8 +11443,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intt) LOAD_SYMBOL(_lantern_squeeze_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_dimname) + LOAD_SYMBOL(_lantern_squeeze_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_dimname) LOAD_SYMBOL(_lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_sspaddmm_tensor_tensor_tensor_scalar_scalar) @@ -11557,6 +11625,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_where_out_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_where_tensor_scalar_tensor) LOAD_SYMBOL(_lantern_where_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern_Tensor_where_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_where_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_where_tensor) LOAD_SYMBOL(_lantern_norm_except_dim_tensor_intt_intt) @@ -11612,7 +11681,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_frexp_tensor) LOAD_SYMBOL(_lantern_Tensor_frexp_tensor) LOAD_SYMBOL(_lantern_frexp_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_frobenius_norm_tensor) LOAD_SYMBOL(_lantern_frobenius_norm_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_nuclear_norm_tensor_bool) @@ -11652,6 +11720,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__sparse_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool) LOAD_SYMBOL(_lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_addmm_tensor_tensor_tensor_scalar_scalar) @@ -11718,13 +11788,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_intt) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_Tensor_to_mkldnn_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_backward_tensor_tensor) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_tensor_scalartype_bool) @@ -11787,7 +11857,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_promote_types_scalartype_scalartype) LOAD_SYMBOL(_lantern__local_scalar_dense_tensor) LOAD_SYMBOL(_lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_tensor_tensor_tensor_tensor_tensor_bool) @@ -11988,7 +12058,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_diag_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern_diag_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_diag_tensor_intt) - LOAD_SYMBOL(_lantern_diag_backward_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_cross_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_cross_tensor_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_cross_tensor_tensor_intt) @@ -12137,10 +12206,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_linalg_solve_triangular_out_tensor_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_vander_tensor_intt) - LOAD_SYMBOL(_lantern_symeig_out_tensor_tensor_tensor_bool_bool) - LOAD_SYMBOL(_lantern_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern_Tensor_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern__symeig_helper_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_tensor_bool_bool) LOAD_SYMBOL(_lantern_Tensor_svd_tensor_bool_bool) @@ -12286,6 +12351,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_max_tensor_tensor) LOAD_SYMBOL(_lantern_max_out_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern_max_out_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_out_tensor_tensor_tensor) @@ -12380,6 +12446,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_tensorlist_scalar) @@ -12388,6 +12462,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_arrayrefscalar) @@ -12396,6 +12478,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_div__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero__tensorlist) LOAD_SYMBOL(_lantern__foreach_exp__tensorlist) @@ -12456,21 +12546,24 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_scalar_tensor_bool_bool) LOAD_SYMBOL(_lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern__convert_indices_from_coo_to_csr_tensor_intt_bool) @@ -12641,29 +12734,17 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__pad_enum_tensor_intarrayref_intt_double) LOAD_SYMBOL(_lantern_pad_tensor_intarrayref_cstringview_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_double) @@ -13031,6 +13112,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_split_with_sizes_copy_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_squeeze_copy_tensor) LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_t_copy_tensor) LOAD_SYMBOL(_lantern_transpose_copy_tensor_intt_intt) LOAD_SYMBOL(_lantern_unsqueeze_copy_tensor_intt) @@ -13043,56 +13125,34 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_ccol_indices_copy_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_tensor) LOAD_SYMBOL(_lantern_unbind_copy_tensor_intt) + LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) + LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) + LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_view_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_view_copy_tensor_scalartype) LOAD_SYMBOL(_lantern_unfold_copy_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_alias_copy_tensor) - LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) - LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) - LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) - LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) - LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) - LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_to_padded_tensor_tensor_double_intarrayref) LOAD_SYMBOL(_lantern__nested_tensor_softmax_with_shape_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) + LOAD_SYMBOL(_lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool) LOAD_SYMBOL(_lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool) + LOAD_SYMBOL(_lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool) + LOAD_SYMBOL(_lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool) + LOAD_SYMBOL(_lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_out_tensor_tensor) - LOAD_SYMBOL(_lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool) LOAD_SYMBOL(_lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_special_bessel_j0_tensor) @@ -13191,6 +13251,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_special_spherical_bessel_j0_out_tensor_tensor) LOAD_SYMBOL(_lantern__foobar_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool) LOAD_SYMBOL(_lantern__cudnn_rnn_flatten_weight_out_tensor_tensorlist_intt_intt_intt_intt_intt_intt_bool_bool) @@ -13241,6 +13302,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_cudnn_grid_sampler_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool) + LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern_diag_embed_out_tensor_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_diagonal_backward_out_tensor_tensor_intarrayref_intt_intt_intt) @@ -13304,8 +13366,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_matmul_backward_out_tensor_tensor_tensor_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor_intt_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -13317,6 +13378,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -13325,8 +13388,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_miopen_rnn_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_intt_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor) LOAD_SYMBOL(_lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_mul_out_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_out_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_with_counts_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_tensor) @@ -13359,8 +13422,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_repeat_interleave_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern__mkldnn_reshape_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern_relu_out_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt) LOAD_SYMBOL(_lantern_celu_out_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_slice_backward_out_tensor_tensor_intarrayref_intt_intt_intt_intt) @@ -13442,13 +13503,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_tensor_tensor_bool) LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool) LOAD_SYMBOL(_lantern_quantize_per_tensor_out_tensor_tensor_double_intt_scalartype) @@ -13470,8 +13531,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__to_copy_out_tensor_tensor_bool_memoryformat) - LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_gru_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor) @@ -13523,7 +13584,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_tril_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_triu_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_trace_out_tensor_tensor) - LOAD_SYMBOL(_lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_dist_out_tensor_tensor_tensor_scalar) LOAD_SYMBOL(_lantern__histogramdd_bin_edges_out_tensorlist_tensor_intarrayref_arrayrefdouble_tensor_bool) @@ -13541,14 +13601,26 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_tensorlist) @@ -13582,12 +13654,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_out_tensor_scalar_tensor_bool_bool) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_glu_backward_jvp_out_tensor_tensor_tensor_tensor_tensor_tensor_intt) @@ -13598,30 +13671,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__adaptive_avg_pool2d_backward_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool) LOAD_SYMBOL(_lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) @@ -13637,10 +13686,40 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar) LOAD_SYMBOL(_lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar) LOAD_SYMBOL(_lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool) + LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) + LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_ccol_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) + LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref) - LOAD_SYMBOL(_lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_out_tensor_tensor_tensor_tensor_double) @@ -13650,6 +13729,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foobar_out_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) /* Autogen Symbols -- End */ return true; diff --git a/man/torch_eig.Rd b/man/torch_eig.Rd index 3664001f11..793aad8f34 100644 --- a/man/torch_eig.Rd +++ b/man/torch_eig.Rd @@ -12,11 +12,6 @@ \description{ Eig } -\note{ -\if{html}{\out{
}}\preformatted{Since eigenvalues and eigenvectors might be complex, backward pass is supported only -for [`torch_symeig`] -}\if{html}{\out{
}} -} \section{eig(input, eigenvectors=False, out=NULL) -> (Tensor, Tensor) }{ diff --git a/man/torch_std.Rd b/man/torch_std.Rd index 795c0b4fda..8e4f8f53a6 100644 --- a/man/torch_std.Rd +++ b/man/torch_std.Rd @@ -5,18 +5,18 @@ \alias{torch_std} \title{Std} \usage{ -torch_std(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_std(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} + +\item{correction}{The type of correction.} } \description{ Std diff --git a/man/torch_std_mean.Rd b/man/torch_std_mean.Rd index d79a71da2e..65b7470b6a 100644 --- a/man/torch_std_mean.Rd +++ b/man/torch_std_mean.Rd @@ -5,15 +5,13 @@ \alias{torch_std_mean} \title{Std_mean} \usage{ -torch_std_mean(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_std_mean(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} diff --git a/man/torch_symeig.Rd b/man/torch_symeig.Rd deleted file mode 100644 index 6be0c5944a..0000000000 --- a/man/torch_symeig.Rd +++ /dev/null @@ -1,71 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/gen-namespace-docs.R, -% R/gen-namespace-examples.R, R/gen-namespace.R -\name{torch_symeig} -\alias{torch_symeig} -\title{Symeig} -\usage{ -torch_symeig(self, eigenvectors = FALSE, upper = TRUE) -} -\arguments{ -\item{self}{(Tensor) the input tensor of size \eqn{(*, n, n)} where \code{*} is zero or more batch dimensions consisting of symmetric matrices.} - -\item{eigenvectors}{(boolean, optional) controls whether eigenvectors have to be computed} - -\item{upper}{(boolean, optional) controls whether to consider upper-triangular or lower-triangular region} -} -\description{ -Symeig -} -\note{ -The eigenvalues are returned in ascending order. If \code{input} is a batch of matrices, -then the eigenvalues of each matrix in the batch is returned in ascending order. - -Irrespective of the original strides, the returned matrix \code{V} will -be transposed, i.e. with strides \verb{V.contiguous().transpose(-1, -2).stride()}. - -Extra care needs to be taken when backward through outputs. Such -operation is really only stable when all eigenvalues are distinct. -Otherwise, \code{NaN} can appear as the gradients are not properly defined. -} -\section{symeig(input, eigenvectors=False, upper=TRUE) -> (Tensor, Tensor) }{ - - -This function returns eigenvalues and eigenvectors -of a real symmetric matrix \code{input} or a batch of real symmetric matrices, -represented by a namedtuple (eigenvalues, eigenvectors). - -This function calculates all eigenvalues (and vectors) of \code{input} -such that \eqn{\mbox{input} = V \mbox{diag}(e) V^T}. - -The boolean argument \code{eigenvectors} defines computation of -both eigenvectors and eigenvalues or eigenvalues only. - -If it is \code{FALSE}, only eigenvalues are computed. If it is \code{TRUE}, -both eigenvalues and eigenvectors are computed. - -Since the input matrix \code{input} is supposed to be symmetric, -only the upper triangular portion is used by default. - -If \code{upper} is \code{FALSE}, then lower triangular portion is used. -} - -\examples{ -if (torch_is_installed()) { - -a = torch_randn(c(5, 5)) -a = a + a$t() # To make a symmetric -a -o = torch_symeig(a, eigenvectors=TRUE) -e = o[[1]] -v = o[[2]] -e -v -a_big = torch_randn(c(5, 2, 2)) -a_big = a_big + a_big$transpose(-2, -1) # To make a_big symmetric -o = a_big$symeig(eigenvectors=TRUE) -e = o[[1]] -v = o[[2]] -torch_allclose(torch_matmul(v, torch_matmul(e$diag_embed(), v$transpose(-2, -1))), a_big) -} -} diff --git a/man/torch_var.Rd b/man/torch_var.Rd index 0935891e9b..ad54627194 100644 --- a/man/torch_var.Rd +++ b/man/torch_var.Rd @@ -5,15 +5,13 @@ \alias{torch_var} \title{Var} \usage{ -torch_var(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_var(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} diff --git a/man/torch_var_mean.Rd b/man/torch_var_mean.Rd index 72cfecdf58..4cda19876a 100644 --- a/man/torch_var_mean.Rd +++ b/man/torch_var_mean.Rd @@ -5,15 +5,13 @@ \alias{torch_var_mean} \title{Var_mean} \usage{ -torch_var_mean(self, dim, correction, unbiased = TRUE, keepdim = FALSE) +torch_var_mean(self, dim, unbiased = TRUE, keepdim = FALSE) } \arguments{ \item{self}{(Tensor) the input tensor.} \item{dim}{(int or tuple of ints) the dimension or dimensions to reduce.} -\item{correction}{The type of correction.} - \item{unbiased}{(bool) whether to use the unbiased estimation or not} \item{keepdim}{(bool) whether the output tensor has \code{dim} retained or not.} diff --git a/src/RcppExports.cpp b/src/RcppExports.cpp index 32c3bd98ca..87752d320e 100644 --- a/src/RcppExports.cpp +++ b/src/RcppExports.cpp @@ -1522,6 +1522,28 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method__is_all_true_self_Tensor +XPtrTorchTensor cpp_torch_method__is_all_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_method__is_all_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method__is_all_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_method__is_any_true_self_Tensor +XPtrTorchTensor cpp_torch_method__is_any_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_method__is_any_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method__is_any_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_all_self_Tensor_dim_int64_t XPtrTorchTensor cpp_torch_method_all_self_Tensor_dim_int64_t(XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_method_all_self_Tensor_dim_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP keepdimSEXP) { @@ -4988,19 +5010,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor -Rcpp::List cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(grad_output, self, weight)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_hardshrink_self_Tensor XPtrTorchTensor cpp_torch_method_hardshrink_self_Tensor(XPtrTorchTensor self, XPtrTorchScalar lambd); RcppExport SEXP _torch_cpp_torch_method_hardshrink_self_Tensor(SEXP selfSEXP, SEXP lambdSEXP) { @@ -5505,6 +5514,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_squeeze__self_Tensor XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor(XPtrTorchTensor self); RcppExport SEXP _torch_cpp_torch_method_squeeze__self_Tensor(SEXP selfSEXP) { @@ -5528,6 +5549,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_squeeze__self_Tensor_dim_Dimname XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_Dimname(XPtrTorchTensor self, XPtrTorchDimname dim); RcppExport SEXP _torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname(SEXP selfSEXP, SEXP dimSEXP) { @@ -5755,20 +5788,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_std_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_method_std_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -5783,20 +5802,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_prod_self_Tensor XPtrTorchTensor cpp_torch_method_prod_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype); RcppExport SEXP _torch_cpp_torch_method_prod_self_Tensor(SEXP selfSEXP, SEXP dtypeSEXP) { @@ -6153,20 +6158,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_var_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_method_var_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -6181,20 +6172,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_view_as_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_method_view_as_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); RcppExport SEXP _torch_cpp_torch_method_view_as_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { @@ -6220,6 +6197,19 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar +XPtrTorchTensor cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar(XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchScalar other); +RcppExport SEXP _torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar(SEXP conditionSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type condition(conditionSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar(condition, self, other)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType XPtrTorchTensor cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType(XPtrTorchTensor self, XPtrTorchoptional_scalar p, XPtrTorchDtype dtype); RcppExport SEXP _torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType(SEXP selfSEXP, SEXP pSEXP, SEXP dtypeSEXP) { @@ -6825,59 +6815,66 @@ BEGIN_RCPP END_RCPP } // cpp_torch_method_to_sparse_self_Tensor -XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_self_Tensor(SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor(XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_self_Tensor(SEXP selfSEXP, SEXP layoutSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_self_Tensor(self)); + Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type blocksize(blocksizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_self_Tensor(self, layout, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_csr_self_Tensor -XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_csr_self_Tensor(SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_csr_self_Tensor(SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csr_self_Tensor(self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csr_self_Tensor(self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_csc_self_Tensor -XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_csc_self_Tensor(SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_csc_self_Tensor(SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csc_self_Tensor(self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_csc_self_Tensor(self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef(self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef(self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } @@ -9156,19 +9153,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method_symeig_self_Tensor -Rcpp::List cpp_torch_method_symeig_self_Tensor(XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_method_symeig_self_Tensor(SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method_symeig_self_Tensor(self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_method_svd_self_Tensor Rcpp::List cpp_torch_method_svd_self_Tensor(XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv); RcppExport SEXP _torch_cpp_torch_method_svd_self_Tensor(SEXP selfSEXP, SEXP someSEXP, SEXP compute_uvSEXP) { @@ -10411,20 +10395,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double -XPtrTorchTensor cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double(XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps); -RcppExport SEXP _torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double(SEXP selfSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP epsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double(self, weight, bias, eps)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__cast_Byte_self_Tensor XPtrTorchTensor cpp_torch_namespace__cast_Byte_self_Tensor(XPtrTorchTensor self, XPtrTorchbool non_blocking); RcppExport SEXP _torch_cpp_torch_namespace__cast_Byte_self_Tensor(SEXP selfSEXP, SEXP non_blockingSEXP) { @@ -11570,6 +11540,39 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__is_all_true_self_Tensor +XPtrTorchTensor cpp_torch_namespace__is_all_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__is_all_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__is_all_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__is_any_true_self_Tensor +XPtrTorchTensor cpp_torch_namespace__is_any_true_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__is_any_true_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__is_any_true_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_check_tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_check_tensor_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_check_tensor_self_Tensor(SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_check_tensor_self_Tensor(self)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_all_self_Tensor_dim_int64_t XPtrTorchTensor cpp_torch_namespace_all_self_Tensor_dim_int64_t(XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP keepdimSEXP) { @@ -18137,25 +18140,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef(SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef(self, kernel_size, stride, padding, dilation, ceil_mode)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { +// cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); +RcppExport SEXP _torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -18166,7 +18153,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); return rcpp_result_gen; END_RCPP } @@ -18654,6 +18641,65 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(SEXP inputSEXP, SEXP weight0SEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP hx_SEXP, SEXP cx_SEXP, SEXP reverseSEXP, SEXP batch_sizesSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP, SEXP trainSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight0(weight0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_(cx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(SEXP inputSEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP weight4SEXP, SEXP hx_SEXP, SEXP cx_tmpSEXP, SEXP outputSEXP, SEXP hy_SEXP, SEXP cy_SEXP, SEXP grad_outputSEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP reverseSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_sizesSEXP, SEXP batch_firstSEXP, SEXP workspaceSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight4(weight4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_tmp(cx_tmpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hy_(hy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cy_(cy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_hy(grad_hySEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_cy(grad_cySEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type workspace(workspaceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double Rcpp::List cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon); RcppExport SEXP _torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP exponential_average_factorSEXP, SEXP epsilonSEXP) { @@ -18876,27 +18922,28 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor -XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view +XPtrTorchTensor cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view(XPtrTorchTensor sparse, XPtrTorchTensor dense, XPtrTorchstring_view reduce); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view(SEXP sparseSEXP, SEXP denseSEXP, SEXP reduceSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type other(otherSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(self, other)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type sparse(sparseSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type dense(denseSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view(sparse, dense, reduce)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor(XPtrTorchTensor t, XPtrTorchTensor mask_indices); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor(SEXP tSEXP, SEXP mask_indicesSEXP) { +// cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor +XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type t(tSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type mask_indices(mask_indicesSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor(t, mask_indices)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor(self, other)); return rcpp_result_gen; END_RCPP } @@ -19176,6 +19223,80 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_mean(running_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_var(running_varSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(input, weight, bias, running_mean, running_var, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(SEXP outSEXP, SEXP save_meanSEXP, SEXP save_invstdSEXP, SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_mean(save_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_invstd(save_invstdSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_mean(running_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_var(running_varSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(input, weight, bias, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(SEXP outSEXP, SEXP save_meanSEXP, SEXP save_invstdSEXP, SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_mean(save_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type save_invstd(save_invstdSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double Rcpp::List cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double(XPtrTorchTensor input, XPtrTorchdouble eps); RcppExport SEXP _torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double(SEXP inputSEXP, SEXP epsSEXP) { @@ -20321,6 +20442,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef(self, size)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef XPtrTorchTensor cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride); RcppExport SEXP _torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP) { @@ -20503,16 +20636,28 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor -Rcpp::List cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { +// cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor +XPtrTorchTensor cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor(XPtrTorchTensor self, XPtrTorchTensor weight); +RcppExport SEXP _torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor(SEXP selfSEXP, SEXP weightSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor(self, weight)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor +Rcpp::List cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); +RcppExport SEXP _torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor(grad_output, self, weight)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor(grad_output, self, weight)); return rcpp_result_gen; END_RCPP } @@ -21473,6 +21618,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor XPtrTorchTensor cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor(XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor(SEXP selfSEXP, SEXP mat1SEXP, SEXP mat2SEXP, SEXP betaSEXP, SEXP alphaSEXP) { @@ -21894,20 +22051,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_mean_self_Tensor Rcpp::List cpp_torch_namespace_std_mean_self_Tensor(XPtrTorchTensor self, XPtrTorchbool unbiased); RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor(SEXP selfSEXP, SEXP unbiasedSEXP) { @@ -21934,20 +22077,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -21962,20 +22091,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -21991,21 +22106,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_std_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22035,35 +22135,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_prod_self_Tensor XPtrTorchTensor cpp_torch_namespace_prod_self_Tensor(XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype); RcppExport SEXP _torch_cpp_torch_namespace_prod_self_Tensor(SEXP selfSEXP, SEXP dtypeSEXP) { @@ -22837,20 +22908,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22866,21 +22923,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_self_Tensor_dim_DimnameList XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22910,35 +22952,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t(out, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_mean_self_Tensor Rcpp::List cpp_torch_namespace_var_mean_self_Tensor(XPtrTorchTensor self, XPtrTorchbool unbiased); RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor(SEXP selfSEXP, SEXP unbiasedSEXP) { @@ -22965,20 +22978,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList(SEXP selfSEXP, SEXP dimSEXP, SEXP unbiasedSEXP, SEXP keepdimSEXP) { @@ -22993,20 +22992,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t(XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t(SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDimnameList >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t(self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor(XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchTensor other); RcppExport SEXP _torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor(SEXP conditionSEXP, SEXP selfSEXP, SEXP otherSEXP) { @@ -23694,17 +23679,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_frobenius_norm_self_Tensor -XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_frobenius_norm_self_Tensor(SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_frobenius_norm_self_Tensor(self)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim, XPtrTorchbool keepdim); RcppExport SEXP _torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP, SEXP keepdimSEXP) { @@ -24020,6 +23994,35 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view(XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchstring_view reduce); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view(SEXP selfSEXP, SEXP otherSEXP, SEXP reduceSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type other(otherSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view(self, other, reduce)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2 +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2(XPtrTorchTensor self, XPtrTorchTensor grad_out, XPtrTorchTensor weight, XPtrTorchstring_view reduce, XPtrTorchTensor arg_out, std::vector output_mask); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2(SEXP selfSEXP, SEXP grad_outSEXP, SEXP weightSEXP, SEXP reduceSEXP, SEXP arg_outSEXP, SEXP output_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out(grad_outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type arg_out(arg_outSEXP); + Rcpp::traits::input_parameter< std::vector >::type output_mask(output_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2(self, grad_out, weight, reduce, arg_out, output_mask)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor XPtrTorchTensor cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP mat1SEXP, SEXP mat2SEXP, SEXP betaSEXP, SEXP alphaSEXP) { @@ -24562,8 +24565,8 @@ BEGIN_RCPP END_RCPP } // cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups); -RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP) { +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP, SEXP input_sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -24572,7 +24575,8 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type groups(groupsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(self, padding, stride, dilation, groups)); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type input_size(input_sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor(self, padding, stride, dilation, groups, input_size)); return rcpp_result_gen; END_RCPP } @@ -25220,9 +25224,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool -Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); -RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { +// cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool +Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); +RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP layersOutputsSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -25232,6 +25236,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type z_state(z_stateSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type cell_state_fwd(cell_state_fwdSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type layersOutputs(layersOutputsSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type hx(hxSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type params(paramsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); @@ -25240,7 +25245,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); return rcpp_result_gen; END_RCPP } @@ -26666,19 +26671,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t -XPtrTorchTensor cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t(XPtrTorchTensor grad, XPtrTorchIntArrayRef input_sizes, XPtrTorchint64_t diagonal); -RcppExport SEXP _torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t(SEXP gradSEXP, SEXP input_sizesSEXP, SEXP diagonalSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad(gradSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_sizes(input_sizesSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type diagonal(diagonalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t(grad, input_sizes, diagonal)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchoptional_index_int64_t dim); RcppExport SEXP _torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP, SEXP dimSEXP) { @@ -27808,47 +27800,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor -Rcpp::List cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor(XPtrTorchTensor e, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor(SEXP eSEXP, SEXP VSEXP, SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type e(eSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type V(VSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor(e, V, self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_symeig_self_Tensor -Rcpp::List cpp_torch_namespace_symeig_self_Tensor(XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace_symeig_self_Tensor(SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_symeig_self_Tensor(self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool -Rcpp::List cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool(XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool(SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool(self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor Rcpp::List cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor(XPtrTorchTensor U, XPtrTorchTensor S, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv); RcppExport SEXP _torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor(SEXP USEXP, SEXP SSEXP, SEXP VSEXP, SEXP selfSEXP, SEXP someSEXP, SEXP compute_uvSEXP) { @@ -28993,6 +28944,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_max_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_max_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_max_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_minimum_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace_minimum_self_Tensor_other_Tensor(XPtrTorchTensor self, XPtrTorchTensor other); RcppExport SEXP _torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor(SEXP selfSEXP, SEXP otherSEXP) { @@ -29832,6 +29795,98 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar(self, scalar)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar(XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar(SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar(self, scalar); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP, SEXP alphaSEXP) { @@ -29928,6 +29983,98 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(self, other)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(self, other); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { @@ -30020,6 +30167,98 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar(self, scalars)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar(self, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_exp_self_TensorList XPtrTorchTensorList cpp_torch_namespace__foreach_exp_self_TensorList(XPtrTorchTensorList self); RcppExport SEXP _torch_cpp_torch_namespace__foreach_exp_self_TensorList(SEXP selfSEXP) { @@ -30657,6 +30896,19 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { @@ -30670,6 +30922,19 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchScalar value); RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP valueSEXP) { @@ -30712,6 +30977,20 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { @@ -30726,64 +31005,82 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList -XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList(self, other)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(self, tensor1, tensor2, scalars)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_norm_self_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList(XPtrTorchTensorList self, XPtrTorchScalar ord); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_norm_self_TensorList(SEXP selfSEXP, SEXP ordSEXP) { BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList(self, other); - return R_NilValue; + Rcpp::traits::input_parameter< XPtrTorchScalar >::type ord(ordSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_norm_self_TensorList(self, ord)); + return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList -XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList(self, other)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type weights(weightsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList(self, tensors1, weights)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList(self, other); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type weights(weightsSEXP); + cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList(self, tensors1, weights); return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_norm_self_TensorList -XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList(XPtrTorchTensorList self, XPtrTorchScalar ord); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_norm_self_TensorList(SEXP selfSEXP, SEXP ordSEXP) { +// cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchScalar >::type ord(ordSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_norm_self_TensorList(self, ord)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type weight(weightSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar(self, tensors1, weight)); return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar(XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar(SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type weight(weightSEXP); + cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar(self, tensors1, weight); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor XPtrTorchTensor cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor(XPtrTorchTensor self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right); RcppExport SEXP _torch_cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor(SEXP selfSEXP, SEXP boundariesSEXP, SEXP out_int32SEXP, SEXP rightSEXP) { @@ -30843,17 +31140,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor(SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor(self)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor XPtrTorchTensor cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor sorted_sequence, XPtrTorchTensor self, XPtrTorchbool out_int32, XPtrTorchbool right, XPtrTorchoptional_string_view side, XPtrTorchOptionalTensor sorter); RcppExport SEXP _torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor(SEXP outSEXP, SEXP sorted_sequenceSEXP, SEXP selfSEXP, SEXP out_int32SEXP, SEXP rightSEXP, SEXP sideSEXP, SEXP sorterSEXP) { @@ -33285,21 +33571,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33314,21 +33585,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33343,21 +33599,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33372,21 +33613,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33401,21 +33627,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { @@ -33430,21 +33641,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, align_corners, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { @@ -33471,34 +33667,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { @@ -33525,34 +33693,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { @@ -33579,34 +33719,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(grad_output, output_size, input_size, scale_factors)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionaldouble scales); RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool(SEXP outSEXP, SEXP selfSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scalesSEXP) { @@ -38395,6 +38507,18 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef(XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef(SEXP selfSEXP, SEXP dimSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef(self, dim)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_t_copy_self_Tensor XPtrTorchTensor cpp_torch_namespace_t_copy_self_Tensor(XPtrTorchTensor self); RcppExport SEXP _torch_cpp_torch_namespace_t_copy_self_Tensor(SEXP selfSEXP) { @@ -38531,254 +38655,16 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(self, size)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType -XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(XPtrTorchTensor self, XPtrTorchDtype dtype); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(SEXP selfSEXP, SEXP dtypeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchDtype >::type dtype(dtypeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(self, dtype)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t -XPtrTorchTensor cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); -RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type dimension(dimensionSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(self, dimension, size, step)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_alias_copy_self_Tensor -XPtrTorchTensor cpp_torch_namespace_alias_copy_self_Tensor(XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_self_Tensor(SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_self_Tensor(self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t -XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level); -RcppExport SEXP _torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP levelSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(out, self, level)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t -XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level); -RcppExport SEXP _torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(SEXP outSEXP, SEXP primalSEXP, SEXP tangentSEXP, SEXP levelSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type primal(primalSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type tangent(tangentSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(out, primal, tangent, level)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset); -RcppExport SEXP _torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP, SEXP storage_offsetSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type storage_offset(storage_offsetSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride, storage_offset)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2); -RcppExport SEXP _torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP offsetSEXP, SEXP dim1SEXP, SEXP dim2SEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type offset(offsetSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim2(dim2SEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(out, self, offset, dim1, dim2)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit); -RcppExport SEXP _torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP implicitSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type implicit(implicitSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size, implicit)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims); -RcppExport SEXP _torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dims(dimsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(out, self, dims)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride); -RcppExport SEXP _torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t -XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index); -RcppExport SEXP _torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP indexSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type index(indexSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(out, self, dim, index)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step); -RcppExport SEXP _torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP startSEXP, SEXP endSEXP, SEXP stepSEXP) { +// cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor +void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); +RcppExport SEXP _torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type start(startSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type end(endSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(out, self, dim, start, end, step)); - return rcpp_result_gen; + cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(out, self, dim); + return R_NilValue; END_RCPP } // cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t @@ -38807,204 +38693,52 @@ BEGIN_RCPP return R_NilValue; END_RCPP } -// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); -RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t -XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1); -RcppExport SEXP _torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dim0SEXP, SEXP dim1SEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim0(dim0SEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(out, self, dim0, dim1)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t -XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); -RcppExport SEXP _torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor -void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); -RcppExport SEXP _torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { -BEGIN_RCPP - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); - cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor(out, self, dim); - return R_NilValue; -END_RCPP -} -// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { +// cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(SEXP selfSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef(self, size)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype); -RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(SEXP outSEXP, SEXP selfSEXP, SEXP dtypeSEXP) { +// cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType +XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(XPtrTorchTensor self, XPtrTorchDtype dtype); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(SEXP selfSEXP, SEXP dtypeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchDtype >::type dtype(dtypeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(out, self, dtype)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType(self, dtype)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t -XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); -RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { +// cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t +XPtrTorchTensor cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); +RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type dimension(dimensionSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type size(sizeSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(out, self, dimension, size, step)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(self, dimension, size, step)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_alias_copy_self_Tensor +XPtrTorchTensor cpp_torch_namespace_alias_copy_self_Tensor(XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_self_Tensor(SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_self_Tensor(self)); return rcpp_result_gen; END_RCPP } @@ -39073,6 +38807,22 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor +XPtrTorchTensor cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type attn_mask(attn_maskSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, is_causal)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal); RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP need_attn_weightsSEXP, SEXP is_causalSEXP) { @@ -39090,9 +38840,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal); -RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP need_attn_weightsSEXP, SEXP is_causalSEXP) { +// cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor +XPtrTorchint64_t cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -39101,15 +38851,14 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type attn_mask(attn_maskSEXP); Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type need_attn_weights(need_attn_weightsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, is_causal)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal); -RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP need_attn_weightsSEXP, SEXP is_causalSEXP) { +Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchOptionalTensor dropout_mask); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP attn_maskSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP dropout_maskSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -39118,9 +38867,176 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type attn_mask(attn_maskSEXP); Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type need_attn_weights(need_attn_weightsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal)); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type dropout_mask(dropout_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP return_debug_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type return_debug_mask(return_debug_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor(query, key, value, dropout_p, is_causal, return_debug_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(SEXP grad_outSEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP philox_seedSEXP, SEXP philox_offsetSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out(grad_outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_seed(philox_seedSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_offset(philox_offsetSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool compute_log_sumexp, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP compute_log_sumexpSEXP, SEXP is_causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type compute_log_sumexp(compute_log_sumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool(query, key, value, compute_log_sumexp, is_causal)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs); +RcppExport SEXP _torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(SEXP grad_out_SEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP is_causalSEXP, SEXP chunk_grad_outputsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out_(grad_out_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type chunk_grad_outputs(chunk_grad_outputsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor +XPtrTorchbool cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool is_causal); +RcppExport SEXP _torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP is_causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor(query, key, value, is_causal)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool +Rcpp::List cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask); +RcppExport SEXP _torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP return_debug_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type return_debug_mask(return_debug_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t +Rcpp::List cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset); +RcppExport SEXP _torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(SEXP grad_outSEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP, SEXP philox_seedSEXP, SEXP philox_offsetSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out(grad_outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_seed(philox_seedSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type philox_offset(philox_offsetSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t +Rcpp::List cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor cu_seqlens_q, XPtrTorchOptionalTensor cu_seqlens_k, XPtrTorchoptional_int64_t max_seqlen_q, XPtrTorchbool compute_log_sumexp, XPtrTorchbool causal); +RcppExport SEXP _torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP cu_seqlens_qSEXP, SEXP cu_seqlens_kSEXP, SEXP max_seqlen_qSEXP, SEXP compute_log_sumexpSEXP, SEXP causalSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type cu_seqlens_q(cu_seqlens_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type cu_seqlens_k(cu_seqlens_kSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type max_seqlen_q(max_seqlen_qSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type compute_log_sumexp(compute_log_sumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type causal(causalSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor +Rcpp::List cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs); +RcppExport SEXP _torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(SEXP grad_out_SEXP, SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP outSEXP, SEXP logsumexpSEXP, SEXP is_causalSEXP, SEXP chunk_grad_outputsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_out_(grad_out_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type logsumexp(logsumexpSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type chunk_grad_outputs(chunk_grad_outputsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs)); return rcpp_result_gen; END_RCPP } @@ -39181,25 +39097,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool -XPtrTorchTensor cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool(XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal); -RcppExport SEXP _torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool(SEXP querySEXP, SEXP keySEXP, SEXP valueSEXP, SEXP cum_seq_qSEXP, SEXP cum_seq_kSEXP, SEXP max_qSEXP, SEXP max_kSEXP, SEXP dropout_pSEXP, SEXP is_causalSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type query(querySEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type key(keySEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type value(valueSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_q(cum_seq_qSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type cum_seq_k(cum_seq_kSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_q(max_qSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type max_k(max_kSEXP); - Rcpp::traits::input_parameter< XPtrTorchdouble >::type dropout_p(dropout_pSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type is_causal(is_causalSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor Rcpp::List cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchOptionalTensor incr_key, XPtrTorchOptionalTensor incr_value); RcppExport SEXP _torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(SEXP srcSEXP, SEXP embed_dimSEXP, SEXP num_headsSEXP, SEXP qkv_weightSEXP, SEXP qkv_biasSEXP, SEXP proj_weightSEXP, SEXP proj_biasSEXP, SEXP use_geluSEXP, SEXP norm_firstSEXP, SEXP epsSEXP, SEXP norm_weight_1SEXP, SEXP norm_bias_1SEXP, SEXP norm_weight_2SEXP, SEXP norm_bias_2SEXP, SEXP ffn_weight_1SEXP, SEXP ffn_bias_1SEXP, SEXP ffn_weight_2SEXP, SEXP ffn_bias_2SEXP, SEXP maskSEXP, SEXP incr_keySEXP, SEXP incr_valueSEXP) { @@ -40446,6 +40343,30 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool +void cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf); +RcppExport SEXP _torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(SEXP selfSEXP, SEXP gradsSEXP, SEXP exp_avgsSEXP, SEXP exp_avg_sqsSEXP, SEXP max_exp_avg_sqsSEXP, SEXP state_stepsSEXP, SEXP lrSEXP, SEXP beta1SEXP, SEXP beta2SEXP, SEXP weight_decaySEXP, SEXP epsSEXP, SEXP amsgradSEXP, SEXP maximizeSEXP, SEXP grad_scaleSEXP, SEXP found_infSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type grads(gradsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avgs(exp_avgsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avg_sqs(exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type max_exp_avg_sqs(max_exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type state_steps(state_stepsSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type lr(lrSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta1(beta1SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta2(beta2SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type weight_decay(weight_decaySEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type amsgrad(amsgradSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type maximize(maximizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_scale(grad_scaleSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type found_inf(found_infSEXP); + cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor XPtrTorchTensor cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchint64_t self_num_batch_dims); RcppExport SEXP _torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP, SEXP self_num_batch_dimsSEXP) { @@ -41290,6 +41211,24 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor +Rcpp::List cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchTensor input_lengths, XPtrTorchTensor target_lengths, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity); +RcppExport SEXP _torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP log_probsSEXP, SEXP targetsSEXP, SEXP input_lengthsSEXP, SEXP target_lengthsSEXP, SEXP blankSEXP, SEXP zero_infinitySEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type log_probs(log_probsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type targets(targetsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input_lengths(input_lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type target_lengths(target_lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type blank(blankSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type zero_infinity(zero_infinitySEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t XPtrTorchTensor cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t(XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchIntArrayRef input_lengths, XPtrTorchIntArrayRef target_lengths, XPtrTorchTensor neg_log_likelihood, XPtrTorchTensor log_alpha, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity); RcppExport SEXP _torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t(SEXP outSEXP, SEXP gradSEXP, SEXP log_probsSEXP, SEXP targetsSEXP, SEXP input_lengthsSEXP, SEXP target_lengthsSEXP, SEXP neg_log_likelihoodSEXP, SEXP log_alphaSEXP, SEXP blankSEXP, SEXP zero_infinitySEXP) { @@ -42255,26 +42194,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef(out, self, kernel_size, stride, padding, dilation, ceil_mode)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); -RcppExport SEXP _torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { +// cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode); +RcppExport SEXP _torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP, SEXP ceil_modeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -42286,7 +42208,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type ceil_mode(ceil_modeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode)); return rcpp_result_gen; END_RCPP } @@ -42477,6 +42399,76 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP inputSEXP, SEXP weight0SEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP hx_SEXP, SEXP cx_SEXP, SEXP reverseSEXP, SEXP batch_sizesSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP, SEXP trainSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out3(out3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight0(weight0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_(cx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor out6, XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP out4SEXP, SEXP out5SEXP, SEXP out6SEXP, SEXP inputSEXP, SEXP weight1SEXP, SEXP weight2SEXP, SEXP weight3SEXP, SEXP weight4SEXP, SEXP hx_SEXP, SEXP cx_tmpSEXP, SEXP outputSEXP, SEXP hy_SEXP, SEXP cy_SEXP, SEXP grad_outputSEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP reverseSEXP, SEXP modeSEXP, SEXP hidden_sizeSEXP, SEXP num_layersSEXP, SEXP has_biasesSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_sizesSEXP, SEXP batch_firstSEXP, SEXP workspaceSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out3(out3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out4(out4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out5(out5SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out6(out6SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight1(weight1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight2(weight2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight3(weight3SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight4(weight4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hx_(hx_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cx_tmp(cx_tmpSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type hy_(hy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type cy_(cy_SEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_hy(grad_hySEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_cy(grad_cySEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type reverse(reverseSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type mode(modeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type hidden_size(hidden_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type num_layers(num_layersSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type batch_sizes(batch_sizesSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type workspace(workspaceSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double Rcpp::List cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon); RcppExport SEXP _torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP exponential_average_factorSEXP, SEXP epsilonSEXP) { @@ -42656,19 +42648,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor(XPtrTorchTensor out, XPtrTorchTensor t, XPtrTorchTensor mask_indices); -RcppExport SEXP _torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor(SEXP outSEXP, SEXP tSEXP, SEXP mask_indicesSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type t(tSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type mask_indices(mask_indicesSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor(out, t, mask_indices)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar XPtrTorchTensor cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchScalar other); RcppExport SEXP _torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { @@ -42682,6 +42661,24 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps); +RcppExport SEXP _torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(SEXP inputSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP running_meanSEXP, SEXP running_varSEXP, SEXP trainingSEXP, SEXP momentumSEXP, SEXP epsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_mean(running_meanSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type running_var(running_varSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type training(trainingSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type momentum(momentumSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double(input, weight, bias, running_mean, running_var, training, momentum, eps)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double Rcpp::List cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor input, XPtrTorchdouble eps); RcppExport SEXP _torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double(SEXP out0SEXP, SEXP out1SEXP, SEXP inputSEXP, SEXP epsSEXP) { @@ -43154,34 +43151,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor -XPtrTorchTensor cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor(out, self, weight)); - return rcpp_result_gen; -END_RCPP -} -// cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor -Rcpp::List cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight); -RcppExport SEXP _torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor(out0, out1, grad_output, self, weight)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t XPtrTorchTensor cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchIntArrayRef input_sizes, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index); RcppExport SEXP _torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t(SEXP outSEXP, SEXP grad_outputSEXP, SEXP input_sizesSEXP, SEXP dimSEXP, SEXP indexSEXP) { @@ -43330,22 +43299,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP out0SEXP, SEXP out1SEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out0, out1, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_prod_out_out_Tensor_self_Tensor XPtrTorchTensor cpp_torch_namespace_prod_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype); RcppExport SEXP _torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dtypeSEXP) { @@ -43626,22 +43579,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t -Rcpp::List cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim); -RcppExport SEXP _torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(SEXP out0SEXP, SEXP out1SEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP correctionSEXP, SEXP keepdimSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIndexIntArrayRef >::type dim(dimSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type correction(correctionSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type keepdim(keepdimSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t(out0, out1, self, dim, correction, keepdim)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor Rcpp::List cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor v, XPtrTorchTensor g, XPtrTorchindex_int64_t dim); RcppExport SEXP _torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor(SEXP out0SEXP, SEXP out1SEXP, SEXP vSEXP, SEXP gSEXP, SEXP dimSEXP) { @@ -44328,64 +44265,71 @@ BEGIN_RCPP END_RCPP } // cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP layoutSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type blocksize(blocksizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor(out, self, layout, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor(out, self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor(out, self, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } // cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize); -RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP) { +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim); +RcppExport SEXP _torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP blocksizeSEXP, SEXP dense_dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type blocksize(blocksizeSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize)); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type dense_dim(dense_dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef(out, self, blocksize, dense_dim)); return rcpp_result_gen; END_RCPP } @@ -44403,8 +44347,8 @@ BEGIN_RCPP END_RCPP } // cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups); -RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP) { +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size); +RcppExport SEXP _torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP paddingSEXP, SEXP strideSEXP, SEXP dilationSEXP, SEXP groupsSEXP, SEXP input_sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -44414,7 +44358,8 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); Rcpp::traits::input_parameter< XPtrTorchint64_t >::type groups(groupsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(out, self, padding, stride, dilation, groups)); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type input_size(input_sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor(out, self, padding, stride, dilation, groups, input_size)); return rcpp_result_gen; END_RCPP } @@ -44746,9 +44691,9 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool -Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); -RcppExport SEXP _torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP out4SEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { +// cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool +Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); +RcppExport SEXP _torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP out3SEXP, SEXP out4SEXP, SEXP out5SEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; @@ -44757,6 +44702,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type out3(out3SEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type out4(out4SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out5(out5SEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type hx(hxSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type params(paramsSEXP); @@ -44766,13 +44712,13 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool -void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); -RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { +// cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool +void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first); +RcppExport SEXP _torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_ySEXP, SEXP grad_hySEXP, SEXP grad_cySEXP, SEXP z_stateSEXP, SEXP cell_state_fwdSEXP, SEXP inputSEXP, SEXP layersOutputsSEXP, SEXP hxSEXP, SEXP paramsSEXP, SEXP has_biasesSEXP, SEXP num_layersSEXP, SEXP dropoutSEXP, SEXP trainSEXP, SEXP bidirectionalSEXP, SEXP batch_firstSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); @@ -44784,6 +44730,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchTensor >::type z_state(z_stateSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type cell_state_fwd(cell_state_fwdSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type layersOutputs(layersOutputsSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type hx(hxSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type params(paramsSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type has_biases(has_biasesSEXP); @@ -44792,7 +44739,7 @@ BEGIN_RCPP Rcpp::traits::input_parameter< XPtrTorchbool >::type train(trainSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type bidirectional(bidirectionalSEXP); Rcpp::traits::input_parameter< XPtrTorchbool >::type batch_first(batch_firstSEXP); - cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); + cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); return R_NilValue; END_RCPP } @@ -45507,21 +45454,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool -Rcpp::List cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper); -RcppExport SEXP _torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool(SEXP out0SEXP, SEXP out1SEXP, SEXP selfSEXP, SEXP eigenvectorsSEXP, SEXP upperSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type eigenvectors(eigenvectorsSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type upper(upperSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool(out0, out1, self, eigenvectors, upper)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool XPtrTorchTensor cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor A, XPtrTorchbool upper); RcppExport SEXP _torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool(SEXP outSEXP, SEXP selfSEXP, SEXP ASEXP, SEXP upperSEXP) { @@ -45762,6 +45694,54 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type scalar(scalarSEXP); + cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar(out, self, scalar); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP, SEXP alphaSEXP) { @@ -45812,6 +45792,54 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); + cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); RcppExport SEXP _torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { @@ -45860,6 +45888,54 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP scalarsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar(out, self, scalars); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList void cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self); RcppExport SEXP _torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList(SEXP outSEXP, SEXP selfSEXP) { @@ -46232,41 +46308,45 @@ BEGIN_RCPP return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar -void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { +// cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); - Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); - cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(out, self, tensor1, tensor2, scalars); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(out, self, tensor1, tensor2, scalars); return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchvector_Scalar >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar(out, self, tensor1, tensor2, scalars); return R_NilValue; END_RCPP } -// cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList -void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other); -RcppExport SEXP _torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP otherSEXP) { +// cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP tensor1SEXP, SEXP tensor2SEXP, SEXP scalarsSEXP) { BEGIN_RCPP Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type other(otherSEXP); - cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList(out, self, other); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor1(tensor1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensor2(tensor2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type scalars(scalarsSEXP); + cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor(out, self, tensor1, tensor2, scalars); return R_NilValue; END_RCPP } @@ -46282,6 +46362,32 @@ BEGIN_RCPP return R_NilValue; END_RCPP } +// cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList(SEXP outSEXP, SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightsSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type weights(weightsSEXP); + cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList(out, self, tensors1, weights); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight); +RcppExport SEXP _torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar(SEXP outSEXP, SEXP selfSEXP, SEXP tensors1SEXP, SEXP weightSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type tensors1(tensors1SEXP); + Rcpp::traits::input_parameter< XPtrTorchScalar >::type weight(weightSEXP); + cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar(out, self, tensors1, weight); + return R_NilValue; +END_RCPP +} // cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor XPtrTorchTensor cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor(XPtrTorchTensor out, XPtrTorchScalar self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right); RcppExport SEXP _torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP boundariesSEXP, SEXP out_int32SEXP, SEXP rightSEXP) { @@ -46297,18 +46403,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor(out, self)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar XPtrTorchTensor cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar(XPtrTorchTensor out, XPtrTorchTensor sorted_sequence, XPtrTorchScalar self, XPtrTorchbool out_int32, XPtrTorchbool right, XPtrTorchoptional_string_view side, XPtrTorchOptionalTensor sorter); RcppExport SEXP _torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar(SEXP outSEXP, SEXP sorted_sequenceSEXP, SEXP selfSEXP, SEXP out_int32SEXP, SEXP rightSEXP, SEXP sideSEXP, SEXP sorterSEXP) { @@ -46454,614 +46548,657 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 +Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask); +RcppExport SEXP _torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP output_maskSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< std::vector >::type output_mask(output_maskSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); +RcppExport SEXP _torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); +RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); +RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); +RcppExport SEXP _torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); +RcppExport SEXP _torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble +XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends); +RcppExport SEXP _torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type addends(addendsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(out, values, addends)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(out, self)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view +XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial); +RcppExport SEXP _torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP indicesSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP unsafeSEXP, SEXP initialSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexTensor >::type indices(indicesSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type unsafe(unsafeSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial)); + return rcpp_result_gen; +END_RCPP +} +// cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view +XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial); +RcppExport SEXP _torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP gradSEXP, SEXP outputSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP initialSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad(gradSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); + Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(out, grad, output, data, reduce, lengths, offsets, axis, initial)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList +XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory); +RcppExport SEXP _torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(SEXP outSEXP, SEXP listSEXP, SEXP dtypeSEXP, SEXP layoutSEXP, SEXP deviceSEXP, SEXP pin_memorySEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type list(listSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_scalar_type >::type dtype(dtypeSEXP); + Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); + Rcpp::traits::input_parameter< XPtrTorchDevice >::type device(deviceSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_bool >::type pin_memory(pin_memorySEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(out, list, dtype, layout, device, pin_memory)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t +XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level); +RcppExport SEXP _torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP levelSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t(out, self, level)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t +XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level); +RcppExport SEXP _torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(SEXP outSEXP, SEXP primalSEXP, SEXP tangentSEXP, SEXP levelSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type primal(primalSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type tangent(tangentSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type level(levelSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t(out, primal, tangent, level)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, input, output_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP align_cornersSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type align_corners(align_cornersSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset); +RcppExport SEXP _torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP, SEXP storage_offsetSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type storage_offset(storage_offsetSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride, storage_offset)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2); +RcppExport SEXP _torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP offsetSEXP, SEXP dim1SEXP, SEXP dim2SEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type offset(offsetSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim2(dim2SEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor(out, self, offset, dim1, dim2)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit); +RcppExport SEXP _torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP implicitSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type implicit(implicitSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size, implicit)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims); +RcppExport SEXP _torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimsSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dims(dimsSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef(out, self, dims)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef +XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride); +RcppExport SEXP _torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP, SEXP strideSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef(out, self, size, stride)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t +XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index); +RcppExport SEXP _torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP indexSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type index(indexSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t(out, self, dim, index)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP inputSEXP, SEXP output_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type input(inputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble(out, input, output_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step); +RcppExport SEXP _torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP, SEXP startSEXP, SEXP endSEXP, SEXP stepSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type start(startSEXP); + Rcpp::traits::input_parameter< XPtrTorchoptional_int64_t >::type end(endSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor(out, self, dim, start, end, step)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors); -RcppExport SEXP _torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(SEXP outSEXP, SEXP grad_outputSEXP, SEXP output_sizeSEXP, SEXP input_sizeSEXP, SEXP scale_factorsSEXP) { +// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type output_size(output_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type input_size(input_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type scale_factors(scale_factorsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble(out, grad_output, output_size, input_size, scale_factors)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 -Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask); -RcppExport SEXP _torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(SEXP out0SEXP, SEXP out1SEXP, SEXP out2SEXP, SEXP grad_outputSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP output_maskSEXP) { +// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out0(out0SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out1(out1SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out2(out2SEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad_output(grad_outputSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< std::vector >::type output_mask(output_maskSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask)); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); -RcppExport SEXP _torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { +// cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim); +RcppExport SEXP _torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); + Rcpp::traits::input_parameter< XPtrTorchIndexIntArrayRef >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef(out, self, dim)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); -RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { +// cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation); -RcppExport SEXP _torch_cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP kernel_sizeSEXP, SEXP biasSEXP, SEXP strideSEXP, SEXP paddingSEXP, SEXP dilationSEXP) { +// cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t +XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1); +RcppExport SEXP _torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dim0SEXP, SEXP dim1SEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type kernel_size(kernel_sizeSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type stride(strideSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type padding(paddingSEXP); - Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type dilation(dilationSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef(out, self, weight, kernel_size, bias, stride, padding, dilation)); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim0(dim0SEXP); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim1(dim1SEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t(out, self, dim0, dim1)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t +XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim); +RcppExport SEXP _torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchindex_int64_t >::type dim(dimSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t(out, self, dim)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); -RcppExport SEXP _torch_cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +// cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef -XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends); -RcppExport SEXP _torch_cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +// cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalIntArrayRef >::type addends(addendsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef(out, values, addends)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble -XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends); -RcppExport SEXP _torch_cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(SEXP outSEXP, SEXP valuesSEXP, SEXP addendsSEXP) { +// cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type values(valuesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalDoubleArrayRef >::type addends(addendsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble(out, values, addends)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view -XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial); -RcppExport SEXP _torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP indicesSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP unsafeSEXP, SEXP initialSEXP) { +// cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); - Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); - Rcpp::traits::input_parameter< XPtrTorchIndexTensor >::type indices(indicesSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); - Rcpp::traits::input_parameter< XPtrTorchbool >::type unsafe(unsafeSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view(out, data, reduce, lengths, indices, offsets, axis, unsafe, initial)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view -XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial); -RcppExport SEXP _torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(SEXP outSEXP, SEXP gradSEXP, SEXP outputSEXP, SEXP dataSEXP, SEXP reduceSEXP, SEXP lengthsSEXP, SEXP offsetsSEXP, SEXP axisSEXP, SEXP initialSEXP) { +// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(SEXP outSEXP, SEXP selfSEXP, SEXP sizeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type grad(gradSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type output(outputSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type data(dataSEXP); - Rcpp::traits::input_parameter< XPtrTorchstring_view >::type reduce(reduceSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type lengths(lengthsSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type offsets(offsetsSEXP); - Rcpp::traits::input_parameter< XPtrTorchint64_t >::type axis(axisSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_scalar >::type initial(initialSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view(out, grad, output, data, reduce, lengths, offsets, axis, initial)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchIntArrayRef >::type size(sizeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef(out, self, size)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList -XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory); -RcppExport SEXP _torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(SEXP outSEXP, SEXP listSEXP, SEXP dtypeSEXP, SEXP layoutSEXP, SEXP deviceSEXP, SEXP pin_memorySEXP) { +// cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype); +RcppExport SEXP _torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(SEXP outSEXP, SEXP selfSEXP, SEXP dtypeSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensorList >::type list(listSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_scalar_type >::type dtype(dtypeSEXP); - Rcpp::traits::input_parameter< XPtrTorchLayout >::type layout(layoutSEXP); - Rcpp::traits::input_parameter< XPtrTorchDevice >::type device(deviceSEXP); - Rcpp::traits::input_parameter< XPtrTorchoptional_bool >::type pin_memory(pin_memorySEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList(out, list, dtype, layout, device, pin_memory)); + Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchDtype >::type dtype(dtypeSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType(out, self, dtype)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t +XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step); +RcppExport SEXP _torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(SEXP outSEXP, SEXP selfSEXP, SEXP dimensionSEXP, SEXP sizeSEXP, SEXP stepSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor(out, self)); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type dimension(dimensionSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type size(sizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchint64_t >::type step(stepSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t(out, self, dimension, size, step)); return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor -XPtrTorchTensor cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); -RcppExport SEXP _torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { +// cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor +XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(XPtrTorchTensor out, XPtrTorchTensor self); +RcppExport SEXP _torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(SEXP outSEXP, SEXP selfSEXP) { BEGIN_RCPP Rcpp::RObject rcpp_result_gen; Rcpp::RNGScope rcpp_rngScope_gen; Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor(out, self)); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor(out, self)); return rcpp_result_gen; END_RCPP } @@ -47079,21 +47216,6 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } -// cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double -XPtrTorchTensor cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double(XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps); -RcppExport SEXP _torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double(SEXP outSEXP, SEXP selfSEXP, SEXP weightSEXP, SEXP biasSEXP, SEXP epsSEXP) { -BEGIN_RCPP - Rcpp::RObject rcpp_result_gen; - Rcpp::RNGScope rcpp_rngScope_gen; - Rcpp::traits::input_parameter< XPtrTorchTensor >::type out(outSEXP); - Rcpp::traits::input_parameter< XPtrTorchTensor >::type self(selfSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type weight(weightSEXP); - Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type bias(biasSEXP); - Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); - rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double(out, self, weight, bias, eps)); - return rcpp_result_gen; -END_RCPP -} // cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor XPtrTorchTensor cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(XPtrTorchTensor out, XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchoptional_int64_t mask_type); RcppExport SEXP _torch_cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor(SEXP outSEXP, SEXP srcSEXP, SEXP embed_dimSEXP, SEXP num_headsSEXP, SEXP qkv_weightSEXP, SEXP qkv_biasSEXP, SEXP proj_weightSEXP, SEXP proj_biasSEXP, SEXP use_geluSEXP, SEXP norm_firstSEXP, SEXP epsSEXP, SEXP norm_weight_1SEXP, SEXP norm_bias_1SEXP, SEXP norm_weight_2SEXP, SEXP norm_bias_2SEXP, SEXP ffn_weight_1SEXP, SEXP ffn_bias_1SEXP, SEXP ffn_weight_2SEXP, SEXP ffn_bias_2SEXP, SEXP maskSEXP, SEXP mask_typeSEXP) { @@ -47313,6 +47435,56 @@ BEGIN_RCPP return rcpp_result_gen; END_RCPP } +// cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool +void cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf); +RcppExport SEXP _torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(SEXP outSEXP, SEXP selfSEXP, SEXP gradsSEXP, SEXP exp_avgsSEXP, SEXP exp_avg_sqsSEXP, SEXP max_exp_avg_sqsSEXP, SEXP state_stepsSEXP, SEXP lrSEXP, SEXP beta1SEXP, SEXP beta2SEXP, SEXP weight_decaySEXP, SEXP epsSEXP, SEXP amsgradSEXP, SEXP maximizeSEXP, SEXP grad_scaleSEXP, SEXP found_infSEXP) { +BEGIN_RCPP + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type out(outSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type grads(gradsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avgs(exp_avgsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avg_sqs(exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type max_exp_avg_sqs(max_exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type state_steps(state_stepsSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type lr(lrSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta1(beta1SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta2(beta2SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type weight_decay(weight_decaySEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type amsgrad(amsgradSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type maximize(maximizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_scale(grad_scaleSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type found_inf(found_infSEXP); + cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); + return R_NilValue; +END_RCPP +} +// cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool +Rcpp::List cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf); +RcppExport SEXP _torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(SEXP selfSEXP, SEXP gradsSEXP, SEXP exp_avgsSEXP, SEXP exp_avg_sqsSEXP, SEXP max_exp_avg_sqsSEXP, SEXP state_stepsSEXP, SEXP lrSEXP, SEXP beta1SEXP, SEXP beta2SEXP, SEXP weight_decaySEXP, SEXP epsSEXP, SEXP amsgradSEXP, SEXP maximizeSEXP, SEXP grad_scaleSEXP, SEXP found_infSEXP) { +BEGIN_RCPP + Rcpp::RObject rcpp_result_gen; + Rcpp::RNGScope rcpp_rngScope_gen; + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type self(selfSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type grads(gradsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avgs(exp_avgsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type exp_avg_sqs(exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type max_exp_avg_sqs(max_exp_avg_sqsSEXP); + Rcpp::traits::input_parameter< XPtrTorchTensorList >::type state_steps(state_stepsSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type lr(lrSEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta1(beta1SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type beta2(beta2SEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type weight_decay(weight_decaySEXP); + Rcpp::traits::input_parameter< XPtrTorchdouble >::type eps(epsSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type amsgrad(amsgradSEXP); + Rcpp::traits::input_parameter< XPtrTorchbool >::type maximize(maximizeSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type grad_scale(grad_scaleSEXP); + Rcpp::traits::input_parameter< XPtrTorchOptionalTensor >::type found_inf(found_infSEXP); + rcpp_result_gen = Rcpp::wrap(cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf)); + return rcpp_result_gen; +END_RCPP +} // cpp_torch_generator XPtrTorchGenerator cpp_torch_generator(); RcppExport SEXP _torch_cpp_torch_generator() { @@ -49026,6 +49198,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_addmv__self_Tensor_mat_Tensor_vec_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addmv__self_Tensor_mat_Tensor_vec_Tensor, 5}, {"_torch_cpp_torch_method_addr_self_Tensor_vec1_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addr_self_Tensor_vec1_Tensor_vec2_Tensor, 5}, {"_torch_cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor, 5}, + {"_torch_cpp_torch_method__is_all_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method__is_all_true_self_Tensor, 1}, + {"_torch_cpp_torch_method__is_any_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method__is_any_true_self_Tensor, 1}, {"_torch_cpp_torch_method_all_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_all_self_Tensor_dim_int64_t, 3}, {"_torch_cpp_torch_method_all_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_all_self_Tensor_dim_Dimname, 3}, {"_torch_cpp_torch_method_allclose_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_method_allclose_self_Tensor_other_Tensor, 5}, @@ -49310,7 +49484,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_relu_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_relu_self_Tensor, 1}, {"_torch_cpp_torch_method_relu__self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_relu__self_Tensor, 1}, {"_torch_cpp_torch_method_prelu_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_method_prelu_self_Tensor_weight_Tensor, 2}, - {"_torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor, 3}, {"_torch_cpp_torch_method_hardshrink_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_hardshrink_self_Tensor, 2}, {"_torch_cpp_torch_method_hardshrink_backward_grad_out_Tensor_self_Tensor_lambd_Scalar", (DL_FUNC) &_torch_cpp_torch_method_hardshrink_backward_grad_out_Tensor_self_Tensor_lambd_Scalar, 3}, {"_torch_cpp_torch_method_rsqrt_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_rsqrt_self_Tensor, 1}, @@ -49352,8 +49525,10 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_squeeze_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor, 1}, {"_torch_cpp_torch_method_squeeze_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_method_squeeze_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor_dim_Dimname, 2}, + {"_torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_method_squeeze__self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor, 1}, {"_torch_cpp_torch_method_squeeze__self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor_dim_int64_t, 2}, + {"_torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_squeeze__self_Tensor_dim_Dimname, 2}, {"_torch_cpp_torch_method_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_method_stft_self_Tensor_n_fft_int64_t", (DL_FUNC) &_torch_cpp_torch_method_stft_self_Tensor_n_fft_int64_t, 10}, @@ -49371,9 +49546,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_square__self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_square__self_Tensor, 1}, {"_torch_cpp_torch_method_std_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor, 2}, {"_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_method_prod_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_prod_self_Tensor, 2}, {"_torch_cpp_torch_method_prod_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_prod_self_Tensor_dim_int64_t, 4}, {"_torch_cpp_torch_method_prod_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_prod_self_Tensor_dim_Dimname, 4}, @@ -49404,11 +49577,10 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_unsqueeze__self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_unsqueeze__self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_method_var_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor, 2}, {"_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_method_view_as_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_method_view_as_self_Tensor_other_Tensor, 2}, {"_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor, 3}, + {"_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar", (DL_FUNC) &_torch_cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar, 3}, {"_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType, 3}, {"_torch_cpp_torch_method_norm_self_Tensor_p_Scalar", (DL_FUNC) &_torch_cpp_torch_method_norm_self_Tensor_p_Scalar, 2}, {"_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dim_IntArrayRef_keepdim_bool_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_method_norm_self_Tensor_p_Scalar_dim_IntArrayRef_keepdim_bool_dtype_ScalarType, 5}, @@ -49458,11 +49630,11 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_unbind_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_unbind_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_method_unbind_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_method_unbind_self_Tensor_dim_Dimname, 2}, {"_torch_cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_self_Tensor_sparse_dim_int64_t, 2}, - {"_torch_cpp_torch_method_to_sparse_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_self_Tensor, 1}, - {"_torch_cpp_torch_method_to_sparse_csr_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csr_self_Tensor, 1}, - {"_torch_cpp_torch_method_to_sparse_csc_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csc_self_Tensor, 1}, - {"_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef, 2}, - {"_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef, 2}, + {"_torch_cpp_torch_method_to_sparse_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_self_Tensor, 4}, + {"_torch_cpp_torch_method_to_sparse_csr_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csr_self_Tensor, 2}, + {"_torch_cpp_torch_method_to_sparse_csc_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_csc_self_Tensor, 2}, + {"_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef, 3}, + {"_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef, 3}, {"_torch_cpp_torch_method_to_mkldnn_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_to_mkldnn_self_Tensor, 2}, {"_torch_cpp_torch_method_dequantize_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_dequantize_self_Tensor, 1}, {"_torch_cpp_torch_method_q_scale_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_q_scale_self_Tensor, 1}, @@ -49642,7 +49814,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_addcdiv_self_Tensor_tensor1_Tensor_tensor2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addcdiv_self_Tensor_tensor1_Tensor_tensor2_Tensor, 4}, {"_torch_cpp_torch_method_addcdiv__self_Tensor_tensor1_Tensor_tensor2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_addcdiv__self_Tensor_tensor1_Tensor_tensor2_Tensor, 4}, {"_torch_cpp_torch_method_triangular_solve_self_Tensor_A_Tensor", (DL_FUNC) &_torch_cpp_torch_method_triangular_solve_self_Tensor_A_Tensor, 5}, - {"_torch_cpp_torch_method_symeig_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_symeig_self_Tensor, 3}, {"_torch_cpp_torch_method_svd_self_Tensor", (DL_FUNC) &_torch_cpp_torch_method_svd_self_Tensor, 3}, {"_torch_cpp_torch_method_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t", (DL_FUNC) &_torch_cpp_torch_method_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t, 3}, {"_torch_cpp_torch_method_swapaxes__self_Tensor_axis0_int64_t_axis1_int64_t", (DL_FUNC) &_torch_cpp_torch_method_swapaxes__self_Tensor_axis0_int64_t_axis1_int64_t, 3}, @@ -49744,7 +49915,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_method_outer_self_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_outer_self_Tensor_vec2_Tensor, 2}, {"_torch_cpp_torch_method_ger_self_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_method_ger_self_Tensor_vec2_Tensor, 2}, {"_torch_cpp_torch_method_to_padded_tensor_self_Tensor_padding_double", (DL_FUNC) &_torch_cpp_torch_method_to_padded_tensor_self_Tensor_padding_double, 3}, - {"_torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double, 4}, {"_torch_cpp_torch_namespace__cast_Byte_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__cast_Byte_self_Tensor, 2}, {"_torch_cpp_torch_namespace__cast_Char_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__cast_Char_self_Tensor, 2}, {"_torch_cpp_torch_namespace__cast_Double_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__cast_Double_self_Tensor, 2}, @@ -49833,6 +50003,9 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_addr_out_out_Tensor_self_Tensor_vec1_Tensor_vec2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addr_out_out_Tensor_self_Tensor_vec1_Tensor_vec2_Tensor, 6}, {"_torch_cpp_torch_namespace_affine_grid_generator_theta_Tensor_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_affine_grid_generator_theta_Tensor_size_IntArrayRef_align_corners_bool, 3}, {"_torch_cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_size_IntArrayRef_align_corners_bool, 3}, + {"_torch_cpp_torch_namespace__is_all_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__is_all_true_self_Tensor, 1}, + {"_torch_cpp_torch_namespace__is_any_true_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__is_any_true_self_Tensor, 1}, + {"_torch_cpp_torch_namespace__test_check_tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__test_check_tensor_self_Tensor, 1}, {"_torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_all_self_Tensor_dim_int64_t, 3}, {"_torch_cpp_torch_namespace_all_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_all_out_out_Tensor_self_Tensor_dim_int64_t, 4}, {"_torch_cpp_torch_namespace_all_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_all_self_Tensor_dim_Dimname, 3}, @@ -50322,8 +50495,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_max_pool1d_with_indices_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool1d_with_indices_self_Tensor_kernel_size_IntArrayRef, 6}, {"_torch_cpp_torch_namespace_max_pool1d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool1d_self_Tensor_kernel_size_IntArrayRef, 6}, {"_torch_cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool2d_self_Tensor_kernel_size_IntArrayRef, 6}, - {"_torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef, 6}, - {"_torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, + {"_torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_self_Tensor_kernel_size_IntArrayRef, 6}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef, 8}, {"_torch_cpp_torch_namespace_mkldnn_max_pool3d_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool3d_self_Tensor_kernel_size_IntArrayRef, 6}, @@ -50357,6 +50529,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__mps_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__mps_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 7}, {"_torch_cpp_torch_namespace_mps_convolution_backward_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3", (DL_FUNC) &_torch_cpp_torch_namespace_mps_convolution_backward_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3, 8}, {"_torch_cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 7}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool, 16}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor, 23}, {"_torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double, 8}, {"_torch_cpp_torch_namespace_miopen_batch_norm_backward_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_backward_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double, 8}, {"_torch_cpp_torch_namespace_miopen_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_convolution_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool, 9}, @@ -50369,8 +50543,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_mm_self_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mm_self_Tensor_mat2_Tensor, 2}, {"_torch_cpp_torch_namespace_mm_out_out_Tensor_self_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mm_out_out_Tensor_self_Tensor_mat2_Tensor, 3}, {"_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor, 2}, + {"_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view, 3}, {"_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor, 2}, - {"_torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor, 2}, {"_torch_cpp_torch_namespace_mode_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mode_self_Tensor_dim_int64_t, 3}, {"_torch_cpp_torch_namespace_mode_out_values_Tensor_indices_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mode_out_values_Tensor_indices_Tensor_self_Tensor_dim_int64_t, 5}, {"_torch_cpp_torch_namespace_mode_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_mode_self_Tensor_dim_Dimname, 3}, @@ -50391,6 +50565,10 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_narrow_self_Tensor_dim_int64_t_start_Tensor_length_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_narrow_self_Tensor_dim_int64_t_start_Tensor_length_int64_t, 4}, {"_torch_cpp_torch_namespace_native_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_native_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 8}, {"_torch_cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_native_batch_norm_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 11}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 8}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 11}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double, 6}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double, 9}, {"_torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double, 2}, {"_torch_cpp_torch_namespace_batch_norm_elemt_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_elemt_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double, 6}, {"_torch_cpp_torch_namespace_batch_norm_elemt_out_out_Tensor_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_elemt_out_out_Tensor_input_Tensor_weight_Tensor_bias_Tensor_mean_Tensor_invstd_Tensor_eps_double, 7}, @@ -50478,6 +50656,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_Tensor, 4}, {"_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_repeat_interleave_self_Tensor_repeats_int64_t, 4}, {"_torch_cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef, 2}, + {"_torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef, 2}, {"_torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 3}, {"_torch_cpp_torch_namespace__mkldnn_reshape_self_Tensor_shape_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mkldnn_reshape_self_Tensor_shape_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_round_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_round_self_Tensor, 1}, @@ -50493,7 +50672,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_relu6_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_relu6_self_Tensor, 1}, {"_torch_cpp_torch_namespace_relu6__self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_relu6__self_Tensor, 1}, {"_torch_cpp_torch_namespace_prelu_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_self_Tensor_weight_Tensor, 2}, - {"_torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor, 3}, + {"_torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor, 2}, + {"_torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor, 3}, {"_torch_cpp_torch_namespace_gelu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_gelu_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace_gelu__self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_gelu__self_Tensor, 2}, {"_torch_cpp_torch_namespace_gelu_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_gelu_self_Tensor, 2}, @@ -50571,6 +50751,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_squeeze_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor, 1}, {"_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname, 2}, + {"_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_namespace_sspaddmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sspaddmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 6}, {"_torch_cpp_torch_namespace_stack_tensors_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace_stack_tensors_TensorList, 2}, @@ -50603,18 +50784,12 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_square_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_square_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_std_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor, 2}, {"_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_std_mean_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor, 2}, {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef, 5}, - {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList, 4}, {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList, 5}, - {"_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t, 4}, - {"_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_prod_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prod_self_Tensor, 2}, {"_torch_cpp_torch_namespace_prod_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_prod_self_Tensor_dim_int64_t, 4}, {"_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor_dim_int64_t, 5}, @@ -50675,18 +50850,12 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_vander_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_vander_x_Tensor, 3}, {"_torch_cpp_torch_namespace_var_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor, 2}, {"_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef, 5}, - {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList, 4}, {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList, 5}, - {"_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t, 4}, - {"_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t, 5}, {"_torch_cpp_torch_namespace_var_mean_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor, 2}, {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList, 4}, - {"_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t, 4}, {"_torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_where_out_out_Tensor_condition_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_where_out_out_Tensor_condition_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace_where_condition_Tensor_self_Scalar_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_where_condition_Tensor_self_Scalar_other_Tensor, 3}, @@ -50739,7 +50908,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_norm_out_out_Tensor_self_Tensor_p_Scalar_dim_DimnameList_keepdim_bool", (DL_FUNC) &_torch_cpp_torch_namespace_norm_out_out_Tensor_self_Tensor_p_Scalar_dim_DimnameList_keepdim_bool, 5}, {"_torch_cpp_torch_namespace_frexp_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_frexp_self_Tensor, 1}, {"_torch_cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_frexp_out_mantissa_Tensor_exponent_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_frobenius_norm_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_frobenius_norm_self_Tensor, 1}, {"_torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef, 3}, {"_torch_cpp_torch_namespace_frobenius_norm_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_frobenius_norm_out_out_Tensor_self_Tensor_dim_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_nuclear_norm_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_nuclear_norm_self_Tensor, 2}, @@ -50764,6 +50932,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__sparse_addmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_addmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_namespace_sparse_sampled_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sparse_sampled_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 6}, {"_torch_cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, + {"_torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view, 3}, + {"_torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2, 6}, {"_torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 6}, {"_torch_cpp_torch_namespace_addmm_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addmm_self_Tensor_mat1_Tensor_mat2_Tensor, 5}, {"_torch_cpp_torch_namespace__addmm_activation_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__addmm_activation_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor, 7}, @@ -50803,7 +50973,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_copy_sparse_to_sparse__self_Tensor_src_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_copy_sparse_to_sparse__self_Tensor_src_Tensor, 3}, {"_torch_cpp_torch_namespace_unbind_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_self_Tensor_dim_int64_t, 2}, {"_torch_cpp_torch_namespace_unbind_self_Tensor_dim_Dimname", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_self_Tensor_dim_Dimname, 2}, - {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor, 5}, + {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor, 6}, {"_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_self_Tensor, 5}, {"_torch_cpp_torch_namespace_to_mkldnn_backward_grad_Tensor_input_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_mkldnn_backward_grad_Tensor_input_Tensor, 2}, {"_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_self_Tensor_dtype_ScalarType_reduce_range_bool", (DL_FUNC) &_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_self_Tensor_dtype_ScalarType_reduce_range_bool, 3}, @@ -50851,7 +51021,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_promote_types_type1_ScalarType_type2_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_promote_types_type1_ScalarType_type2_ScalarType, 2}, {"_torch_cpp_torch_namespace__local_scalar_dense_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__local_scalar_dense_self_Tensor, 1}, {"_torch_cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 9}, - {"_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 14}, + {"_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 15}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor, 5}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool, 6}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool, 6}, @@ -50950,7 +51120,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_addbmm_self_Tensor_batch1_Tensor_batch2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_addbmm_self_Tensor_batch1_Tensor_batch2_Tensor, 5}, {"_torch_cpp_torch_namespace_diag_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diag_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace_diag_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diag_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t, 3}, {"_torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace_cross_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cross_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_triu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_triu_out_out_Tensor_self_Tensor, 3}, @@ -51038,9 +51207,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_linalg_solve_triangular_out_out_Tensor_self_Tensor_B_Tensor_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace_linalg_solve_triangular_out_out_Tensor_self_Tensor_B_Tensor_upper_bool, 6}, {"_torch_cpp_torch_namespace_linalg_solve_triangular_self_Tensor_B_Tensor_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace_linalg_solve_triangular_self_Tensor_B_Tensor_upper_bool, 5}, {"_torch_cpp_torch_namespace_linalg_vander_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_linalg_vander_x_Tensor, 2}, - {"_torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor, 5}, - {"_torch_cpp_torch_namespace_symeig_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_symeig_self_Tensor, 3}, - {"_torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool, 3}, {"_torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor, 6}, {"_torch_cpp_torch_namespace_svd_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_svd_self_Tensor, 3}, {"_torch_cpp_torch_namespace_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_swapaxes_self_Tensor_axis0_int64_t_axis1_int64_t, 3}, @@ -51129,6 +51295,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_maximum_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_maximum_out_out_Tensor_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_max_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_max_self_Tensor_other_Tensor, 2}, {"_torch_cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_max_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_minimum_self_Tensor_other_Tensor, 2}, {"_torch_cpp_torch_namespace_minimum_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_minimum_out_out_Tensor_self_Tensor_other_Tensor, 3}, {"_torch_cpp_torch_namespace_min_out_out_Tensor_other_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_min_out_out_Tensor_other_Tensor_self_Tensor, 3}, @@ -51192,6 +51359,14 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalar_Scalar, 2}, {"_torch_cpp_torch_namespace__foreach_div_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_self_TensorList_scalar_Scalar, 2}, {"_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar, 2}, {"_torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_add__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add__self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_sub_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_self_TensorList_other_TensorList, 3}, @@ -51200,6 +51375,14 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_mul__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul__self_TensorList_other_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_div_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_self_TensorList_other_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar, 2}, @@ -51208,6 +51391,14 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar, 2}, + {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar, 2}, {"_torch_cpp_torch_namespace__foreach_exp_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_exp_self_TensorList, 1}, {"_torch_cpp_torch_namespace__foreach_zero__self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_zero__self_TensorList, 1}, {"_torch_cpp_torch_namespace__foreach_exp__self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_exp__self_TensorList, 1}, @@ -51268,21 +51459,24 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, + {"_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, + {"_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, + {"_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 4}, - {"_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList, 2}, - {"_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList, 2}, - {"_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList, 2}, - {"_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 4}, {"_torch_cpp_torch_namespace__foreach_norm_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_norm_self_TensorList, 2}, + {"_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar, 3}, {"_torch_cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor, 4}, {"_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Tensor_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Tensor_boundaries_Tensor, 5}, {"_torch_cpp_torch_namespace_bucketize_self_Scalar_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_self_Scalar_boundaries_Tensor, 4}, {"_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Tensor, 6}, - {"_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor, 1}, {"_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor, 7}, {"_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Scalar, 6}, {"_torch_cpp_torch_namespace__convert_indices_from_coo_to_csr_self_Tensor_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__convert_indices_from_coo_to_csr_self_Tensor_size_int64_t, 3}, @@ -51453,29 +51647,17 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__pad_enum_self_Tensor_pad_IntArrayRef_mode_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__pad_enum_self_Tensor_pad_IntArrayRef_mode_int64_t, 4}, {"_torch_cpp_torch_namespace_pad_self_Tensor_pad_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_pad_self_Tensor_pad_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, - {"_torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, {"_torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, - {"_torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, {"_torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 3}, - {"_torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, {"_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool, 5}, {"_torch_cpp_torch_namespace_upsample_linear1d_self_Tensor_output_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_self_Tensor_output_size_IntArrayRef_align_corners_bool, 4}, {"_torch_cpp_torch_namespace_upsample_linear1d_backward_out_grad_input_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_backward_out_grad_input_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool, 6}, @@ -51828,6 +52010,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_split_with_sizes_copy_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_split_with_sizes_copy_self_Tensor_split_sizes_IntArrayRef, 3}, {"_torch_cpp_torch_namespace_squeeze_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t, 2}, + {"_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_t_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_t_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_transpose_copy_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_transpose_copy_self_Tensor_dim0_int64_t_dim1_int64_t, 3}, {"_torch_cpp_torch_namespace_unsqueeze_copy_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsqueeze_copy_self_Tensor_dim_int64_t, 2}, @@ -51840,54 +52023,33 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_ccol_indices_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_ccol_indices_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_row_indices_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_row_indices_copy_self_Tensor, 1}, {"_torch_cpp_torch_namespace_unbind_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_copy_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t, 4}, + {"_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef, 2}, {"_torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_self_Tensor_dtype_ScalarType, 2}, {"_torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unfold_copy_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t, 4}, {"_torch_cpp_torch_namespace_alias_copy_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_alias_copy_self_Tensor, 1}, - {"_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t, 3}, - {"_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t, 4}, - {"_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 5}, - {"_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor, 5}, - {"_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t, 4}, - {"_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor, 6}, - {"_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t, 4}, - {"_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef, 4}, - {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, - {"_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t, 4}, - {"_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, - {"_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType, 3}, - {"_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t, 5}, - {"_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor, 2}, {"_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor, 20}, {"_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 13}, + {"_torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor, 6}, {"_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor, 7}, - {"_torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor, 7}, + {"_torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor, 6}, {"_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor, 7}, + {"_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor, 6}, + {"_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t, 14}, + {"_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool, 5}, + {"_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor, 8}, + {"_torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor, 4}, + {"_torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool", (DL_FUNC) &_torch_cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool, 10}, + {"_torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t, 14}, + {"_torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t, 8}, + {"_torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor, 8}, {"_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor, 4}, {"_torch_cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 10}, {"_torch_cpp_torch_namespace_special_airy_ai_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_airy_ai_x_Tensor, 1}, {"_torch_cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor, 2}, - {"_torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool", (DL_FUNC) &_torch_cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool, 9}, {"_torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor, 21}, {"_torch_cpp_torch_namespace__native_decoder_only_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__native_decoder_only_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 14}, {"_torch_cpp_torch_namespace_special_bessel_j0_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_bessel_j0_self_Tensor, 1}, @@ -51986,6 +52148,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_special_spherical_bessel_j0_out_out_Tensor_x_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_special_spherical_bessel_j0_out_out_Tensor_x_Tensor, 2}, {"_torch_cpp_torch_namespace__foobar_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foobar_self_Tensor, 4}, {"_torch_cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, + {"_torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, {"_torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace__cudnn_ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_blank_int64_t_deterministic_bool_zero_infinity_bool", (DL_FUNC) &_torch_cpp_torch_namespace__cudnn_ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_blank_int64_t_deterministic_bool_zero_infinity_bool, 9}, {"_torch_cpp_torch_namespace__cudnn_rnn_flatten_weight_out_out_Tensor_weight_arr_TensorList_weight_stride0_int64_t_input_size_int64_t_mode_int64_t_hidden_size_int64_t_proj_size_int64_t_num_layers_int64_t_batch_first_bool_bidirectional_bool", (DL_FUNC) &_torch_cpp_torch_namespace__cudnn_rnn_flatten_weight_out_out_Tensor_weight_arr_TensorList_weight_stride0_int64_t_input_size_int64_t_mode_int64_t_hidden_size_int64_t_proj_size_int64_t_num_layers_int64_t_batch_first_bool_bidirectional_bool, 10}, @@ -52036,6 +52199,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_cudnn_grid_sampler_out_out_Tensor_self_Tensor_grid_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cudnn_grid_sampler_out_out_Tensor_self_Tensor_grid_Tensor, 3}, {"_torch_cpp_torch_namespace_cudnn_grid_sampler_backward_out_out0_Tensor_out1_Tensor_self_Tensor_grid_Tensor_grad_output_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_cudnn_grid_sampler_backward_out_out0_Tensor_out1_Tensor_self_Tensor_grid_Tensor_grad_output_Tensor, 5}, {"_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef, 8}, + {"_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor, 8}, {"_torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t, 10}, {"_torch_cpp_torch_namespace_diag_embed_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diag_embed_out_out_Tensor_self_Tensor, 5}, {"_torch_cpp_torch_namespace_diagonal_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_offset_int64_t_dim1_int64_t_dim2_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_diagonal_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_offset_int64_t_dim1_int64_t_dim2_int64_t, 6}, @@ -52099,8 +52263,7 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_matmul_backward_out_out0_Tensor_out1_Tensor_grad_Tensor_self_Tensor_other_Tensor_mask_stdarraybool2", (DL_FUNC) &_torch_cpp_torch_namespace_matmul_backward_out_out0_Tensor_out1_Tensor_grad_Tensor_self_Tensor_other_Tensor_mask_stdarraybool2, 6}, {"_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__aminmax_out_out0_Tensor_out1_Tensor_self_Tensor_dim_int64_t, 5}, - {"_torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, - {"_torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 8}, + {"_torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef, 8}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, {"_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_output_Tensor_input_Tensor_kernel_size_IntArrayRef, 9}, {"_torch_cpp_torch_namespace_mkldnn_max_pool3d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_max_pool3d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef, 7}, @@ -52112,6 +52275,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__mps_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__mps_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 8}, {"_torch_cpp_torch_namespace_mps_convolution_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3", (DL_FUNC) &_torch_cpp_torch_namespace_mps_convolution_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_grad_output_Tensor_weight_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_output_mask_stdarraybool3, 11}, {"_torch_cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t, 8}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool, 20}, + {"_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor, 30}, {"_torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double, 11}, {"_torch_cpp_torch_namespace_miopen_batch_norm_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_batch_norm_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_grad_output_Tensor_weight_Tensor_running_mean_Tensor_running_var_Tensor_save_mean_Tensor_save_var_Tensor_epsilon_double, 11}, {"_torch_cpp_torch_namespace_miopen_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_convolution_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_padding_IntArrayRef_stride_IntArrayRef_dilation_IntArrayRef_groups_int64_t_benchmark_bool_deterministic_bool, 10}, @@ -52120,8 +52285,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_miopen_rnn_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_weight_TensorList_weight_stride0_int64_t_hx_Tensor_cx_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_rnn_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_weight_TensorList_weight_stride0_int64_t_hx_Tensor_cx_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor, 19}, {"_torch_cpp_torch_namespace_miopen_rnn_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_TensorList_input_Tensor_weight_TensorList_weight_stride0_int64_t_weight_buf_Tensor_hx_Tensor_cx_Tensor_output_Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor_reserve_Tensor_output_mask_stdarraybool4", (DL_FUNC) &_torch_cpp_torch_namespace_miopen_rnn_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_TensorList_input_Tensor_weight_TensorList_weight_stride0_int64_t_weight_buf_Tensor_hx_Tensor_cx_Tensor_output_Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_batch_first_bool_dropout_double_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_dropout_state_Tensor_reserve_Tensor_output_mask_stdarraybool4, 25}, {"_torch_cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_sparse_matmul_out_out_Tensor_self_Tensor_other_Tensor, 3}, - {"_torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor, 3}, {"_torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar, 3}, + {"_torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double, 8}, {"_torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_stats_out_out0_Tensor_out1_Tensor_input_Tensor_eps_double, 4}, {"_torch_cpp_torch_namespace_batch_norm_gather_stats_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_count_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_gather_stats_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_count_int64_t, 10}, {"_torch_cpp_torch_namespace_batch_norm_gather_stats_with_counts_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_counts_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_batch_norm_gather_stats_with_counts_out_out0_Tensor_out1_Tensor_input_Tensor_mean_Tensor_invstd_Tensor_running_mean_Tensor_running_var_Tensor_momentum_double_eps_double_counts_Tensor, 10}, @@ -52154,8 +52319,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_repeat_interleave_out_out_Tensor_repeats_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_repeat_interleave_out_out_Tensor_repeats_Tensor, 3}, {"_torch_cpp_torch_namespace__mkldnn_reshape_out_out_Tensor_self_Tensor_shape_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__mkldnn_reshape_out_out_Tensor_self_Tensor_shape_IntArrayRef, 3}, {"_torch_cpp_torch_namespace_relu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_relu_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor, 3}, - {"_torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor, 5}, {"_torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t, 5}, {"_torch_cpp_torch_namespace_celu_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_celu_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace_slice_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_start_int64_t_end_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_slice_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_start_int64_t_end_int64_t_step_int64_t, 7}, @@ -52166,7 +52329,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_unsafe_split_out_out_TensorList_self_Tensor_split_size_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsafe_split_out_out_TensorList_self_Tensor_split_size_int64_t, 4}, {"_torch_cpp_torch_namespace_unsafe_split_with_sizes_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_unsafe_split_with_sizes_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_sum_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_sum_out_out_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 6}, {"_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_prod_out_out_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace__mkldnn_transpose_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__mkldnn_transpose_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t, 4}, {"_torch_cpp_torch_namespace_flip_out_out_Tensor_self_Tensor_dims_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_flip_out_out_Tensor_self_Tensor_dims_IntArrayRef, 3}, @@ -52186,7 +52348,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_unique_dim_consecutive_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unique_dim_consecutive_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor_dim_int64_t, 7}, {"_torch_cpp_torch_namespace__unique2_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__unique2_out_out0_Tensor_out1_Tensor_out2_Tensor_self_Tensor, 7}, {"_torch_cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t, 6}, {"_torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor, 5}, {"_torch_cpp_torch_namespace__weight_norm_interface_backward_out_out0_Tensor_out1_Tensor_grad_w_Tensor_saved_v_Tensor_saved_g_Tensor_saved_norms_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__weight_norm_interface_backward_out_out0_Tensor_out1_Tensor_grad_w_Tensor_saved_v_Tensor_saved_g_Tensor_saved_norms_Tensor_dim_int64_t, 7}, {"_torch_cpp_torch_namespace_zeros_out_out_Tensor_size_IntArrayRef_names_DimnameList", (DL_FUNC) &_torch_cpp_torch_namespace_zeros_out_out_Tensor_size_IntArrayRef_names_DimnameList, 3}, @@ -52237,13 +52398,13 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_copy_sparse_to_sparse_out_out_Tensor_self_Tensor_src_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_copy_sparse_to_sparse_out_out_Tensor_self_Tensor_src_Tensor, 4}, {"_torch_cpp_torch_namespace_copy_sparse_to_sparse_self_Tensor_src_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_copy_sparse_to_sparse_self_Tensor_src_Tensor, 3}, {"_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor_sparse_dim_int64_t, 3}, - {"_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 3}, - {"_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor, 5}, + {"_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor, 3}, + {"_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 4}, + {"_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef, 4}, {"_torch_cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_to_mkldnn_out_out_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor, 6}, + {"_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor, 7}, {"_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_mkldnn_reorder_conv3d_weight_out_out_Tensor_self_Tensor, 6}, {"_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_out_out_Tensor_self_Tensor_dtype_ScalarType_reduce_range_bool", (DL_FUNC) &_torch_cpp_torch_namespace_quantize_per_tensor_dynamic_out_out_Tensor_self_Tensor_dtype_ScalarType_reduce_range_bool, 4}, {"_torch_cpp_torch_namespace_quantize_per_tensor_out_out_Tensor_self_Tensor_scale_double_zero_point_int64_t_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_quantize_per_tensor_out_out_Tensor_self_Tensor_scale_double_zero_point_int64_t_dtype_ScalarType, 5}, @@ -52265,8 +52426,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_out_out0_Tensor_out1_Tensor_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_out_out0_Tensor_out1_Tensor_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t, 15}, {"_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_functional_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fused_moving_avg_obs_fq_helper_functional_self_Tensor_observer_on_Tensor_fake_quant_on_Tensor_running_min_Tensor_running_max_Tensor_scale_Tensor_zero_point_Tensor_averaging_const_double_quant_min_int64_t_quant_max_int64_t_ch_axis_int64_t, 13}, {"_torch_cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__to_copy_out_out_Tensor_self_Tensor, 4}, - {"_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 14}, - {"_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 17}, + {"_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 15}, + {"_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool", (DL_FUNC) &_torch_cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool, 18}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_out_out0_Tensor_out1_Tensor_out2_Tensor_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_out_out0_Tensor_out1_Tensor_out2_Tensor_input_gates_Tensor_hidden_gates_Tensor_cx_Tensor, 8}, {"_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_lstm_cell_backward_impl_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_hy_Tensor_grad_cy_Tensor_cx_Tensor_cy_Tensor_workspace_Tensor_has_bias_bool, 9}, {"_torch_cpp_torch_namespace__thnn_fused_gru_cell_out_out0_Tensor_out1_Tensor_input_gates_Tensor_hidden_gates_Tensor_hx_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__thnn_fused_gru_cell_out_out0_Tensor_out1_Tensor_input_gates_Tensor_hidden_gates_Tensor_hx_Tensor, 7}, @@ -52318,7 +52479,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_tril_indices_out_out_Tensor_row_int64_t_col_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_tril_indices_out_out_Tensor_row_int64_t_col_int64_t, 4}, {"_torch_cpp_torch_namespace_triu_indices_out_out_Tensor_row_int64_t_col_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_triu_indices_out_out_Tensor_row_int64_t_col_int64_t, 4}, {"_torch_cpp_torch_namespace_trace_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_trace_out_out_Tensor_self_Tensor, 2}, - {"_torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool, 5}, {"_torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool", (DL_FUNC) &_torch_cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool, 4}, {"_torch_cpp_torch_namespace_dist_out_out_Tensor_self_Tensor_other_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_dist_out_out_Tensor_self_Tensor_other_Tensor, 4}, {"_torch_cpp_torch_namespace__histogramdd_bin_edges_out_out_TensorList_self_Tensor_bins_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__histogramdd_bin_edges_out_out_TensorList_self_Tensor_bins_IntArrayRef, 6}, @@ -52336,14 +52496,26 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, {"_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, {"_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, + {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar, 3}, {"_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_other_TensorList, 4}, {"_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList, 3}, {"_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_sub_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, + {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar, 3}, {"_torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_zero_out_out_TensorList_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_zero_out_out_TensorList_self_TensorList, 2}, {"_torch_cpp_torch_namespace__foreach_zero_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_zero_self_TensorList, 1}, @@ -52377,12 +52549,13 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList, 5}, {"_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList, 5}, {"_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 5}, + {"_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 5}, {"_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar, 5}, - {"_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList, 3}, - {"_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor, 5}, {"_torch_cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList, 3}, + {"_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList, 4}, + {"_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar, 4}, {"_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor, 5}, - {"_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar", (DL_FUNC) &_torch_cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Scalar, 7}, {"_torch_cpp_torch_namespace_glu_jvp_out_out_Tensor_glu_Tensor_x_Tensor_dx_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_glu_jvp_out_out_Tensor_glu_Tensor_x_Tensor_dx_Tensor_dim_int64_t, 5}, {"_torch_cpp_torch_namespace_glu_backward_jvp_out_out_Tensor_grad_x_Tensor_grad_glu_Tensor_x_Tensor_dgrad_glu_Tensor_dx_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_glu_backward_jvp_out_out_Tensor_grad_x_Tensor_grad_glu_Tensor_x_Tensor_dgrad_glu_Tensor_dx_Tensor_dim_int64_t, 7}, @@ -52393,30 +52566,6 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__adaptive_avg_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__adaptive_avg_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor, 3}, {"_torch_cpp_torch_namespace__adaptive_avg_pool3d_out_out_Tensor_self_Tensor_output_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__adaptive_avg_pool3d_out_out_Tensor_self_Tensor_output_size_IntArrayRef, 3}, {"_torch_cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__adaptive_avg_pool3d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor, 3}, - {"_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble, 6}, - {"_torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble, 4}, - {"_torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, - {"_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble", (DL_FUNC) &_torch_cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble, 5}, {"_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3", (DL_FUNC) &_torch_cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3, 10}, {"_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef, 8}, {"_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef, 8}, @@ -52432,10 +52581,40 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view, 9}, {"_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view", (DL_FUNC) &_torch_cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view, 9}, {"_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList", (DL_FUNC) &_torch_cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList, 6}, + {"_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t, 3}, + {"_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t, 4}, + {"_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 5}, + {"_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor, 5}, + {"_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 4}, + {"_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef, 4}, + {"_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t, 4}, + {"_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor, 6}, + {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, + {"_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t, 4}, + {"_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t, 3}, + {"_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_ccol_indices_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_row_indices_copy_out_out_Tensor_self_Tensor, 2}, + {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef, 3}, + {"_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType", (DL_FUNC) &_torch_cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType, 3}, + {"_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t", (DL_FUNC) &_torch_cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t, 5}, + {"_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor, 2}, {"_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double", (DL_FUNC) &_torch_cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double, 4}, - {"_torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double", (DL_FUNC) &_torch_cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double, 5}, {"_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__transformer_encoder_layer_fwd_out_out_Tensor_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor, 21}, {"_torch_cpp_torch_namespace__native_multi_head_attention_out_out0_Tensor_out1_Tensor_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__native_multi_head_attention_out_out0_Tensor_out1_Tensor_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor, 15}, {"_torch_cpp_torch_namespace__triton_scaled_dot_attention_out_out_Tensor_q_Tensor_k_Tensor_v_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__triton_scaled_dot_attention_out_out_Tensor_q_Tensor_k_Tensor_v_Tensor, 5}, @@ -52445,6 +52624,8 @@ static const R_CallMethodDef CallEntries[] = { {"_torch_cpp_torch_namespace__foobar_out_out_Tensor_self_Tensor", (DL_FUNC) &_torch_cpp_torch_namespace__foobar_out_out_Tensor_self_Tensor, 5}, {"_torch_cpp_torch_namespace__fused_adam_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adam_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 16}, {"_torch_cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adam_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, + {"_torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 16}, + {"_torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool", (DL_FUNC) &_torch_cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool, 15}, {"_torch_cpp_torch_generator", (DL_FUNC) &_torch_cpp_torch_generator, 0}, {"_torch_cpp_generator_current_seed", (DL_FUNC) &_torch_cpp_generator_current_seed, 1}, {"_torch_cpp_generator_set_current_seed", (DL_FUNC) &_torch_cpp_generator_set_current_seed, 2}, diff --git a/src/gen-namespace.cpp b/src/gen-namespace.cpp index c7f056132a..10af3c7375 100644 --- a/src/gen-namespace.cpp +++ b/src/gen-namespace.cpp @@ -257,6 +257,18 @@ XPtrTorchTensor cpp_torch_method_addr__self_Tensor_vec1_Tensor_vec2_Tensor (XPtr return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method__is_all_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern_Tensor__is_all_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method__is_any_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern_Tensor__is_any_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_all_self_Tensor_dim_int64_t (XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim) { auto r_out = lantern_Tensor_all_tensor_intt_bool(self.get(), dim.get(), keepdim.get()); @@ -1978,13 +1990,6 @@ XPtrTorchTensor cpp_torch_method_prelu_self_Tensor_weight_Tensor (XPtrTorchTenso return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_method_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_Tensor_prelu_backward_tensor_tensor_tensor(grad_output.get(), self.get(), weight.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_hardshrink_self_Tensor (XPtrTorchTensor self, XPtrTorchScalar lambd) { auto r_out = lantern_Tensor_hardshrink_tensor_scalar(self.get(), lambd.get()); @@ -2231,6 +2236,12 @@ XPtrTorchTensor cpp_torch_method_squeeze_self_Tensor_dim_Dimname (XPtrTorchTenso return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method_squeeze_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_Tensor_squeeze_tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor (XPtrTorchTensor self) { auto r_out = lantern_Tensor_squeeze__tensor(self.get()); @@ -2243,6 +2254,12 @@ XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_int64_t (XPtrTorchTens return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_Tensor_squeeze__tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_squeeze__self_Tensor_dim_Dimname (XPtrTorchTensor self, XPtrTorchDimname dim) { auto r_out = lantern_Tensor_squeeze__tensor_dimname(self.get(), dim.get()); @@ -2345,24 +2362,12 @@ XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_IntArrayRef (XPtrTorchTenso return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_std_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_Tensor_std_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_std_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_std_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_prod_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype) { auto r_out = lantern_Tensor_prod_tensor_scalartype(self.get(), dtype.get()); @@ -2543,24 +2548,12 @@ XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_IntArrayRef (XPtrTorchTenso return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_var_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_Tensor_var_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_var_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_Tensor_var_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_view_as_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { auto r_out = lantern_Tensor_view_as_tensor_tensor(self.get(), other.get()); @@ -2573,6 +2566,12 @@ XPtrTorchTensor cpp_torch_method_where_condition_Tensor_self_Tensor_other_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_method_where_condition_Tensor_self_Tensor_other_Scalar (XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchScalar other) { + auto r_out = lantern_Tensor_where_tensor_tensor_scalar(condition.get(), self.get(), other.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_method_norm_self_Tensor_p_Scalar_dtype_ScalarType (XPtrTorchTensor self, XPtrTorchoptional_scalar p, XPtrTorchDtype dtype) { auto r_out = lantern_Tensor_norm_tensor_scalar_scalartype(self.get(), p.get(), dtype.get()); @@ -2869,32 +2868,32 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_Tensor_to_sparse_tensor(self.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_self_Tensor (XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(self.get(), layout.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_Tensor_to_sparse_csr_tensor(self.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_csr_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_csr_tensor_intt(self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_Tensor_to_sparse_csc_tensor(self.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_csc_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_csc_tensor_intt(self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_Tensor_to_sparse_bsr_tensor_intarrayref(self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_bsr_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_Tensor_to_sparse_bsc_tensor_intarrayref(self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_method_to_sparse_bsc_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } @@ -3973,13 +3972,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_method_symeig_self_Tensor (XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern_Tensor_symeig_tensor_bool_bool(self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_method_svd_self_Tensor (XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv) { auto r_out = lantern_Tensor_svd_tensor_bool_bool(self.get(), some.get(), compute_uv.get()); @@ -4596,12 +4588,6 @@ XPtrTorchTensor cpp_torch_method_to_padded_tensor_self_Tensor_padding_double (XP return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_method__nested_tensor_layer_norm_self_Tensor_weight_Tensor_bias_Tensor_eps_double (XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps) { - auto r_out = lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(self.get(), weight.get(), bias.get(), eps.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__cast_Byte_self_Tensor (XPtrTorchTensor self, XPtrTorchbool non_blocking) { auto r_out = lantern__cast_byte_tensor_bool(self.get(), non_blocking.get()); @@ -5137,6 +5123,24 @@ XPtrTorchTensor cpp_torch_namespace_affine_grid_generator_backward_grad_Tensor_s return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__is_all_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern__is_all_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__is_any_true_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern__is_any_true_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__test_check_tensor_self_Tensor (XPtrTorchTensor self) { + auto r_out = lantern__test_check_tensor_tensor(self.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_all_self_Tensor_dim_int64_t (XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchbool keepdim) { auto r_out = lantern_all_tensor_intt_bool(self.get(), dim.get(), keepdim.get()); @@ -8117,14 +8121,8 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { + auto r_out = lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); return XPtrTorchTensor(r_out); } @@ -8339,6 +8337,20 @@ XPtrTorchTensor cpp_torch_namespace_mkldnn_convolution_self_Tensor_weight_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool (XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train) { + auto r_out = lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(input.get(), weight0.get(), weight1.get(), weight2.get(), weight3.get(), hx_.get(), cx_.get(), reverse.get(), batch_sizes.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), bidirectional.get(), batch_first.get(), train.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor (XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace) { + auto r_out = lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(input.get(), weight1.get(), weight2.get(), weight3.get(), weight4.get(), hx_.get(), cx_tmp.get(), output.get(), hy_.get(), cy_.get(), grad_output.get(), grad_hy.get(), grad_cy.get(), reverse.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), train.get(), bidirectional.get(), batch_sizes.get(), batch_first.get(), workspace.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 6))); +} + // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_miopen_batch_norm_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double (XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon) { auto r_out = lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), exponential_average_factor.get(), epsilon.get()); @@ -8416,14 +8428,14 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { - auto r_out = lantern__sparse_sparse_matmul_tensor_tensor(self.get(), other.get()); +XPtrTorchTensor cpp_torch_namespace__sparse_mm_sparse_Tensor_dense_Tensor_reduce_c10string_view (XPtrTorchTensor sparse, XPtrTorchTensor dense, XPtrTorchstring_view reduce) { + auto r_out = lantern__sparse_mm_tensor_tensor_cstringview(sparse.get(), dense.get(), reduce.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_t_Tensor_mask_indices_Tensor (XPtrTorchTensor t, XPtrTorchTensor mask_indices) { - auto r_out = lantern__sparse_mask_helper_tensor_tensor(t.get(), mask_indices.get()); +XPtrTorchTensor cpp_torch_namespace__sparse_sparse_matmul_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { + auto r_out = lantern__sparse_sparse_matmul_tensor_tensor(self.get(), other.get()); return XPtrTorchTensor(r_out); } @@ -8553,6 +8565,34 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out.get(), save_mean.get(), save_invstd.get(), input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_out_out_Tensor_save_mean_Tensor_save_invstd_Tensor_input_Tensor_weight_Tensor_bias_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor out, XPtrTorchTensor save_mean, XPtrTorchTensor save_invstd, XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out.get(), save_mean.get(), save_invstd.get(), input.get(), weight.get(), bias.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_batch_norm_stats_input_Tensor_eps_double (XPtrTorchTensor input, XPtrTorchdouble eps) { auto r_out = lantern_batch_norm_stats_tensor_double(input.get(), eps.get()); @@ -9081,6 +9121,12 @@ XPtrTorchTensor cpp_torch_namespace_reshape_self_Tensor_shape_IntArrayRef (XPtrT return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace__reshape_copy_self_Tensor_size_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef size) { + auto r_out = lantern__reshape_copy_tensor_intarrayref(self.get(), size.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__reshape_alias_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride) { auto r_out = lantern__reshape_alias_tensor_intarrayref_intarrayref(self.get(), size.get(), stride.get()); @@ -9172,8 +9218,14 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_prelu_backward_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_prelu_backward_tensor_tensor_tensor(grad_output.get(), self.get(), weight.get()); +XPtrTorchTensor cpp_torch_namespace__prelu_kernel_self_Tensor_weight_Tensor (XPtrTorchTensor self, XPtrTorchTensor weight) { + auto r_out = lantern__prelu_kernel_tensor_tensor(self.get(), weight.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__prelu_kernel_backward_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { + auto r_out = lantern__prelu_kernel_backward_tensor_tensor_tensor(grad_output.get(), self.get(), weight.get()); auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } @@ -9640,6 +9692,12 @@ XPtrTorchTensor cpp_torch_namespace_squeeze_self_Tensor_dim_Dimname (XPtrTorchTe return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_squeeze_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_squeeze_tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_sspaddmm_self_Tensor_mat1_Tensor_mat2_Tensor (XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha) { auto r_out = lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar(self.get(), mat1.get(), mat2.get(), beta.get(), alpha.get()); @@ -9832,12 +9890,6 @@ XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef (XPtrTorchTe return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_std_mean_self_Tensor (XPtrTorchTensor self, XPtrTorchbool unbiased) { auto r_out = lantern_std_mean_tensor_bool(self.get(), unbiased.get()); @@ -9852,13 +9904,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_mean_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_std_mean_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -9866,25 +9911,12 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_std_mean_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_mean_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_std_out_tensor_tensor_intarrayref_bool_bool(out.get(), self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_out_tensor_tensor_intarrayref_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_std_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -9897,18 +9929,6 @@ XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameLi return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_std_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_out_tensor_tensor_dimnamelist_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_prod_self_Tensor (XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype) { auto r_out = lantern_prod_tensor_scalartype(self.get(), dtype.get()); @@ -10275,24 +10295,12 @@ XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef (XPtrTorchTe return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_var_out_tensor_tensor_intarrayref_bool_bool(out.get(), self.get(), dim.get(), unbiased.get(), keepdim.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_out_tensor_tensor_intarrayref_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_var_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -10305,18 +10313,6 @@ XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameLi return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_var_out_out_Tensor_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_out_tensor_tensor_dimnamelist_intt_bool(out.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_var_mean_self_Tensor (XPtrTorchTensor self, XPtrTorchbool unbiased) { auto r_out = lantern_var_mean_tensor_bool(self.get(), unbiased.get()); @@ -10331,13 +10327,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_mean_tensor_intarrayref_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchbool unbiased, XPtrTorchbool keepdim) { auto r_out = lantern_var_mean_tensor_dimnamelist_bool_bool(self.get(), dim.get(), unbiased.get(), keepdim.get()); @@ -10345,13 +10334,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_var_mean_self_Tensor_dim_DimnameList_correction_int64_t (XPtrTorchTensor self, XPtrTorchDimnameList dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_mean_tensor_dimnamelist_intt_bool(self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_where_condition_Tensor_self_Tensor_other_Tensor (XPtrTorchTensor condition, XPtrTorchTensor self, XPtrTorchTensor other) { auto r_out = lantern_where_tensor_tensor_tensor(condition.get(), self.get(), other.get()); @@ -10669,12 +10651,6 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern_frobenius_norm_tensor(self.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_frobenius_norm_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim, XPtrTorchbool keepdim) { auto r_out = lantern_frobenius_norm_tensor_intarrayref_bool(self.get(), dim.get(), keepdim.get()); @@ -10819,6 +10795,20 @@ XPtrTorchTensor cpp_torch_namespace_sparse_sampled_addmm_self_Tensor_mat1_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_self_Tensor_other_Tensor_reduce_c10string_view (XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchstring_view reduce) { + auto r_out = lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(self.get(), other.get(), reduce.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__sparse_mm_reduce_impl_backward_self_Tensor_grad_out_Tensor_weight_Tensor_reduce_c10string_view_arg_out_Tensor_output_mask_stdarraybool2 (XPtrTorchTensor self, XPtrTorchTensor grad_out, XPtrTorchTensor weight, XPtrTorchstring_view reduce, XPtrTorchTensor arg_out, std::vector output_mask) { + auto r_out = lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(self.get(), grad_out.get(), weight.get(), reduce.get(), arg_out.get(), reinterpret_cast(&output_mask)); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_addmm_out_out_Tensor_self_Tensor_mat1_Tensor_mat2_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor mat1, XPtrTorchTensor mat2, XPtrTorchScalar beta, XPtrTorchScalar alpha) { auto r_out = lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out.get(), self.get(), mat1.get(), mat2.get(), beta.get(), alpha.get()); @@ -11048,8 +11038,8 @@ return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor (XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups) { - auto r_out = lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self.get(), padding.get(), stride.get(), dilation.get(), groups.get()); +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_self_Tensor (XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size) { + auto r_out = lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(self.get(), padding.get(), stride.get(), dilation.get(), groups.get(), input_size.get()); return XPtrTorchTensor(r_out); } @@ -11341,12 +11331,12 @@ return XPtrTorchScalar(r_out); Rcpp::List cpp_torch_namespace__lstm_mps_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { auto r_out = lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5))); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { - auto r_out = lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); +Rcpp::List cpp_torch_namespace_lstm_mps_backward_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { + auto r_out = lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), layersOutputs.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 2))); } @@ -11958,12 +11948,6 @@ XPtrTorchTensor cpp_torch_namespace_diag_self_Tensor (XPtrTorchTensor self, XPtr return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_diag_backward_grad_Tensor_input_sizes_IntArrayRef_diagonal_int64_t (XPtrTorchTensor grad, XPtrTorchIntArrayRef input_sizes, XPtrTorchint64_t diagonal) { - auto r_out = lantern_diag_backward_tensor_intarrayref_intt(grad.get(), input_sizes.get(), diagonal.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_cross_out_out_Tensor_self_Tensor_other_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchoptional_index_int64_t dim) { auto r_out = lantern_cross_out_tensor_tensor_tensor_intt(out.get(), self.get(), other.get(), dim.get()); @@ -12487,27 +12471,6 @@ XPtrTorchTensor cpp_torch_namespace_linalg_vander_x_Tensor (XPtrTorchTensor x, X return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_symeig_out_e_Tensor_V_Tensor_self_Tensor (XPtrTorchTensor e, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern_symeig_out_tensor_tensor_tensor_bool_bool(e.get(), V.get(), self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_symeig_self_Tensor (XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern_symeig_tensor_bool_bool(self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__symeig_helper_self_Tensor_eigenvectors_bool_upper_bool (XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern__symeig_helper_tensor_bool_bool(self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_svd_out_U_Tensor_S_Tensor_V_Tensor_self_Tensor (XPtrTorchTensor U, XPtrTorchTensor S, XPtrTorchTensor V, XPtrTorchTensor self, XPtrTorchbool some, XPtrTorchbool compute_uv) { auto r_out = lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(U.get(), S.get(), V.get(), self.get(), some.get(), compute_uv.get()); @@ -13052,6 +13015,12 @@ XPtrTorchTensor cpp_torch_namespace_max_out_out_Tensor_other_Tensor_self_Tensor return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_max_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_max_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_minimum_self_Tensor_other_Tensor (XPtrTorchTensor self, XPtrTorchTensor other) { auto r_out = lantern_minimum_tensor_tensor(self.get(), other.get()); @@ -13435,6 +13404,50 @@ void cpp_torch_namespace__foreach_div__self_TensorList_scalar_Scalar (XPtrTorchT lantern__foreach_div__tensorlist_scalar(self.get(), scalar.get()); } +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_clamp_min_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_min__tensorlist_scalar(self.get(), scalar.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_clamp_max_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_max__tensorlist_scalar(self.get(), scalar.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_maximum_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_maximum__tensorlist_scalar(self.get(), scalar.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + auto r_out = lantern__foreach_minimum_tensorlist_scalar(self.get(), scalar.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalar_Scalar (XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_minimum__tensorlist_scalar(self.get(), scalar.get()); +} + // [[Rcpp::export]] XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha) { auto r_out = lantern__foreach_add_tensorlist_tensorlist_scalar(self.get(), other.get(), alpha.get()); @@ -13480,52 +13493,140 @@ void cpp_torch_namespace__foreach_div__self_TensorList_other_TensorList (XPtrTor } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_add_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_clamp_min_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_add__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_min__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_sub_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_clamp_max_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_sub__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_sub__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_max__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_div_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_div_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_maximum_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_div__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_maximum__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - auto r_out = lantern__foreach_mul_tensorlist_arrayrefscalar(self.get(), scalars.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + auto r_out = lantern__foreach_minimum_tensorlist_tensorlist(self.get(), other.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { - lantern__foreach_mul__tensorlist_arrayrefscalar(self.get(), scalars.get()); +void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_minimum__tensorlist_tensorlist(self.get(), other.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_exp_self_TensorList (XPtrTorchTensorList self) { - auto r_out = lantern__foreach_exp_tensorlist(self.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_add_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_add_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_add__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_add__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_sub_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_sub_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_sub__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_sub__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_div_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_div_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_div__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_div__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_mul_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_mul_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_mul__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_mul__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_min_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_clamp_min_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_min__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_clamp_max_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_clamp_max_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_max__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_maximum_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_maximum__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + auto r_out = lantern__foreach_minimum_tensorlist_arrayrefscalar(self.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum__self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_minimum__tensorlist_arrayrefscalar(self.get(), scalars.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_exp_self_TensorList (XPtrTorchTensorList self) { + auto r_out = lantern__foreach_exp_tensorlist(self.get()); return XPtrTorchTensorList(r_out); } @@ -13851,11 +13952,21 @@ void cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_te lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(self.get(), tensor1.get(), tensor2.get(), scalars.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_addcdiv__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(self.get(), tensor1.get(), tensor2.get(), scalars.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_addcmul__self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); +} + // [[Rcpp::export]] XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchScalar value) { auto r_out = lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(self.get(), tensor1.get(), tensor2.get(), value.get()); @@ -13874,6 +13985,12 @@ XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1 return XPtrTorchTensorList(r_out); } +// [[Rcpp::export]] +XPtrTorchTensorList cpp_torch_namespace__foreach_addcdiv_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + auto r_out = lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); +return XPtrTorchTensorList(r_out); +} + // [[Rcpp::export]] XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { auto r_out = lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(self.get(), tensor1.get(), tensor2.get(), scalars.get()); @@ -13881,33 +13998,39 @@ return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_maximum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - auto r_out = lantern__foreach_maximum_tensorlist_tensorlist(self.get(), other.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_addcmul_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + auto r_out = lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(self.get(), tensor1.get(), tensor2.get(), scalars.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_maximum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_maximum__tensorlist_tensorlist(self.get(), other.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList (XPtrTorchTensorList self, XPtrTorchScalar ord) { + auto r_out = lantern__foreach_norm_tensorlist_scalar(self.get(), ord.get()); +return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_minimum_self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - auto r_out = lantern__foreach_minimum_tensorlist_tensorlist(self.get(), other.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weights_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights) { + auto r_out = lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(self.get(), tensors1.get(), weights.get()); return XPtrTorchTensorList(r_out); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_minimum__self_TensorList_other_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_minimum__tensorlist_tensorlist(self.get(), other.get()); +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weights_TensorList (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights) { + lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(self.get(), tensors1.get(), weights.get()); } // [[Rcpp::export]] -XPtrTorchTensorList cpp_torch_namespace__foreach_norm_self_TensorList (XPtrTorchTensorList self, XPtrTorchScalar ord) { - auto r_out = lantern__foreach_norm_tensorlist_scalar(self.get(), ord.get()); +XPtrTorchTensorList cpp_torch_namespace__foreach_lerp_self_TensorList_tensors1_TensorList_weight_Scalar (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight) { + auto r_out = lantern__foreach_lerp_tensorlist_tensorlist_scalar(self.get(), tensors1.get(), weight.get()); return XPtrTorchTensorList(r_out); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_lerp__self_TensorList_tensors1_TensorList_weight_Scalar (XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight) { + lantern__foreach_lerp__tensorlist_tensorlist_scalar(self.get(), tensors1.get(), weight.get()); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_bucketize_self_Tensor_boundaries_Tensor (XPtrTorchTensor self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right) { auto r_out = lantern_bucketize_tensor_tensor_bool_bool(self.get(), boundaries.get(), out_int32.get(), right.get()); @@ -13932,12 +14055,6 @@ XPtrTorchTensor cpp_torch_namespace_searchsorted_sorted_sequence_Tensor_self_Ten return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_self_Tensor (XPtrTorchTensor self) { - auto r_out = lantern__torch_cuda_cu_linker_symbol_op_tensor(self.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_searchsorted_out_out_Tensor_sorted_sequence_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor sorted_sequence, XPtrTorchTensor self, XPtrTorchbool out_int32, XPtrTorchbool right, XPtrTorchoptional_string_view side, XPtrTorchOptionalTensor sorter) { auto r_out = lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(out.get(), sorted_sequence.get(), self.get(), out_int32.get(), right.get(), side.get(), sorter.get()); @@ -14978,72 +15095,36 @@ XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_input_Tensor_output_size_I return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(input.get(), output_size.get(), align_corners.get(), scale_factors.get()); return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(input.get(), output_size.get(), scale_factors.get()); @@ -15056,18 +15137,6 @@ XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_input_Tensor_outpu return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(input.get(), output_size.get(), scale_factors.get()); @@ -15080,18 +15149,6 @@ XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_input_Tensor_outpu return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { auto r_out = lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(input.get(), output_size.get(), scale_factors.get()); @@ -15104,18 +15161,6 @@ XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_input_Tensor_outpu return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_self_Tensor_output_size_IntArrayRef_align_corners_bool (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionaldouble scales) { auto r_out = lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(out.get(), self.get(), output_size.get(), align_corners.get(), scales.get()); @@ -17270,6 +17315,12 @@ XPtrTorchTensor cpp_torch_namespace_squeeze_copy_self_Tensor_dim_int64_t (XPtrTo return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_self_Tensor_dim_IntArrayRef (XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_squeeze_copy_tensor_intarrayref(self.get(), dim.get()); +return XPtrTorchTensor(r_out); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_t_copy_self_Tensor (XPtrTorchTensor self) { auto r_out = lantern_t_copy_tensor(self.get()); @@ -17342,6 +17393,21 @@ XPtrTorchTensorList cpp_torch_namespace_unbind_copy_self_Tensor (XPtrTorchTensor return XPtrTorchTensorList(r_out); } +// [[Rcpp::export]] +void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { + lantern_unbind_copy_out_tensorlist_tensor_intt(out.get(), self.get(), dim.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchint64_t split_size, XPtrTorchindex_int64_t dim) { + lantern_split_copy_out_tensorlist_tensor_intt_intt(out.get(), self.get(), split_size.get(), dim.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchIntArrayRef split_sizes, XPtrTorchindex_int64_t dim) { + lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out.get(), self.get(), split_sizes.get(), dim.get()); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_view_copy_self_Tensor_size_IntArrayRef (XPtrTorchTensor self, XPtrTorchIntArrayRef size) { auto r_out = lantern_view_copy_tensor_intarrayref(self.get(), size.get()); @@ -17367,249 +17433,121 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level) { - auto r_out = lantern__fw_primal_copy_out_tensor_tensor_intt(out.get(), self.get(), level.get()); +XPtrTorchTensor cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor (XPtrTorchTensor self, XPtrTorchTensor query) { + auto r_out = lantern__nested_tensor_softmax_with_shape_tensor_tensor(self.get(), query.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level) { - auto r_out = lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out.get(), primal.get(), tangent.get(), level.get()); +XPtrTorchTensor cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor (XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchoptional_int64_t mask_type) { + auto r_out = lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src.get(), embed_dim.get(), num_heads.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), use_gelu.get(), norm_first.get(), eps.get(), norm_weight_1.get(), norm_bias_1.get(), norm_weight_2.get(), norm_bias_2.get(), ffn_weight_1.get(), ffn_bias_1.get(), ffn_weight_2.get(), ffn_bias_2.get(), mask.get(), mask_type.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_view_as_real_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask, XPtrTorchbool need_weights, XPtrTorchbool average_attn_weights, XPtrTorchoptional_int64_t mask_type) { + auto r_out = lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get(), need_weights.get(), average_attn_weights.get(), mask_type.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_view_as_complex_copy_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal) { + auto r_out = lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), is_causal.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__conj_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { + auto r_out = lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__neg_view_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +XPtrTorchint64_t cpp_torch_namespace__fused_sdp_choice_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal) { + auto r_out = lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), is_causal.get()); +return XPtrTorchint64_t(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset) { - auto r_out = lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out.get(), self.get(), size.get(), stride.get(), storage_offset.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchOptionalTensor dropout_mask) { + auto r_out = lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), is_causal.get(), dropout_mask.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { - auto r_out = lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask) { + auto r_out = lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), dropout_p.get(), is_causal.get(), return_debug_mask.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 4)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 5)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 6)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 7)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 8))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2) { - auto r_out = lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), offset.get(), dim1.get(), dim2.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t (XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset) { + auto r_out = lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get(), philox_seed.get(), philox_offset.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit) { - auto r_out = lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out.get(), self.get(), size.get(), implicit.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_query_Tensor_key_Tensor_value_Tensor_compute_log_sumexp_bool (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool compute_log_sumexp, XPtrTorchbool is_causal) { + auto r_out = lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(query.get(), key.get(), value.get(), compute_log_sumexp.get(), is_causal.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims) { - auto r_out = lantern_permute_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), dims.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__scaled_dot_product_efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor (XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs) { + auto r_out = lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), is_causal.get(), chunk_grad_outputs.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride) { - auto r_out = lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out.get(), self.get(), size.get(), stride.get()); -return XPtrTorchTensor(r_out); +XPtrTorchbool cpp_torch_namespace__chunk_grad_outputs_efficient_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchbool is_causal) { + auto r_out = lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(query.get(), key.get(), value.get(), is_causal.get()); +return XPtrTorchbool(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index) { - auto r_out = lantern_select_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim.get(), index.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__flash_attention_forward_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_return_debug_mask_bool (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchbool return_debug_mask) { + auto r_out = lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(query.get(), key.get(), value.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get(), return_debug_mask.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 2)),XPtrTorchint64_t(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_detach_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__flash_attention_backward_grad_out_Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool_philox_seed_int64_t_philox_offset_int64_t (XPtrTorchTensor grad_out, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal, XPtrTorchint64_t philox_seed, XPtrTorchint64_t philox_offset) { + auto r_out = lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get(), philox_seed.get(), philox_offset.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step) { - auto r_out = lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out.get(), self.get(), dim.get(), start.get(), end.get(), step.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__efficient_attention_forward_query_Tensor_key_Tensor_value_Tensor_cu_seqlens_q_Tensor_cu_seqlens_k_Tensor_max_seqlen_q_int64_t (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor cu_seqlens_q, XPtrTorchOptionalTensor cu_seqlens_k, XPtrTorchoptional_int64_t max_seqlen_q, XPtrTorchbool compute_log_sumexp, XPtrTorchbool causal) { + auto r_out = lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(query.get(), key.get(), value.get(), cu_seqlens_q.get(), cu_seqlens_k.get(), max_seqlen_q.get(), compute_log_sumexp.get(), causal.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } // [[Rcpp::export]] -void cpp_torch_namespace_split_copy_out_out_TensorList_self_Tensor_split_size_int64_t (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchint64_t split_size, XPtrTorchindex_int64_t dim) { - lantern_split_copy_out_tensorlist_tensor_intt_intt(out.get(), self.get(), split_size.get(), dim.get()); +Rcpp::List cpp_torch_namespace__efficient_attention_backward_grad_out__Tensor_query_Tensor_key_Tensor_value_Tensor_out_Tensor_logsumexp_Tensor (XPtrTorchTensor grad_out_, XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor out, XPtrTorchTensor logsumexp, XPtrTorchbool is_causal, XPtrTorchbool chunk_grad_outputs) { + auto r_out = lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_.get(), query.get(), key.get(), value.get(), out.get(), logsumexp.get(), is_causal.get(), chunk_grad_outputs.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); } // [[Rcpp::export]] -void cpp_torch_namespace_split_with_sizes_copy_out_out_TensorList_self_Tensor_split_sizes_IntArrayRef (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchIntArrayRef split_sizes, XPtrTorchindex_int64_t dim) { - lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out.get(), self.get(), split_sizes.get(), dim.get()); +XPtrTorchTensor cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor (XPtrTorchTensor q, XPtrTorchTensor k, XPtrTorchTensor v, XPtrTorchdouble dropout_p) { + auto r_out = lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q.get(), k.get(), v.get(), dropout_p.get()); +return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_squeeze_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { - auto r_out = lantern_squeeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_t_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1) { - auto r_out = lantern_transpose_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim0.get(), dim1.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { - auto r_out = lantern_unsqueeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__values_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_values_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_crow_indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_col_indices_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -void cpp_torch_namespace_unbind_copy_out_out_TensorList_self_Tensor (XPtrTorchTensorList out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { - lantern_unbind_copy_out_tensorlist_tensor_intt(out.get(), self.get(), dim.get()); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { - auto r_out = lantern_view_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype) { - auto r_out = lantern_view_copy_out_tensor_tensor_scalartype(out.get(), self.get(), dtype.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step) { - auto r_out = lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), dimension.get(), size.get(), step.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_alias_copy_out_tensor_tensor(out.get(), self.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__nested_tensor_softmax_with_shape_self_Tensor_query_Tensor (XPtrTorchTensor self, XPtrTorchTensor query) { - auto r_out = lantern__nested_tensor_softmax_with_shape_tensor_tensor(self.get(), query.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__transformer_encoder_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor (XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchoptional_int64_t mask_type) { - auto r_out = lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src.get(), embed_dim.get(), num_heads.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), use_gelu.get(), norm_first.get(), eps.get(), norm_weight_1.get(), norm_bias_1.get(), norm_weight_2.get(), norm_bias_2.get(), ffn_weight_1.get(), ffn_bias_1.get(), ffn_weight_2.get(), ffn_bias_2.get(), mask.get(), mask_type.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__native_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask, XPtrTorchbool need_weights, XPtrTorchbool average_attn_weights, XPtrTorchoptional_int64_t mask_type) { - auto r_out = lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get(), need_weights.get(), average_attn_weights.get(), mask_type.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { - auto r_out = lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_forward_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { - auto r_out = lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__scaled_dot_product_attention_math_query_Tensor_key_Tensor_value_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchOptionalTensor attn_mask, XPtrTorchdouble dropout_p, XPtrTorchbool need_attn_weights, XPtrTorchbool is_causal) { - auto r_out = lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(query.get(), key.get(), value.get(), attn_mask.get(), dropout_p.get(), need_attn_weights.get(), is_causal.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__triton_scaled_dot_attention_q_Tensor_k_Tensor_v_Tensor (XPtrTorchTensor q, XPtrTorchTensor k, XPtrTorchTensor v, XPtrTorchdouble dropout_p) { - auto r_out = lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q.get(), k.get(), v.get(), dropout_p.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask) { - auto r_out = lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get()); +XPtrTorchTensor cpp_torch_namespace__triton_multi_head_attention_query_Tensor_key_Tensor_value_Tensor_embed_dim_int64_t_num_head_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_head, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchOptionalTensor mask) { + auto r_out = lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(query.get(), key.get(), value.get(), embed_dim.get(), num_head.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), mask.get()); return XPtrTorchTensor(r_out); } @@ -17625,12 +17563,6 @@ XPtrTorchTensor cpp_torch_namespace_special_airy_ai_out_out_Tensor_x_Tensor (XPt return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__flash_scaled_dot_product_attention_query_Tensor_key_Tensor_value_Tensor_cum_seq_q_Tensor_cum_seq_k_Tensor_max_q_int64_t_max_k_int64_t_dropout_p_double_is_causal_bool (XPtrTorchTensor query, XPtrTorchTensor key, XPtrTorchTensor value, XPtrTorchTensor cum_seq_q, XPtrTorchTensor cum_seq_k, XPtrTorchint64_t max_q, XPtrTorchint64_t max_k, XPtrTorchdouble dropout_p, XPtrTorchbool is_causal) { - auto r_out = lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(query.get(), key.get(), value.get(), cum_seq_q.get(), cum_seq_k.get(), max_q.get(), max_k.get(), dropout_p.get(), is_causal.get()); -return XPtrTorchTensor(r_out); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace__transformer_decoder_only_layer_fwd_src_Tensor_embed_dim_int64_t_num_heads_int64_t_qkv_weight_Tensor_qkv_bias_Tensor_proj_weight_Tensor_proj_bias_Tensor_use_gelu_bool_norm_first_bool_eps_double_norm_weight_1_Tensor_norm_bias_1_Tensor_norm_weight_2_Tensor_norm_bias_2_Tensor_ffn_weight_1_Tensor_ffn_bias_1_Tensor_ffn_weight_2_Tensor_ffn_bias_2_Tensor (XPtrTorchTensor src, XPtrTorchint64_t embed_dim, XPtrTorchint64_t num_heads, XPtrTorchTensor qkv_weight, XPtrTorchTensor qkv_bias, XPtrTorchTensor proj_weight, XPtrTorchTensor proj_bias, XPtrTorchbool use_gelu, XPtrTorchbool norm_first, XPtrTorchdouble eps, XPtrTorchTensor norm_weight_1, XPtrTorchTensor norm_bias_1, XPtrTorchTensor norm_weight_2, XPtrTorchTensor norm_bias_2, XPtrTorchTensor ffn_weight_1, XPtrTorchTensor ffn_bias_1, XPtrTorchTensor ffn_weight_2, XPtrTorchTensor ffn_bias_2, XPtrTorchOptionalTensor mask, XPtrTorchOptionalTensor incr_key, XPtrTorchOptionalTensor incr_value) { auto r_out = lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(src.get(), embed_dim.get(), num_heads.get(), qkv_weight.get(), qkv_bias.get(), proj_weight.get(), proj_bias.get(), use_gelu.get(), norm_first.get(), eps.get(), norm_weight_1.get(), norm_bias_1.get(), norm_weight_2.get(), norm_bias_2.get(), ffn_weight_1.get(), ffn_bias_1.get(), ffn_weight_2.get(), ffn_bias_2.get(), mask.get(), incr_key.get(), incr_value.get()); @@ -18220,6 +18152,11 @@ void cpp_torch_namespace__fused_adam__self_TensorList_grads_TensorList_exp_avgs_ lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__fused_adamw__self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool (XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf) { + lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__new_zeros_with_same_feature_meta_out_out_Tensor_self_Tensor_other_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor other, XPtrTorchint64_t self_num_batch_dims) { auto r_out = lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(out.get(), self.get(), other.get(), self_num_batch_dims.get()); @@ -18530,6 +18467,13 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__ctc_loss_out_out0_Tensor_out1_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_Tensor_target_lengths_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchTensor input_lengths, XPtrTorchTensor target_lengths, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity) { + auto r_out = lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(out0.get(), out1.get(), log_probs.get(), targets.get(), input_lengths.get(), target_lengths.get(), blank.get(), zero_infinity.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); +} + // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__ctc_loss_backward_out_out_Tensor_grad_Tensor_log_probs_Tensor_targets_Tensor_input_lengths_IntArrayRef_target_lengths_IntArrayRef_neg_log_likelihood_Tensor_log_alpha_Tensor_blank_int64_t (XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor log_probs, XPtrTorchTensor targets, XPtrTorchIntArrayRef input_lengths, XPtrTorchIntArrayRef target_lengths, XPtrTorchTensor neg_log_likelihood, XPtrTorchTensor log_alpha, XPtrTorchint64_t blank, XPtrTorchbool zero_infinity) { auto r_out = lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(out.get(), grad.get(), log_probs.get(), targets.get(), input_lengths.get(), target_lengths.get(), neg_log_likelihood.get(), log_alpha.get(), blank.get(), zero_infinity.get()); @@ -18923,14 +18867,8 @@ return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPt } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__mps_max_pool2d_out_out_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mps_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { - auto r_out = lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out.get(), grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); +XPtrTorchTensor cpp_torch_namespace_max_pool2d_backward_out_out_Tensor_grad_output_Tensor_self_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation, XPtrTorchbool ceil_mode) { + auto r_out = lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out.get(), grad_output.get(), self.get(), kernel_size.get(), stride.get(), padding.get(), dilation.get(), ceil_mode.get()); return XPtrTorchTensor(r_out); } @@ -19001,6 +18939,20 @@ XPtrTorchTensor cpp_torch_namespace_mkldnn_convolution_out_out_Tensor_self_Tenso return XPtrTorchTensor(r_out); } +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_input_Tensor_weight0_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_hx__Tensor_cx__Tensor_reverse_bool_batch_sizes_IntArrayRef_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_bidirectional_bool_batch_first_bool_train_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor input, XPtrTorchTensor weight0, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor hx_, XPtrTorchTensor cx_, XPtrTorchbool reverse, XPtrTorchIntArrayRef batch_sizes, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool bidirectional, XPtrTorchbool batch_first, XPtrTorchbool train) { + auto r_out = lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(out0.get(), out1.get(), out2.get(), out3.get(), input.get(), weight0.get(), weight1.get(), weight2.get(), weight3.get(), hx_.get(), cx_.get(), reverse.get(), batch_sizes.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), bidirectional.get(), batch_first.get(), train.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3))); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace_mkldnn_rnn_layer_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_out6_Tensor_input_Tensor_weight1_Tensor_weight2_Tensor_weight3_Tensor_weight4_Tensor_hx__Tensor_cx_tmp_Tensor_output_Tensor_hy__Tensor_cy__Tensor_grad_output_Tensor_grad_hy_Tensor_grad_cy_Tensor_reverse_bool_mode_int64_t_hidden_size_int64_t_num_layers_int64_t_has_biases_bool_train_bool_bidirectional_bool_batch_sizes_IntArrayRef_batch_first_bool_workspace_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor out6, XPtrTorchTensor input, XPtrTorchTensor weight1, XPtrTorchTensor weight2, XPtrTorchTensor weight3, XPtrTorchTensor weight4, XPtrTorchTensor hx_, XPtrTorchTensor cx_tmp, XPtrTorchTensor output, XPtrTorchTensor hy_, XPtrTorchTensor cy_, XPtrTorchOptionalTensor grad_output, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchbool reverse, XPtrTorchint64_t mode, XPtrTorchint64_t hidden_size, XPtrTorchint64_t num_layers, XPtrTorchbool has_biases, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchIntArrayRef batch_sizes, XPtrTorchbool batch_first, XPtrTorchTensor workspace) { + auto r_out = lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(out0.get(), out1.get(), out2.get(), out3.get(), out4.get(), out5.get(), out6.get(), input.get(), weight1.get(), weight2.get(), weight3.get(), weight4.get(), hx_.get(), cx_tmp.get(), output.get(), hy_.get(), cy_.get(), grad_output.get(), grad_hy.get(), grad_cy.get(), reverse.get(), mode.get(), hidden_size.get(), num_layers.get(), has_biases.get(), train.get(), bidirectional.get(), batch_sizes.get(), batch_first.get(), workspace.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 6))); +} + // [[Rcpp::export]] Rcpp::List cpp_torch_namespace_miopen_batch_norm_out_out0_Tensor_out1_Tensor_out2_Tensor_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_exponential_average_factor_double_epsilon_double (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor input, XPtrTorchTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchOptionalTensor running_mean, XPtrTorchOptionalTensor running_var, XPtrTorchbool training, XPtrTorchdouble exponential_average_factor, XPtrTorchdouble epsilon) { auto r_out = lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out0.get(), out1.get(), out2.get(), input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), exponential_average_factor.get(), epsilon.get()); @@ -19052,15 +19004,16 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__sparse_mask_helper_out_out_Tensor_t_Tensor_mask_indices_Tensor (XPtrTorchTensor out, XPtrTorchTensor t, XPtrTorchTensor mask_indices) { - auto r_out = lantern__sparse_mask_helper_out_tensor_tensor_tensor(out.get(), t.get(), mask_indices.get()); +XPtrTorchTensor cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchScalar other) { + auto r_out = lantern_mul_out_tensor_tensor_scalar(out.get(), self.get(), other.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mul_out_out_Tensor_self_Tensor_other_Scalar (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchScalar other) { - auto r_out = lantern_mul_out_tensor_tensor_scalar(out.get(), self.get(), other.get()); -return XPtrTorchTensor(r_out); +Rcpp::List cpp_torch_namespace__native_batch_norm_legit_functional_input_Tensor_weight_Tensor_bias_Tensor_running_mean_Tensor_running_var_Tensor_training_bool_momentum_double_eps_double (XPtrTorchTensor input, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchTensor running_mean, XPtrTorchTensor running_var, XPtrTorchbool training, XPtrTorchdouble momentum, XPtrTorchdouble eps) { + auto r_out = lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(input.get(), weight.get(), bias.get(), running_mean.get(), running_var.get(), training.get(), momentum.get(), eps.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); } // [[Rcpp::export]] @@ -19261,19 +19214,6 @@ XPtrTorchTensor cpp_torch_namespace_relu_out_out_Tensor_self_Tensor (XPtrTorchTe return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_prelu_out_out_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_prelu_out_tensor_tensor_tensor(out.get(), self.get(), weight.get()); -return XPtrTorchTensor(r_out); -} - -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_prelu_backward_out_out0_Tensor_out1_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight) { - auto r_out = lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(out0.get(), out1.get(), grad_output.get(), self.get(), weight.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_select_backward_out_out_Tensor_grad_output_Tensor_input_sizes_IntArrayRef_dim_int64_t_index_int64_t (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchIntArrayRef input_sizes, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index) { auto r_out = lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(out.get(), grad_output.get(), input_sizes.get(), dim.get(), index.get()); @@ -19332,13 +19272,6 @@ XPtrTorchTensor cpp_torch_namespace_sum_out_out_Tensor_self_Tensor (XPtrTorchTen return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_std_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_std_mean_out_tensor_tensor_tensor_intarrayref_intt_bool(out0.get(), out1.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace_prod_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_scalar_type dtype) { auto r_out = lantern_prod_out_tensor_tensor_scalartype(out.get(), self.get(), dtype.get()); @@ -19459,13 +19392,6 @@ XPtrTorchTensor cpp_torch_namespace__unsafe_view_out_out_Tensor_self_Tensor_size return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace_var_mean_out_out0_Tensor_out1_Tensor_self_Tensor_dim_IntArrayRef_correction_int64_t (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchOptionalIndexIntArrayRef dim, XPtrTorchoptional_int64_t correction, XPtrTorchbool keepdim) { - auto r_out = lantern_var_mean_out_tensor_tensor_tensor_intarrayref_intt_bool(out0.get(), out1.get(), self.get(), dim.get(), correction.get(), keepdim.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] Rcpp::List cpp_torch_namespace__weight_norm_interface_out_out0_Tensor_out1_Tensor_v_Tensor_g_Tensor (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor v, XPtrTorchTensor g, XPtrTorchindex_int64_t dim) { auto r_out = lantern__weight_norm_interface_out_tensor_tensor_tensor_tensor_intt(out0.get(), out1.get(), v.get(), g.get(), dim.get()); @@ -19769,32 +19695,32 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_to_sparse_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchLayout layout, XPtrTorchOptionalIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(out.get(), self.get(), layout.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_to_sparse_csr_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_csr_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_csr_out_tensor_tensor_intt(out.get(), self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_to_sparse_csc_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_csc_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_csc_out_tensor_tensor_intt(out.get(), self.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(out.get(), self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsr_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(out.get(), self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize) { - auto r_out = lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(out.get(), self.get(), blocksize.get()); +XPtrTorchTensor cpp_torch_namespace_to_sparse_bsc_out_out_Tensor_self_Tensor_blocksize_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef blocksize, XPtrTorchoptional_int64_t dense_dim) { + auto r_out = lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(out.get(), self.get(), blocksize.get(), dense_dim.get()); return XPtrTorchTensor(r_out); } @@ -19805,8 +19731,8 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups) { - auto r_out = lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out.get(), self.get(), padding.get(), stride.get(), dilation.get(), groups.get()); +XPtrTorchTensor cpp_torch_namespace_mkldnn_reorder_conv2d_weight_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef dilation, XPtrTorchint64_t groups, XPtrTorchOptionalIntArrayRef input_size) { + auto r_out = lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(out.get(), self.get(), padding.get(), stride.get(), dilation.get(), groups.get(), input_size.get()); return XPtrTorchTensor(r_out); } @@ -19940,15 +19866,15 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { - auto r_out = lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), out3.get(), out4.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); +Rcpp::List cpp_torch_namespace__lstm_mps_out_out0_Tensor_out1_Tensor_out2_Tensor_out3_Tensor_out4_Tensor_out5_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor out3, XPtrTorchTensor out4, XPtrTorchTensor out5, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { + auto r_out = lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), out3.get(), out4.get(), out5.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4))); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 4)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 5))); } // [[Rcpp::export]] -void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { - lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); +void cpp_torch_namespace_lstm_mps_backward_out_out0_Tensor_out1_TensorList_out2_TensorList_grad_y_Tensor_grad_hy_Tensor_grad_cy_Tensor_z_state_Tensor_cell_state_fwd_Tensor_input_Tensor_layersOutputs_Tensor_hx_TensorList_params_TensorList_has_biases_bool_num_layers_int64_t_dropout_double_train_bool_bidirectional_bool_batch_first_bool (XPtrTorchTensor out0, XPtrTorchTensorList out1, XPtrTorchTensorList out2, XPtrTorchTensor grad_y, XPtrTorchOptionalTensor grad_hy, XPtrTorchOptionalTensor grad_cy, XPtrTorchTensor z_state, XPtrTorchTensor cell_state_fwd, XPtrTorchTensor input, XPtrTorchTensor layersOutputs, XPtrTorchTensorList hx, XPtrTorchTensorList params, XPtrTorchbool has_biases, XPtrTorchint64_t num_layers, XPtrTorchdouble dropout, XPtrTorchbool train, XPtrTorchbool bidirectional, XPtrTorchbool batch_first) { + lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0.get(), out1.get(), out2.get(), grad_y.get(), grad_hy.get(), grad_cy.get(), z_state.get(), cell_state_fwd.get(), input.get(), layersOutputs.get(), hx.get(), params.get(), has_biases.get(), num_layers.get(), dropout.get(), train.get(), bidirectional.get(), batch_first.get()); } // [[Rcpp::export]] @@ -20262,13 +20188,6 @@ XPtrTorchTensor cpp_torch_namespace_trace_out_out_Tensor_self_Tensor (XPtrTorchT return XPtrTorchTensor(r_out); } -// [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__symeig_helper_out_out0_Tensor_out1_Tensor_self_Tensor_eigenvectors_bool_upper_bool (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor self, XPtrTorchbool eigenvectors, XPtrTorchbool upper) { - auto r_out = lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(out0.get(), out1.get(), self.get(), eigenvectors.get(), upper.get()); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1))); -} - // [[Rcpp::export]] XPtrTorchTensor cpp_torch_namespace__cholesky_solve_helper_out_out_Tensor_self_Tensor_A_Tensor_upper_bool (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor A, XPtrTorchbool upper) { auto r_out = lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(out.get(), self.get(), A.get(), upper.get()); @@ -20367,6 +20286,26 @@ void cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_scalar_ lantern__foreach_div_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalar_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchScalar scalar) { + lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(out.get(), self.get(), scalar.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other, XPtrTorchScalar alpha) { lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(out.get(), self.get(), other.get(), alpha.get()); @@ -20387,6 +20326,26 @@ void cpp_torch_namespace__foreach_div_out_out_TensorList_self_TensorList_other_T lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { + lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_add_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); @@ -20407,6 +20366,26 @@ void cpp_torch_namespace__foreach_mul_out_out_TensorList_self_TensorList_scalars lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); } +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_min_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_clamp_max_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + +// [[Rcpp::export]] +void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchvector_Scalar scalars) { + lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), scalars.get()); +} + // [[Rcpp::export]] void cpp_torch_namespace__foreach_exp_out_out_TensorList_self_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self) { lantern__foreach_exp_out_tensorlist_tensorlist(out.get(), self.get()); @@ -20574,18 +20553,18 @@ void cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_ten } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { - lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); +void cpp_torch_namespace__foreach_addcdiv_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_maximum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_ArrayRefScalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchvector_Scalar scalars) { + lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); } // [[Rcpp::export]] -void cpp_torch_namespace__foreach_minimum_out_out_TensorList_self_TensorList_other_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList other) { - lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out.get(), self.get(), other.get()); +void cpp_torch_namespace__foreach_addcmul_out_out_TensorList_self_TensorList_tensor1_TensorList_tensor2_TensorList_scalars_Tensor (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensor1, XPtrTorchTensorList tensor2, XPtrTorchTensor scalars) { + lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out.get(), self.get(), tensor1.get(), tensor2.get(), scalars.get()); } // [[Rcpp::export]] @@ -20594,14 +20573,18 @@ void cpp_torch_namespace__foreach_norm_out_out_TensorList_self_TensorList (XPtrT } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor (XPtrTorchTensor out, XPtrTorchScalar self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right) { - auto r_out = lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out.get(), self.get(), boundaries.get(), out_int32.get(), right.get()); -return XPtrTorchTensor(r_out); +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weights_TensorList (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchTensorList weights) { + lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(out.get(), self.get(), tensors1.get(), weights.get()); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__torch_cuda_cu_linker_symbol_op_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(out.get(), self.get()); +void cpp_torch_namespace__foreach_lerp_out_out_TensorList_self_TensorList_tensors1_TensorList_weight_Scalar (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList tensors1, XPtrTorchScalar weight) { + lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(out.get(), self.get(), tensors1.get(), weight.get()); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_bucketize_out_out_Tensor_self_Scalar_boundaries_Tensor (XPtrTorchTensor out, XPtrTorchScalar self, XPtrTorchTensor boundaries, XPtrTorchbool out_int32, XPtrTorchbool right) { + auto r_out = lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out.get(), self.get(), boundaries.get(), out_int32.get(), right.get()); return XPtrTorchTensor(r_out); } @@ -20666,237 +20649,255 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask) { + auto r_out = lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0.get(), out1.get(), out2.get(), grad_output.get(), self.get(), weight.get(), kernel_size.get(), stride.get(), padding.get(), reinterpret_cast(&output_mask)); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { + auto r_out = lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_linear1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { + auto r_out = lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { + auto r_out = lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bilinear2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_isinf_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_linalg_matrix_exp_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bilinear2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { + auto r_out = lantern__test_optional_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { + auto r_out = lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_trilinear3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends) { + auto r_out = lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(out.get(), values.get(), addends.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__test_warn_in_autograd_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_bicubic2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__test_autograd_multiple_dispatch_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_out_out_Tensor_input_Tensor_output_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out.get(), input.get(), output_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_bicubic2d_aa_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_align_corners_bool_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchbool align_corners, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), align_corners.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial) { + auto r_out = lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(out.get(), data.get(), reduce.get(), lengths.get(), indices.get(), offsets.get(), axis.get(), unsafe.get(), initial.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial) { + auto r_out = lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out.get(), grad.get(), output.get(), data.get(), reduce.get(), lengths.get(), offsets.get(), axis.get(), initial.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList (XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory) { + auto r_out = lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out.get(), list.get(), dtype.get(), layout.get(), device.get(), pin_memory.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__fw_primal_copy_out_out_Tensor_self_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t level) { + auto r_out = lantern__fw_primal_copy_out_tensor_tensor_intt(out.get(), self.get(), level.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact1d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__make_dual_copy_out_out_Tensor_primal_Tensor_tangent_Tensor_level_int64_t (XPtrTorchTensor out, XPtrTorchTensor primal, XPtrTorchTensor tangent, XPtrTorchint64_t level) { + auto r_out = lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out.get(), primal.get(), tangent.get(), level.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_view_as_real_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_view_as_real_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_view_as_complex_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_view_as_complex_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__conj_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__conj_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact2d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__neg_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__neg_view_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_as_strided_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride, XPtrTorchoptional_int64_t storage_offset) { + auto r_out = lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out.get(), self.get(), size.get(), stride.get(), storage_offset.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_out_out_Tensor_input_Tensor_output_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor input, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(out.get(), input.get(), output_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace__sparse_broadcast_to_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { + auto r_out = lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_upsample_nearest3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_diagonal_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t offset, XPtrTorchindex_int64_t dim1, XPtrTorchindex_int64_t dim2) { + auto r_out = lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), offset.get(), dim1.get(), dim2.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__upsample_nearest_exact3d_backward_out_out_Tensor_grad_output_Tensor_output_size_IntArrayRef_input_size_IntArrayRef_scale_factors_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor grad_output, XPtrTorchOptionalIntArrayRef output_size, XPtrTorchIntArrayRef input_size, XPtrTorchOptionalDoubleArrayRef scale_factors) { - auto r_out = lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out.get(), grad_output.get(), output_size.get(), input_size.get(), scale_factors.get()); +XPtrTorchTensor cpp_torch_namespace_expand_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchbool implicit) { + auto r_out = lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out.get(), self.get(), size.get(), implicit.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -Rcpp::List cpp_torch_namespace__slow_conv2d_backward_out_out0_Tensor_out1_Tensor_out2_Tensor_grad_output_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_stride_IntArrayRef_padding_IntArrayRef_output_mask_stdarraybool3 (XPtrTorchTensor out0, XPtrTorchTensor out1, XPtrTorchTensor out2, XPtrTorchTensor grad_output, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, std::vector output_mask) { - auto r_out = lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0.get(), out1.get(), out2.get(), grad_output.get(), self.get(), weight.get(), kernel_size.get(), stride.get(), padding.get(), reinterpret_cast(&output_mask)); -auto wrap = XPtrTorchvector_void(r_out); -return Rcpp::List::create(XPtrTorchTensor(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensor(lantern_vector_get(wrap.get(), 2))); +XPtrTorchTensor cpp_torch_namespace_permute_copy_out_out_Tensor_self_Tensor_dims_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dims) { + auto r_out = lantern_permute_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), dims.get()); +return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_conv_depthwise3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef_bias_Tensor_stride_IntArrayRef_padding_IntArrayRef_dilation_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { - auto r_out = lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); +XPtrTorchTensor cpp_torch_namespace__reshape_alias_copy_out_out_Tensor_self_Tensor_size_IntArrayRef_stride_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size, XPtrTorchIntArrayRef stride) { + auto r_out = lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out.get(), self.get(), size.get(), stride.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated2d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { - auto r_out = lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); +XPtrTorchTensor cpp_torch_namespace_select_copy_out_out_Tensor_self_Tensor_dim_int64_t_index_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchindex_int64_t index) { + auto r_out = lantern_select_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim.get(), index.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_slow_conv_dilated3d_out_out_Tensor_self_Tensor_weight_Tensor_kernel_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchTensor weight, XPtrTorchIntArrayRef kernel_size, XPtrTorchOptionalTensor bias, XPtrTorchIntArrayRef stride, XPtrTorchIntArrayRef padding, XPtrTorchIntArrayRef dilation) { - auto r_out = lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(out.get(), self.get(), weight.get(), kernel_size.get(), bias.get(), stride.get(), padding.get(), dilation.get()); +XPtrTorchTensor cpp_torch_namespace_detach_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_detach_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_isinf_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_isinf_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_slice_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim, XPtrTorchoptional_int64_t start, XPtrTorchoptional_int64_t end, XPtrTorchint64_t step) { + auto r_out = lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out.get(), self.get(), dim.get(), start.get(), end.get(), step.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_linalg_matrix_exp_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern_linalg_matrix_exp_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_squeeze_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_optional_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { - auto r_out = lantern__test_optional_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { + auto r_out = lantern_squeeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_optional_filled_intlist_out_out_Tensor_values_Tensor_addends_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalIntArrayRef addends) { - auto r_out = lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(out.get(), values.get(), addends.get()); +XPtrTorchTensor cpp_torch_namespace_squeeze_copy_out_out_Tensor_self_Tensor_dim_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIndexIntArrayRef dim) { + auto r_out = lantern_squeeze_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_optional_floatlist_out_out_Tensor_values_Tensor_addends_ArrayRefdouble (XPtrTorchTensor out, XPtrTorchTensor values, XPtrTorchOptionalDoubleArrayRef addends) { - auto r_out = lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(out.get(), values.get(), addends.get()); +XPtrTorchTensor cpp_torch_namespace_t_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_t_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_warn_in_autograd_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__test_warn_in_autograd_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_transpose_copy_out_out_Tensor_self_Tensor_dim0_int64_t_dim1_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim0, XPtrTorchindex_int64_t dim1) { + auto r_out = lantern_transpose_copy_out_tensor_tensor_intt_intt(out.get(), self.get(), dim0.get(), dim1.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__test_autograd_multiple_dispatch_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace_unsqueeze_copy_out_out_Tensor_self_Tensor_dim_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchindex_int64_t dim) { + auto r_out = lantern_unsqueeze_copy_out_tensor_tensor_intt(out.get(), self.get(), dim.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__test_autograd_multiple_dispatch_view_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { - auto r_out = lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(out.get(), self.get()); +XPtrTorchTensor cpp_torch_namespace__indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__indices_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_segment_reduce_out_out_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchIndexTensor indices, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchbool unsafe, XPtrTorchoptional_scalar initial) { - auto r_out = lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(out.get(), data.get(), reduce.get(), lengths.get(), indices.get(), offsets.get(), axis.get(), unsafe.get(), initial.get()); +XPtrTorchTensor cpp_torch_namespace__values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern__values_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__segment_reduce_backward_out_out_Tensor_grad_Tensor_output_Tensor_data_Tensor_reduce_c10string_view (XPtrTorchTensor out, XPtrTorchTensor grad, XPtrTorchTensor output, XPtrTorchTensor data, XPtrTorchstring_view reduce, XPtrTorchOptionalTensor lengths, XPtrTorchOptionalTensor offsets, XPtrTorchint64_t axis, XPtrTorchoptional_scalar initial) { - auto r_out = lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out.get(), grad.get(), output.get(), data.get(), reduce.get(), lengths.get(), offsets.get(), axis.get(), initial.get()); +XPtrTorchTensor cpp_torch_namespace_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_indices_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__nested_tensor_from_tensor_list_out_out_Tensor_list_TensorList (XPtrTorchTensor out, XPtrTorchTensorList list, XPtrTorchoptional_scalar_type dtype, XPtrTorchLayout layout, XPtrTorchDevice device, XPtrTorchoptional_bool pin_memory) { - auto r_out = lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out.get(), list.get(), dtype.get(), layout.get(), device.get(), pin_memory.get()); +XPtrTorchTensor cpp_torch_namespace_values_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_values_copy_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_crow_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_crow_indices_copy_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_col_indices_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_col_indices_copy_out_tensor_tensor(out.get(), self.get()); return XPtrTorchTensor(r_out); } @@ -20913,14 +20914,32 @@ return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchdouble padding, XPtrTorchOptionalIntArrayRef output_size) { - auto r_out = lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out.get(), self.get(), padding.get(), output_size.get()); +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_size_IntArrayRef (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchIntArrayRef size) { + auto r_out = lantern_view_copy_out_tensor_tensor_intarrayref(out.get(), self.get(), size.get()); return XPtrTorchTensor(r_out); } // [[Rcpp::export]] -XPtrTorchTensor cpp_torch_namespace__nested_tensor_layer_norm_out_out_Tensor_self_Tensor_weight_Tensor_bias_Tensor_eps_double (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchOptionalTensor weight, XPtrTorchOptionalTensor bias, XPtrTorchdouble eps) { - auto r_out = lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(out.get(), self.get(), weight.get(), bias.get(), eps.get()); +XPtrTorchTensor cpp_torch_namespace_view_copy_out_out_Tensor_self_Tensor_dtype_ScalarType (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchDtype dtype) { + auto r_out = lantern_view_copy_out_tensor_tensor_scalartype(out.get(), self.get(), dtype.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_unfold_copy_out_out_Tensor_self_Tensor_dimension_int64_t_size_int64_t_step_int64_t (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchint64_t dimension, XPtrTorchint64_t size, XPtrTorchint64_t step) { + auto r_out = lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out.get(), self.get(), dimension.get(), size.get(), step.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_alias_copy_out_out_Tensor_self_Tensor (XPtrTorchTensor out, XPtrTorchTensor self) { + auto r_out = lantern_alias_copy_out_tensor_tensor(out.get(), self.get()); +return XPtrTorchTensor(r_out); +} + +// [[Rcpp::export]] +XPtrTorchTensor cpp_torch_namespace_to_padded_tensor_out_out_Tensor_self_Tensor_padding_double (XPtrTorchTensor out, XPtrTorchTensor self, XPtrTorchdouble padding, XPtrTorchOptionalIntArrayRef output_size) { + auto r_out = lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out.get(), self.get(), padding.get(), output_size.get()); return XPtrTorchTensor(r_out); } @@ -20981,3 +21000,15 @@ auto wrap = XPtrTorchvector_void(r_out); return Rcpp::List::create(XPtrTorchTensorList(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 4))); } +// [[Rcpp::export]] +void cpp_torch_namespace__fused_adamw_out_out_TensorList_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool (XPtrTorchTensorList out, XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf) { + lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out.get(), self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); +} + +// [[Rcpp::export]] +Rcpp::List cpp_torch_namespace__fused_adamw_self_TensorList_grads_TensorList_exp_avgs_TensorList_exp_avg_sqs_TensorList_max_exp_avg_sqs_TensorList_state_steps_TensorList_lr_double_beta1_double_beta2_double_weight_decay_double_eps_double_amsgrad_bool_maximize_bool (XPtrTorchTensorList self, XPtrTorchTensorList grads, XPtrTorchTensorList exp_avgs, XPtrTorchTensorList exp_avg_sqs, XPtrTorchTensorList max_exp_avg_sqs, XPtrTorchTensorList state_steps, XPtrTorchdouble lr, XPtrTorchdouble beta1, XPtrTorchdouble beta2, XPtrTorchdouble weight_decay, XPtrTorchdouble eps, XPtrTorchbool amsgrad, XPtrTorchbool maximize, XPtrTorchOptionalTensor grad_scale, XPtrTorchOptionalTensor found_inf) { + auto r_out = lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self.get(), grads.get(), exp_avgs.get(), exp_avg_sqs.get(), max_exp_avg_sqs.get(), state_steps.get(), lr.get(), beta1.get(), beta2.get(), weight_decay.get(), eps.get(), amsgrad.get(), maximize.get(), grad_scale.get(), found_inf.get()); +auto wrap = XPtrTorchvector_void(r_out); +return Rcpp::List::create(XPtrTorchTensorList(lantern_vector_get(wrap.get(), 0)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 1)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 2)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 3)),XPtrTorchTensorList(lantern_vector_get(wrap.get(), 4))); +} + diff --git a/src/lantern/CMakeLists.txt b/src/lantern/CMakeLists.txt index 759e9b4cbb..f9c79e8de0 100644 --- a/src/lantern/CMakeLists.txt +++ b/src/lantern/CMakeLists.txt @@ -1,7 +1,7 @@ cmake_minimum_required(VERSION 3.19.2) project(lantern) -set(TORCH_VERSION "1.13.1") +set(TORCH_VERSION "2.0.1") if (NOT DEFINED TORCH_PATH) if (DEFINED ENV{TORCH_PATH}) @@ -17,6 +17,9 @@ if (DEFINED ENV{CUDA} AND NOT "$ENV{CUDA}" STREQUAL "") string(REPLACE "\." "" CUDA_VERSION_NUMBER "$ENV{CUDA}") set(CUDA_VERSION "$ENV{CUDA}") message(STATUS "CUDA VERSION: $ENV{CUDA} | ${CUDA_VERSION} | ${CUDA_VERSION_NUMBER}") + + set(CAFFE2_USE_CUDNN 1) + set(ENV{TORCH_CUDA_ARCH_LIST} "3.7 5.0 5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX") endif() diff --git a/src/lantern/headers/declarations/declarations.yaml b/src/lantern/headers/declarations/declarations.yaml index 30d70db719..88688e1499 100644 --- a/src/lantern/headers/declarations/declarations.yaml +++ b/src/lantern/headers/declarations/declarations.yaml @@ -6150,6 +6150,113 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _is_all_true + operator_name: _is_all_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_all_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _is_any_true + operator_name: _is_any_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_any_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_check_tensor + operator_name: _test_check_tensor + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_check_tensor(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: all operator_name: all overload_name: dim @@ -10177,11 +10284,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: bilinear operator_name: bilinear overload_name: '' @@ -11999,7 +12106,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::broadcast_to(Tensor(a) self, int[] size) -> Tensor(a) + schema_string: aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -13072,7 +13179,7 @@ type: ::std::vector inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: false with_gil: false deprecated: false @@ -13082,7 +13189,7 @@ overload_name: sections manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.sections(Tensor(a -> *) self, int sections, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -13140,7 +13247,7 @@ overload_name: indices manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.indices(Tensor(a -> *) self, int[] indices, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -14875,7 +14982,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd(Tensor self, int[] pad, Scalar value=0) -> Tensor + schema_string: aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -14981,7 +15088,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor + schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15096,7 +15203,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -15486,7 +15593,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor + schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15881,7 +15988,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -17272,11 +17379,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: copy_ operator_name: copy_ overload_name: '' @@ -24191,7 +24298,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor + schema_string: aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24272,7 +24379,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor + schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24357,7 +24464,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor + schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25234,7 +25341,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25381,7 +25488,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25508,7 +25615,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31728,7 +31835,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c(Tensor self, int[] dim, int normalization, bool forward) -> Tensor + schema_string: aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31793,7 +31900,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c.out(Tensor self, int[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -34412,7 +34519,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::layer_norm(Tensor input, int[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor + schema_string: aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -39598,7 +39705,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, int[] sizes, bool keepdim) -> Tensor + schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, SymInt[] sizes, bool keepdim) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40106,17 +40213,128 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: true -- name: _mps_max_pool2d - operator_name: _mps_max_pool2d +- name: max_pool2d_backward + operator_name: max_pool2d_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_max_pool2d + operator_name: mkldnn_max_pool2d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40212,12 +40430,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mps_max_pool2d_backward - operator_name: mps_max_pool2d_backward +- name: mkldnn_max_pool2d_backward + operator_name: mkldnn_max_pool2d_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40227,7 +40445,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40262,7 +40485,7 @@ is_nullable: false name: ceil_mode type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -40272,7 +40495,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40323,12 +40551,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mkldnn_max_pool2d - operator_name: mkldnn_max_pool2d +- name: mkldnn_max_pool3d + operator_name: mkldnn_max_pool3d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40339,28 +40567,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -40379,250 +40607,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool2d_backward - operator_name: mkldnn_max_pool2d_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool3d - operator_name: mkldnn_max_pool3d - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -42969,7 +42975,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups) -> Tensor + schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43059,12 +43065,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: miopen_batch_norm - operator_name: miopen_batch_norm +- name: mkldnn_rnn_layer + operator_name: mkldnn_rnn_layer overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + schema_string: aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -43074,39 +43080,506 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: weight + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward + operator_name: mkldnn_rnn_layer_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: bias + name: grad_output type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_mean + name: grad_hy type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_var + name: grad_cy type: const c10::optional & - annotation: null dynamic_type: bool is_nullable: false - name: training + name: reverse type: bool - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: exponential_average_factor - type: double + name: mode + type: int64_t - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: epsilon - type: double - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + - dynamic_type: at::Tensor + name: result4 + type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor + - dynamic_type: at::Tensor + name: result6 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: miopen_batch_norm + operator_name: miopen_batch_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_mean + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_var + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: exponential_average_factor + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: epsilon + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -43286,7 +43759,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43401,7 +43874,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43526,7 +43999,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -44417,312 +44890,53 @@ with_gil: false deprecated: false has_math_kernel: true -- name: _sparse_sparse_matmul - operator_name: _sparse_sparse_matmul - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _sparse_mask_helper - operator_name: _sparse_mask_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_mask_helper(Tensor t, Tensor mask_indices) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: '' +- name: _sparse_mm + operator_name: _sparse_mm + overload_name: reduce manual_kernel_registration: false category_override: '' - schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + schema_string: aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode_out - operator_name: mode - overload_name: values - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + name: reduce + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: dimname - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool + name: reduce + type: c10::string_view method_of: - Type - - Tensor - namespace mode: native - python_module: '' + python_module: sparse returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: result type: at::Tensor inplace: false is_factory_method: false @@ -44731,106 +44945,375 @@ with_gil: false deprecated: false has_math_kernel: true -- name: mode_out - operator_name: mode - overload_name: dimname_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: mul - operator_name: mul - overload_name: Tensor +- name: _sparse_sparse_matmul + operator_name: _sparse_sparse_matmul + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor + schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode_out + operator_name: mode + overload_name: values + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: dimname + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mode_out + operator_name: mode + overload_name: dimname_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mul + operator_name: mul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -45712,7 +46195,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::narrow(Tensor(a) self, int dim, int start, int length) -> Tensor(a) + schema_string: aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -45778,7 +46261,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, int length) -> Tensor(a) + schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -46103,6 +46586,494 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) + arguments: + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: no_stats + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: no_stats_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: batch_norm_stats operator_name: batch_norm_stats overload_name: '' @@ -47024,7 +47995,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1) -> Tensor + schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -49165,7 +50136,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49247,7 +50218,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49341,7 +50312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::rand(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49411,7 +50382,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49493,7 +50464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49542,7 +50513,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49687,7 +50658,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randint(int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49767,7 +50738,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator(int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49859,7 +50830,7 @@ overload_name: low manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low(int low, int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49949,7 +50920,7 @@ overload_name: low_generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator(int low, int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -50051,7 +51022,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.out(int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50110,7 +51081,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator_out(int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50181,7 +51152,7 @@ overload_name: low_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_out(int low, int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50250,7 +51221,7 @@ overload_name: low_generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator_out(int low, int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50529,7 +51500,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randn(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50599,7 +51570,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50681,7 +51652,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50763,7 +51734,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50857,7 +51828,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50906,7 +51877,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -52180,7 +53151,7 @@ overload_name: self_int manual_kernel_registration: false category_override: '' - schema_string: aten::repeat_interleave.self_int(Tensor self, int repeats, int? dim=None, *, int? output_size=None) -> Tensor + schema_string: aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -52293,6 +53264,51 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _reshape_copy + operator_name: _reshape_copy + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _reshape_alias operator_name: _reshape_alias overload_name: '' @@ -53066,17 +54082,62 @@ type: at::Tensor inplace: false is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: _prelu_kernel + operator_name: _prelu_kernel + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: prelu_backward - operator_name: prelu_backward +- name: _prelu_kernel_backward + operator_name: _prelu_kernel_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) + schema_string: aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -53112,7 +54173,6 @@ type: const at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' @@ -53884,7 +54944,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select.int(Tensor(a) self, int dim, int index) -> Tensor(a) + schema_string: aten::select.int(Tensor(a) self, int dim, SymInt index) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -53940,7 +55000,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, int index) -> Tensor + schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -54005,7 +55065,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, int index) -> Tensor + schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -55688,7 +56748,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, int index) -> Tensor + schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -56417,7 +57477,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56475,7 +57535,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split.Tensor(Tensor(a -> *) self, int split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56533,7 +57593,7 @@ overload_name: sizes manual_kernel_registration: false category_override: '' - schema_string: aten::split.sizes(Tensor(a -> *) self, int[] split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56591,7 +57651,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56649,7 +57709,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes(Tensor(a -> *) self, int[] split_sizes, int dim=0) -> Tensor(a)[] + schema_string: aten::split_with_sizes(Tensor(a -> *) self, SymInt[] split_sizes, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -57106,6 +58166,52 @@ with_gil: false deprecated: false has_math_kernel: true +- name: squeeze + operator_name: squeeze + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) + arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: '' @@ -57186,6 +58292,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_ + operator_name: squeeze_ + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) + arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: self + type: at::Tensor & + inplace: true + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: dimname @@ -59391,7 +60542,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -59399,12 +60550,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59425,12 +60578,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59589,7 +60744,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59597,12 +60752,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59623,12 +60780,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59739,7 +60898,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59753,6 +60912,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59779,6 +60939,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59900,7 +61061,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -59915,12 +61076,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59941,12 +61104,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60144,7 +61309,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -60158,6 +61323,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60184,6 +61350,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60218,7 +61385,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -60239,6 +61406,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60265,6 +61433,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64030,7 +65199,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64038,12 +65207,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64064,12 +65235,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64189,7 +65362,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64204,12 +65377,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64230,12 +65405,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64433,7 +65610,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64447,6 +65624,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64473,6 +65651,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64507,7 +65686,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64528,6 +65707,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64554,6 +65734,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64718,7 +65899,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64726,12 +65907,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64752,12 +65935,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64868,7 +66053,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64882,6 +66067,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64908,6 +66094,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -65205,6 +66392,7 @@ type: const at::Scalar & method_of: - Type + - Tensor - namespace mode: native python_module: '' @@ -68219,23 +69407,47 @@ has_math_kernel: false - name: frobenius_norm operator_name: frobenius_norm - overload_name: '' + overload_name: dim manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm(Tensor self) -> Tensor + schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68252,13 +69464,20 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm +- name: frobenius_norm_out operator_name: frobenius_norm - overload_name: dim + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor + schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -68276,7 +69495,7 @@ is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -68295,6 +69514,60 @@ is_nullable: false name: keepdim type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nuclear_norm + operator_name: nuclear_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68311,12 +69584,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm_out - operator_name: frobenius_norm +- name: nuclear_norm_out + operator_name: nuclear_norm overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -68330,133 +69603,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - annotation: null default: false dynamic_type: bool is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm - operator_name: nuclear_norm - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm_out - operator_name: nuclear_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -69995,20 +71148,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: addmm_out - operator_name: addmm - overload_name: out +- name: _sparse_mm_reduce_impl + operator_name: _sparse_mm_reduce_impl + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_mm_reduce_impl(Tensor self, Tensor other, str reduce) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, c10::string_view) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -70017,28 +71180,164 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat1 + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _sparse_mm_reduce_impl_backward + operator_name: _sparse_mm_reduce_impl_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat2 + name: grad_out type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: beta - type: const at::Scalar & + name: weight + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: c10::string_view is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const at::Tensor &, ::std::array) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: addmm_out + operator_name: addmm + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat2 + type: const at::Tensor & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: beta + type: const at::Scalar & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -72152,7 +73451,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -72703,7 +74002,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -74066,20 +75365,64 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse(Tensor self) -> Tensor + schema_string: aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74101,20 +75444,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr(Tensor self) -> Tensor + schema_string: aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74136,20 +75491,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc(Tensor self) -> Tensor + schema_string: aten::to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74171,7 +75538,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74184,7 +75551,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74197,6 +75570,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74218,7 +75597,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74231,7 +75610,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74244,6 +75629,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74312,7 +75703,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1) -> Tensor + schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74346,7 +75737,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74380,6 +75777,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef method_of: - Type - namespace @@ -77882,7 +79285,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor) + schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -77929,7 +79332,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -77997,6 +79400,9 @@ - dynamic_type: at::Tensor name: result4 type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -78009,7 +79415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) + schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) arguments: - annotation: null dynamic_type: at::Tensor @@ -78041,6 +79447,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -78081,7 +79492,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -78113,6 +79524,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -80846,7 +82262,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pack_padded_sequence_backward(Tensor grad, int[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor + schema_string: aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -88647,180 +90063,125 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag - operator_name: diag - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag_backward - operator_name: diag_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag_backward(Tensor grad, SymInt[] input_sizes, int diagonal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: true -- name: cross_out - operator_name: cross - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: diag + operator_name: diag + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: cross_out + operator_name: cross + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false abstract: false device_guard: true with_gil: false @@ -89327,7 +90688,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::trace_backward(Tensor grad, int[] sizes) -> Tensor + schema_string: aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -93066,7 +94427,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::index_select_backward(Tensor grad, int[] self_sizes, int dim, Tensor index) -> Tensor + schema_string: aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94338,7 +95699,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, float label_smoothing=0.0) -> Tensor + schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94918,190 +96279,55 @@ with_gil: false deprecated: false has_math_kernel: true -- name: symeig_out - operator_name: symeig - overload_name: e +- name: svd_out + operator_name: svd + overload_name: U manual_kernel_registration: false category_override: '' - schema_string: aten::symeig.e(Tensor self, bool eigenvectors=False, bool upper=True, *, Tensor(a!) e, Tensor(b!) V) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) + schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor - field_name: eigenvalues + field_name: U is_nullable: false - name: e + name: U output: true type: at::Tensor & - allocate: true annotation: b! dynamic_type: at::Tensor - field_name: eigenvectors - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: eigenvalues + field_name: S is_nullable: false - name: e + name: S output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: c! dynamic_type: at::Tensor - field_name: eigenvectors + field_name: V is_nullable: false name: V output: true type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: e - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: eigenvectors - name: V - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: symeig - operator_name: symeig - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::symeig(Tensor self, bool eigenvectors=False, bool upper=True) -> (Tensor eigenvalues, Tensor eigenvectors) - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: eigenvalues - type: at::Tensor - - dynamic_type: at::Tensor - field_name: eigenvectors - name: eigenvectors_return - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _symeig_helper - operator_name: _symeig_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper(Tensor self, bool eigenvectors, bool upper) -> (Tensor, Tensor) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper + name: compute_uv type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -95109,100 +96335,16 @@ name: self type: const at::Tensor & - annotation: null + default: true dynamic_type: bool is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null + default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result0 - type: at::Tensor - - dynamic_type: at::Tensor - name: result1 - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: svd_out - operator_name: svd - overload_name: U - manual_kernel_registration: false - category_override: '' - schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: U - is_nullable: false - name: U - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: S - is_nullable: false - name: S - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - field_name: V - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv + name: compute_uv type: bool - allocate: true annotation: a! @@ -101246,45 +102388,48 @@ with_gil: false deprecated: false has_math_kernel: true -- name: minimum - operator_name: minimum - overload_name: '' +- name: max_out + operator_name: max + overload_name: unary_out manual_kernel_registration: false category_override: '' - schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor + schema_string: aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: other + name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Tensor & + name: out + output: true + type: at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result - type: at::Tensor + name: out + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -101292,20 +102437,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: minimum_out +- name: minimum operator_name: minimum - overload_name: out + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -101316,7 +102454,7 @@ is_nullable: false name: other type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101328,22 +102466,16 @@ is_nullable: false name: other type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type + - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -101351,12 +102483,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: min_out - operator_name: min +- name: minimum_out + operator_name: minimum overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101405,147 +102537,17 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: min + has_math_kernel: false +- name: min_out operator_name: min - overload_name: other - manual_kernel_registration: false - category_override: '' - schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile - operator_name: quantile - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile_out - operator_name: quantile overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101562,28 +102564,9 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101593,27 +102576,8 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - allocate: true annotation: a! dynamic_type: at::Tensor @@ -101637,12 +102601,58 @@ with_gil: false deprecated: false has_math_kernel: true +- name: min + operator_name: min + overload_name: other + manual_kernel_registration: false + category_override: '' + schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: quantile operator_name: quantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101650,10 +102660,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101673,7 +102683,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101681,10 +102691,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101723,10 +102733,10 @@ has_math_kernel: true - name: quantile_out operator_name: quantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101741,10 +102751,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101764,7 +102774,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101772,10 +102782,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101818,12 +102828,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile - operator_name: nanquantile - overload_name: '' +- name: quantile + operator_name: quantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101831,10 +102841,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101854,7 +102864,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101862,10 +102872,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101902,12 +102912,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile_out - operator_name: nanquantile - overload_name: out +- name: quantile_out + operator_name: quantile + overload_name: scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101922,10 +102932,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101945,7 +102955,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101953,10 +102963,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102001,10 +103011,10 @@ has_math_kernel: true - name: nanquantile operator_name: nanquantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -102012,10 +103022,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102035,7 +103045,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102043,10 +103053,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102085,10 +103095,10 @@ has_math_kernel: true - name: nanquantile_out operator_name: nanquantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -102103,10 +103113,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102126,7 +103136,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102134,10 +103144,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102180,27 +103190,102 @@ with_gil: false deprecated: false has_math_kernel: true -- name: sort_out - operator_name: sort - overload_name: values +- name: nanquantile + operator_name: nanquantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor - field_name: values is_nullable: false - name: values - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nanquantile_out + operator_name: nanquantile + overload_name: scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + arguments: - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & - annotation: null @@ -102209,18 +103294,30 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102228,31 +103325,34 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view is_nullable: false - name: values - output: true - type: at::Tensor & + kwarg_only: true + name: interpolation + type: c10::string_view - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & method_of: @@ -102262,26 +103362,117 @@ python_module: '' returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: out type: at::Tensor & inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: sort_out operator_name: sort - overload_name: values_stable + overload_name: values manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: sort_out + operator_name: sort + overload_name: values_stable + manual_kernel_registration: false + category_override: '' + schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) arguments: - allocate: true annotation: a! @@ -103814,7 +105005,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward(Tensor grad_in, int[] input_sizes, int dim, int size, int step) -> Tensor + schema_string: aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -105289,7 +106480,7 @@ overload_name: float_float manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float(float mean, float std, int[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::normal.float_float(float mean, float std, SymInt[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: double @@ -105393,7 +106584,7 @@ overload_name: float_float_out manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float_out(float mean, float std, int[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::normal.float_float_out(float mean, float std, SymInt[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -105992,48 +107183,121 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: List +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106051,12 +107315,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: List +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106064,91 +107328,150 @@ name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: - - annotation: a! + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: List +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106166,18 +107489,60 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: List +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add + operator_name: _foreach_add + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -106190,9 +107555,68 @@ kwarg_only: true name: alpha type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -106222,12 +107646,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul +- name: _foreach_sub + operator_name: _foreach_sub overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106239,7 +107663,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106251,6 +107682,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106267,12 +107705,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ +- name: _foreach_sub_ + operator_name: _foreach_sub_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106284,7 +107722,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106296,6 +107741,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106309,12 +107761,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div +- name: _foreach_mul + operator_name: _foreach_mul overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106354,12 +107806,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ +- name: _foreach_mul_ + operator_name: _foreach_mul_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106396,12 +107848,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: ScalarList +- name: _foreach_div + operator_name: _foreach_div + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106409,11 +107861,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106421,10 +107873,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106441,12 +107893,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: ScalarList +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106454,11 +107906,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106466,10 +107918,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106483,12 +107935,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: ScalarList +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106496,11 +107948,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106508,10 +107960,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106528,12 +107980,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: ScalarList +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106541,11 +107993,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106553,10 +108005,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106570,12 +108022,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div - overload_name: ScalarList +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106583,11 +108035,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106595,10 +108047,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106615,12 +108067,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ - overload_name: ScalarList +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106628,11 +108080,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106640,10 +108092,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106657,12 +108109,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul - overload_name: ScalarList +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106670,11 +108122,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106682,10 +108134,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106702,12 +108154,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ - overload_name: ScalarList +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106715,11 +108167,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106727,10 +108179,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106744,25 +108196,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_exp - operator_name: _foreach_exp - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList method_of: - Type - namespace @@ -106779,56 +108241,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_zero_ - operator_name: _foreach_zero_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_exp_ - operator_name: _foreach_exp_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () - arguments: + schema_order_cpp_signature: void (at::TensorList, at::TensorList) + schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList method_of: - Type @@ -106843,25 +108283,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt - operator_name: _foreach_sqrt - overload_name: '' +- name: _foreach_add + operator_name: _foreach_add + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106878,25 +108328,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt_ - operator_name: _foreach_sqrt_ - overload_name: '' +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106910,25 +108370,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs - operator_name: _foreach_abs - overload_name: '' +- name: _foreach_sub + operator_name: _foreach_sub + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106945,25 +108415,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs_ - operator_name: _foreach_abs_ - overload_name: '' +- name: _foreach_sub_ + operator_name: _foreach_sub_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106977,25 +108457,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos - operator_name: _foreach_acos - overload_name: '' +- name: _foreach_div + operator_name: _foreach_div + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107012,25 +108502,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos_ - operator_name: _foreach_acos_ - overload_name: '' +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107044,25 +108544,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin - operator_name: _foreach_asin - overload_name: '' +- name: _foreach_mul + operator_name: _foreach_mul + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107079,25 +108589,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin_ - operator_name: _foreach_asin_ - overload_name: '' +- name: _foreach_mul_ + operator_name: _foreach_mul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107111,25 +108631,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan - operator_name: _foreach_atan - overload_name: '' +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107146,25 +108676,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan_ - operator_name: _foreach_atan_ - overload_name: '' +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107178,25 +108718,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil - operator_name: _foreach_ceil - overload_name: '' +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107213,25 +108763,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil_ - operator_name: _foreach_ceil_ - overload_name: '' +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107245,25 +108805,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos - operator_name: _foreach_cos - overload_name: '' +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107280,25 +108850,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos_ - operator_name: _foreach_cos_ - overload_name: '' +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107312,25 +108892,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh - operator_name: _foreach_cosh - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107347,25 +108937,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh_ - operator_name: _foreach_cosh_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107379,12 +108979,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf - operator_name: _foreach_erf +- name: _foreach_exp + operator_name: _foreach_exp overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107414,12 +109014,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf_ - operator_name: _foreach_erf_ +- name: _foreach_zero_ + operator_name: _foreach_zero_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107446,47 +109046,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erfc - operator_name: _foreach_erfc - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_erfc_ - operator_name: _foreach_erfc_ +- name: _foreach_exp_ + operator_name: _foreach_exp_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107513,12 +109078,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1 - operator_name: _foreach_expm1 +- name: _foreach_sqrt + operator_name: _foreach_sqrt overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107548,12 +109113,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1_ - operator_name: _foreach_expm1_ +- name: _foreach_sqrt_ + operator_name: _foreach_sqrt_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107580,12 +109145,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor - operator_name: _foreach_floor +- name: _foreach_abs + operator_name: _foreach_abs overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107615,12 +109180,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor_ - operator_name: _foreach_floor_ +- name: _foreach_abs_ + operator_name: _foreach_abs_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107647,12 +109212,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log - operator_name: _foreach_log +- name: _foreach_acos + operator_name: _foreach_acos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107682,146 +109247,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log_ - operator_name: _foreach_log_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10 - operator_name: _foreach_log10 - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10_ - operator_name: _foreach_log10_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p - operator_name: _foreach_log1p - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p_ - operator_name: _foreach_log1p_ +- name: _foreach_acos_ + operator_name: _foreach_acos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107848,12 +109279,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2 - operator_name: _foreach_log2 +- name: _foreach_asin + operator_name: _foreach_asin overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107883,12 +109314,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2_ - operator_name: _foreach_log2_ +- name: _foreach_asin_ + operator_name: _foreach_asin_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107915,12 +109346,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg - operator_name: _foreach_neg +- name: _foreach_atan + operator_name: _foreach_atan overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107950,12 +109381,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg_ - operator_name: _foreach_neg_ +- name: _foreach_atan_ + operator_name: _foreach_atan_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107982,12 +109413,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan - operator_name: _foreach_tan +- name: _foreach_ceil + operator_name: _foreach_ceil overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108017,12 +109448,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan_ - operator_name: _foreach_tan_ +- name: _foreach_ceil_ + operator_name: _foreach_ceil_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108049,12 +109480,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh - operator_name: _foreach_tanh +- name: _foreach_cos + operator_name: _foreach_cos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108084,12 +109515,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh_ - operator_name: _foreach_tanh_ +- name: _foreach_cos_ + operator_name: _foreach_cos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108116,12 +109547,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin - operator_name: _foreach_sin +- name: _foreach_cosh + operator_name: _foreach_cosh overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108151,12 +109582,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin_ - operator_name: _foreach_sin_ +- name: _foreach_cosh_ + operator_name: _foreach_cosh_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108183,12 +109614,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh - operator_name: _foreach_sinh +- name: _foreach_erf + operator_name: _foreach_erf overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108218,12 +109649,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh_ - operator_name: _foreach_sinh_ +- name: _foreach_erf_ + operator_name: _foreach_erf_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108250,12 +109681,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round - operator_name: _foreach_round +- name: _foreach_erfc + operator_name: _foreach_erfc overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108285,12 +109716,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round_ - operator_name: _foreach_round_ +- name: _foreach_erfc_ + operator_name: _foreach_erfc_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108317,12 +109748,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma - operator_name: _foreach_lgamma +- name: _foreach_expm1 + operator_name: _foreach_expm1 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108352,12 +109783,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma_ - operator_name: _foreach_lgamma_ +- name: _foreach_expm1_ + operator_name: _foreach_expm1_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108384,12 +109815,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac - operator_name: _foreach_frac +- name: _foreach_floor + operator_name: _foreach_floor overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108419,12 +109850,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac_ - operator_name: _foreach_frac_ +- name: _foreach_floor_ + operator_name: _foreach_floor_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108451,12 +109882,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal - operator_name: _foreach_reciprocal +- name: _foreach_log + operator_name: _foreach_log overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108486,12 +109917,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal_ - operator_name: _foreach_reciprocal_ +- name: _foreach_log_ + operator_name: _foreach_log_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108518,12 +109949,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid - operator_name: _foreach_sigmoid +- name: _foreach_log10 + operator_name: _foreach_log10 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108553,12 +109984,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid_ - operator_name: _foreach_sigmoid_ +- name: _foreach_log10_ + operator_name: _foreach_log10_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108585,12 +110016,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc - operator_name: _foreach_trunc +- name: _foreach_log1p + operator_name: _foreach_log1p overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108620,12 +110051,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc_ - operator_name: _foreach_trunc_ +- name: _foreach_log1p_ + operator_name: _foreach_log1p_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108652,57 +110083,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: Scalar +- name: _foreach_log2 + operator_name: _foreach_log2 + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_log2_ + operator_name: _foreach_log2_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg + operator_name: _foreach_neg + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg_ + operator_name: _foreach_neg_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan + operator_name: _foreach_tan + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan_ + operator_name: _foreach_tan_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108716,57 +110284,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: Scalar +- name: _foreach_tanh + operator_name: _foreach_tanh + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tanh_ + operator_name: _foreach_tanh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin + operator_name: _foreach_sin + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin_ + operator_name: _foreach_sin_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh + operator_name: _foreach_sinh + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh_ + operator_name: _foreach_sinh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108780,55 +110485,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: ScalarList +- name: _foreach_round + operator_name: _foreach_round + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_round_ + operator_name: _foreach_round_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma + operator_name: _foreach_lgamma + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma_ + operator_name: _foreach_lgamma_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac + operator_name: _foreach_frac + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac_ + operator_name: _foreach_frac_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108842,55 +110686,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: ScalarList +- name: _foreach_reciprocal + operator_name: _foreach_reciprocal + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_reciprocal_ + operator_name: _foreach_reciprocal_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid + operator_name: _foreach_sigmoid + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid_ + operator_name: _foreach_sigmoid_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc + operator_name: _foreach_trunc + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc_ + operator_name: _foreach_trunc_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108904,14 +110887,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108932,9 +110915,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108960,25 +110943,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108999,9 +110979,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109027,25 +111007,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109065,9 +111042,9 @@ is_nullable: false name: scalars type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109092,25 +111069,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul - overload_name: ScalarList +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109126,13 +111100,13 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109148,34 +111122,31 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef + type: const at::Tensor & method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum - operator_name: _foreach_maximum - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109183,11 +111154,21 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109195,30 +111176,37 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_ - operator_name: _foreach_maximum_ - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -109228,9 +111216,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -109240,8 +111238,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & method_of: - Type - namespace @@ -109255,12 +111263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum - operator_name: _foreach_minimum - overload_name: List +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109270,9 +111278,20 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109282,8 +111301,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace @@ -109300,14 +111330,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_ - operator_name: _foreach_minimum_ - overload_name: List +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109315,11 +111345,22 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109327,27 +111368,41 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm - operator_name: _foreach_norm - overload_name: Scalar +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109355,12 +111410,21 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109368,11 +111432,20 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -109389,41 +111462,497 @@ with_gil: false deprecated: false has_math_kernel: false -- name: bucketize - operator_name: bucketize +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + schema_string: aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: self - type: const at::Tensor & + type: at::TensorList - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: boundaries - type: const at::Tensor & + name: tensor1 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::TensorList is_nullable: false - kwarg_only: true - name: out_int32 - type: bool + name: tensor2 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: right - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: ScalarList + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_norm + operator_name: _foreach_norm + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: bucketize + operator_name: bucketize + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: boundaries + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: out_int32 + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: right + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & @@ -109723,41 +112252,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Tensor_out @@ -111450,7 +113944,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -111545,7 +114039,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111626,7 +114120,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111707,7 +114201,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -111813,7 +114307,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -111893,7 +114387,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112002,7 +114496,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112097,7 +114591,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112192,7 +114686,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112273,7 +114767,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -112379,7 +114873,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -112459,7 +114953,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112568,7 +115062,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -116944,7 +119438,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -117005,7 +119499,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -117052,7 +119546,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::_adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120595,7 +123089,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120656,7 +123150,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120703,7 +123197,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120774,7 +123268,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120831,7 +123325,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120892,7 +123386,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120939,7 +123433,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121010,7 +123504,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121067,7 +123561,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121128,7 +123622,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121175,7 +123669,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121246,7 +123740,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121303,7 +123797,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121364,7 +123858,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121411,7 +123905,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121482,7 +123976,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121539,7 +124033,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121600,7 +124094,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121647,7 +124141,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121718,7 +124212,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121775,7 +124269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121836,7 +124330,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121883,7 +124377,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121954,7 +124448,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122011,7 +124505,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_circular(Tensor self, int[] pad) -> Tensor + schema_string: aten::_pad_circular(Tensor self, SymInt[] pad) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122056,7 +124550,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_enum(Tensor self, int[] pad, int mode, float? value=None) -> Tensor + schema_string: aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122123,7 +124617,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::pad(Tensor self, int[] pad, str mode="constant", float? value=None) -> Tensor + schema_string: aten::pad(Tensor self, SymInt[] pad, str mode="constant", float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122247,86 +124741,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_linear1d_backward - operator_name: upsample_linear1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_linear1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_bilinear2d operator_name: upsample_bilinear2d overload_name: vec @@ -122387,33 +124806,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bilinear2d_backward - operator_name: upsample_bilinear2d_backward + has_math_kernel: true +- name: _upsample_bilinear2d_aa + operator_name: _upsample_bilinear2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122424,23 +124838,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122462,17 +124871,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa - operator_name: _upsample_bilinear2d_aa + has_math_kernel: true +- name: upsample_trilinear3d + operator_name: upsample_trilinear3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122527,33 +124936,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward - operator_name: _upsample_bilinear2d_aa_backward + has_math_kernel: true +- name: upsample_bicubic2d + operator_name: upsample_bicubic2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122564,23 +124968,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122602,17 +125001,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d - operator_name: upsample_trilinear3d + has_math_kernel: true +- name: _upsample_bicubic2d_aa + operator_name: _upsample_bicubic2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122667,65 +125066,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d_backward - operator_name: upsample_trilinear3d_backward + has_math_kernel: true +- name: upsample_nearest1d + operator_name: upsample_nearest1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122742,17 +125121,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d - operator_name: upsample_bicubic2d + has_math_kernel: true +- name: _upsample_nearest_exact1d + operator_name: _upsample_nearest_exact1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122764,17 +125143,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122786,11 +125160,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122807,65 +125176,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d_backward - operator_name: upsample_bicubic2d_backward + has_math_kernel: true +- name: upsample_nearest2d + operator_name: upsample_nearest2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122882,17 +125231,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa - operator_name: _upsample_bicubic2d_aa + has_math_kernel: true +- name: _upsample_nearest_exact2d + operator_name: _upsample_nearest_exact2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122904,17 +125253,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122926,11 +125270,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122947,65 +125286,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward - operator_name: _upsample_bicubic2d_aa_backward + has_math_kernel: true +- name: upsample_nearest3d + operator_name: upsample_nearest3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -123022,17 +125341,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_nearest1d - operator_name: upsample_nearest1d + has_math_kernel: true +- name: _upsample_nearest_exact3d + operator_name: _upsample_nearest_exact3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -123077,676 +125396,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d - operator_name: _upsample_nearest_exact1d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest1d_backward - operator_name: upsample_nearest1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d_backward - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d - operator_name: upsample_nearest2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d - operator_name: _upsample_nearest_exact2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d_backward - operator_name: upsample_nearest2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d_backward - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d - operator_name: upsample_nearest3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d - operator_name: _upsample_nearest_exact3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d_backward - operator_name: upsample_nearest3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d_backward - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_linear1d_out operator_name: upsample_linear1d overload_name: out @@ -128360,7 +130014,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128499,7 +130153,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -128624,7 +130278,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128763,7 +130417,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129541,7 +131195,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129658,7 +131312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation) -> Tensor + schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129761,7 +131415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation) -> Tensor + schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129864,7 +131518,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129975,7 +131629,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0) -> Tensor + schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130072,7 +131726,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, *, Tensor(a!) output) -> Tensor(a!) + schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -130177,7 +131831,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding) -> Tensor + schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130268,7 +131922,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130379,7 +132033,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -147845,7 +149499,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int(Tensor self, int dim, int index) -> Tensor + schema_string: aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -148018,7 +149672,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split_copy.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::split_copy.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148075,7 +149729,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes_copy(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148207,6 +149861,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_copy + operator_name: squeeze_copy + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_copy.dims(Tensor self, int[] dim) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: t_copy operator_name: t_copy overload_name: '' @@ -148669,221 +150368,32 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: dtype - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy - operator_name: unfold_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: alias_copy - operator_name: alias_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::alias_copy(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _fw_primal_copy_out - operator_name: _fw_primal_copy - overload_name: out +- name: unbind_copy_out + operator_name: unbind_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -148891,26 +150401,24 @@ name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -148918,117 +150426,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _make_dual_copy_out - operator_name: _make_dual_copy - overload_name: out +- name: split_copy_out + operator_name: split_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_copy.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: tangent - type: const at::Tensor & + name: split_size + type: int64_t - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: tangent + name: self type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: level + name: split_size type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_as_real_copy_out - operator_name: view_as_real_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149036,146 +150494,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_as_complex_copy_out - operator_name: view_as_complex_copy +- name: split_with_sizes_copy_out + operator_name: split_with_sizes_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _conj_copy_out - operator_name: _conj_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: out - output: true - type: at::Tensor & + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _neg_view_copy_out - operator_name: _neg_view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149183,20 +150562,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: as_strided_copy_out - operator_name: as_strided_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -149207,18 +150579,7 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149230,24 +150591,6 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149255,8 +150598,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149264,31 +150607,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_broadcast_to_copy_out - operator_name: _sparse_broadcast_to_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: dtype manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::ScalarType is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: dtype + type: at::ScalarType + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149296,17 +150632,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::ScalarType is_nullable: false - name: out - output: true - type: at::Tensor & + name: dtype + type: at::ScalarType method_of: - Type - namespace @@ -149314,8 +150643,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149323,44 +150652,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: diagonal_copy_out - operator_name: diagonal_copy - overload_name: out +- name: unfold_copy + operator_name: unfold_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149368,30 +150687,20 @@ name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149399,8 +150708,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149408,63 +150717,25 @@ with_gil: false deprecated: false has_math_kernel: false -- name: expand_copy_out - operator_name: expand_copy - overload_name: out +- name: alias_copy + operator_name: alias_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy(Tensor self) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149472,8 +150743,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149481,31 +150752,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: permute_copy_out - operator_name: permute_copy - overload_name: out +- name: to_padded_tensor + operator_name: to_padded_tensor + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: double is_nullable: false - name: dims - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149513,26 +150783,25 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dims - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: out - output: true - type: at::Tensor & + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef method_of: - Type - - namespace + - Tensor mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149540,36 +150809,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _reshape_alias_copy_out - operator_name: _reshape_alias_copy - overload_name: out +- name: _nested_tensor_softmax_with_shape + operator_name: _nested_tensor_softmax_with_shape + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: stride - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: query + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149577,22 +150834,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: query + type: const at::Tensor & method_of: - Type - namespace @@ -149600,8 +150845,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149609,449 +150854,219 @@ with_gil: false deprecated: false has_math_kernel: false -- name: select_copy_out - operator_name: select_copy - overload_name: int_out +- name: _transformer_encoder_layer_fwd + operator_name: _transformer_encoder_layer_fwd + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int_out(Tensor self, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: index + name: num_heads type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: index - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: detach_copy_out - operator_name: detach_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: qkv_bias + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + - annotation: null + dynamic_type: bool + is_nullable: false + name: use_gelu + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: norm_first + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_1 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: slice_copy_out - operator_name: slice_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_1 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: start - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: end - type: c10::optional + name: ffn_weight_1 + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_bias_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_weight_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t + name: ffn_bias_2 + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: start - type: c10::optional + name: mask + type: const c10::optional & - annotation: null default: c10::nullopt dynamic_type: int64_t is_nullable: true - name: end + name: mask_type type: c10::optional - - annotation: null - default: 1 - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_copy_out - operator_name: split_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_copy.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: split_size + name: embed_dim type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim + name: num_heads type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: split_size - type: int64_t - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_with_sizes_copy_out - operator_name: split_with_sizes_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_with_sizes_copy.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: split_sizes - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) - schema_order_arguments: + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: bool is_nullable: false - name: split_sizes - type: at::IntArrayRef + name: use_gelu + type: bool - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList + name: norm_first + type: bool + - annotation: null + dynamic_type: double is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: eps + type: double + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_1 type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_2 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: dim_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_2 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: ffn_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_1 type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_2 type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150059,8 +151074,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150068,412 +151083,153 @@ with_gil: false deprecated: false has_math_kernel: false -- name: t_copy_out - operator_name: t_copy - overload_name: out +- name: _native_multi_head_attention + operator_name: _native_multi_head_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: transpose_copy_out - operator_name: transpose_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim0 + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: dim1 + name: num_head type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim0 - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim1 - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unsqueeze_copy_out - operator_name: unsqueeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + name: qkv_bias + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _indices_copy_out - operator_name: _indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: need_weights + type: bool - annotation: null - dynamic_type: at::Tensor + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _values_copy_out - operator_name: _values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: indices_copy_out - operator_name: indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + - annotation: null + dynamic_type: int64_t is_nullable: false - name: out - output: true - type: at::Tensor & + name: embed_dim + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: num_head + type: int64_t - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: values_copy_out - operator_name: values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: crow_indices_copy_out - operator_name: crow_indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_weights + type: bool + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150481,8 +151237,11 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150490,409 +151249,287 @@ with_gil: false deprecated: false has_math_kernel: false -- name: col_indices_copy_out - operator_name: col_indices_copy - overload_name: out +- name: scaled_dot_product_attention + operator_name: scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unbind_copy_out - operator_name: unbind_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: self - type: const at::Tensor & + name: dropout_p + type: double - annotation: null - default: 0 - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) + name: is_causal + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) - schema_order_arguments: - - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: dtype_out + has_math_kernel: true +- name: _scaled_dot_product_attention + operator_name: _scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy_out - operator_name: unfold_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: int64_t + default: 0.0 + dynamic_type: double is_nullable: false - name: dimension - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: size - type: int64_t + name: need_attn_weights + type: bool - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dimension - type: int64_t + name: value + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_attn_weights + type: bool + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: alias_copy_out - operator_name: alias_copy - overload_name: out + has_math_kernel: true +- name: _fused_sdp_choice + operator_name: _fused_sdp_choice + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fused_sdp_choice(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> int arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: to_padded_tensor - operator_name: to_padded_tensor - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: int64_t (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - - dynamic_type: at::Tensor + - dynamic_type: int64_t name: result - type: at::Tensor + type: int64_t inplace: false is_factory_method: false abstract: true @@ -150900,35 +151537,93 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_softmax_with_shape - operator_name: _nested_tensor_softmax_with_shape +- name: _scaled_dot_product_attention_math + operator_name: _scaled_dot_product_attention_math overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor + schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: query + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, const c10::optional &) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: query type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & method_of: - Type - namespace @@ -150936,72 +151631,134 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _nested_tensor_layer_norm - operator_name: _nested_tensor_layer_norm + has_math_kernel: true +- name: _scaled_dot_product_flash_attention + operator_name: _scaled_dot_product_flash_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_layer_norm(Tensor self, Tensor? weight, Tensor? bias, float eps) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention(Tensor query, Tensor key, Tensor value, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False) -> (Tensor ouput, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, int philox_seed, int philox_offset, Tensor debug_attn_mask) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const c10::optional &, const c10::optional &, double) + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result + field_name: ouput + name: ouput + type: at::Tensor + - dynamic_type: at::Tensor + field_name: logsumexp + name: logsumexp + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_q + name: cum_seq_q + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_k + name: cum_seq_k + type: at::Tensor + - dynamic_type: int64_t + field_name: max_q + name: max_q + type: int64_t + - dynamic_type: int64_t + field_name: max_k + name: max_k + type: int64_t + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151010,219 +151767,353 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _transformer_encoder_layer_fwd - operator_name: _transformer_encoder_layer_fwd +- name: _scaled_dot_product_flash_attention_backward + operator_name: _scaled_dot_product_flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: src + name: grad_out type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: embed_dim - type: int64_t + name: query + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: num_heads - type: int64_t + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: use_gelu - type: bool + name: cum_seq_k + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: norm_first - type: bool + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: grad_out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: cum_seq_q type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: cum_seq_k type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t - annotation: null - default: c10::nullopt dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) - schema_order_arguments: + is_nullable: false + name: max_k + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: src - type: const at::Tensor & + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: philox_seed type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_heads + name: philox_offset type: int64_t + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: grad_query + name: grad_query + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_key + name: grad_key + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_value + name: grad_value + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention + operator_name: _scaled_dot_product_efficient_attention + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention(Tensor query, Tensor key, Tensor value, bool compute_log_sumexp, bool is_causal=False) -> (Tensor, Tensor) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: compute_log_sumexp + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value type: const at::Tensor & - annotation: null dynamic_type: bool is_nullable: false - name: use_gelu + name: compute_log_sumexp type: bool - annotation: null + default: false dynamic_type: bool is_nullable: false - name: norm_first + name: is_causal type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention_backward + operator_name: _scaled_dot_product_efficient_attention_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) + arguments: - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: eps - type: double + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: logsumexp type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: grad_out_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: key type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional + dynamic_type: at::Tensor + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool method_of: - Type - namespace @@ -151230,7 +152121,13 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 type: at::Tensor inplace: false is_factory_method: false @@ -151239,12 +152136,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _native_multi_head_attention - operator_name: _native_multi_head_attention +- name: _chunk_grad_outputs_efficient_attention + operator_name: _chunk_grad_outputs_efficient_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) + schema_string: aten::_chunk_grad_outputs_efficient_attention(Tensor query, Tensor key, Tensor value, bool is_causal=False) -> bool arguments: - annotation: null dynamic_type: at::Tensor @@ -151262,61 +152159,57 @@ name: value type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: embed_dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: num_head - type: int64_t - - annotation: null - dynamic_type: at::Tensor + default: false + dynamic_type: bool is_nullable: false - name: qkv_weight - type: const at::Tensor & + name: is_causal + type: bool + schema_order_cpp_signature: bool (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: value type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & - - annotation: null - default: true + default: false dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: average_attn_weights + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: bool + name: result type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) - schema_order_arguments: + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _flash_attention_forward + operator_name: _flash_attention_forward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151332,60 +152225,93 @@ is_nullable: false name: value type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: max_q type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_head + name: max_k type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double - annotation: null - default: true dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - annotation: null - default: true dynamic_type: bool is_nullable: false - name: average_attn_weights + name: return_debug_mask type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional method_of: - Type - namespace @@ -151393,10 +152319,24 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result0 + field_name: output + name: output type: at::Tensor - dynamic_type: at::Tensor - name: result1 + field_name: softmax_logsumexp + name: softmax_logsumexp + type: at::Tensor + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151405,13 +152345,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention - operator_name: _scaled_dot_product_attention +- name: _flash_attention_backward + operator_name: _flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151428,31 +152373,62 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151469,34 +152445,60 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t method_of: - Type - namespace mode: native - python_module: nn + python_module: '' returns: - dynamic_type: at::Tensor name: result0 @@ -151504,19 +152506,22 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: _scaled_dot_product_attention_forward - operator_name: _scaled_dot_product_attention_forward + has_math_kernel: false +- name: _efficient_attention_forward + operator_name: _efficient_attention_forward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, int? max_seqlen_q, bool compute_log_sumexp=False, bool causal=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -151534,30 +152539,33 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, c10::optional, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -151575,28 +152583,31 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool method_of: - Type @@ -151617,13 +152628,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention_math - operator_name: _scaled_dot_product_attention_math +- name: _efficient_attention_backward + operator_name: _efficient_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151640,31 +152656,34 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151681,28 +152700,26 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool method_of: - Type @@ -151716,13 +152733,16 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: _triton_scaled_dot_attention operator_name: _triton_scaled_dot_attention overload_name: '' @@ -152001,121 +153021,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _flash_scaled_dot_product_attention - operator_name: _flash_scaled_dot_product_attention - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_flash_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_decoder_only_layer_fwd operator_name: _transformer_decoder_only_layer_fwd overload_name: '' @@ -157482,6 +158387,200 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_ + operator_name: _fused_adamw_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _new_zeros_with_same_feature_meta_out operator_name: _new_zeros_with_same_feature_meta overload_name: out @@ -159780,7 +160879,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd.out(Tensor self, int[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159851,7 +160950,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159980,7 +161079,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) arguments: - allocate: true annotation: a! @@ -160465,7 +161564,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -162568,6 +163667,126 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _ctc_loss_out + operator_name: _ctc_loss + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _ctc_loss_backward_out operator_name: _ctc_loss_backward overload_name: out @@ -163008,7 +164227,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding.out(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163103,7 +164322,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163720,7 +164939,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -168009,127 +169228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _mps_max_pool2d_out - operator_name: _mps_max_pool2d +- name: max_pool2d_backward_out + operator_name: max_pool2d_backward overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mps_max_pool2d_backward_out - operator_name: mps_max_pool2d_backward - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169214,107 +170318,825 @@ name: out2 output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_convolution_out + operator_name: mkldnn_convolution + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_out + operator_name: mkldnn_rnn_layer + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out3 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward_out + operator_name: mkldnn_rnn_layer_backward + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: out4 + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & + - allocate: true + annotation: g! + dynamic_type: at::Tensor + is_nullable: false + name: out6 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! dynamic_type: at::Tensor is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array + name: out3 + output: true + type: at::Tensor & - allocate: true - annotation: a! + annotation: e! dynamic_type: at::Tensor is_nullable: false - name: out0 + name: out4 output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: f! dynamic_type: at::Tensor is_nullable: false - name: out1 + name: out5 output: true type: at::Tensor & - allocate: true - annotation: c! + annotation: g! dynamic_type: at::Tensor is_nullable: false - name: out2 + name: out6 output: true type: at::Tensor & method_of: @@ -169332,114 +171154,17 @@ - dynamic_type: at::Tensor name: out2 type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_convolution_out - operator_name: mkldnn_convolution - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out3 type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out4 type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - dynamic_type: at::Tensor - name: out + name: out5 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out6 type: at::Tensor & inplace: false is_factory_method: false @@ -169759,7 +171484,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169888,7 +171613,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170027,7 +171752,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170745,12 +172470,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_mask_helper_out - operator_name: _sparse_mask_helper - overload_name: out +- name: mul_out + operator_name: mul + overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_mask_helper.out(Tensor t, Tensor mask_indices, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170762,25 +172487,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + name: other + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & + name: other + type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -170804,49 +172529,95 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mul_out - operator_name: mul - overload_name: Scalar_out +- name: _native_batch_norm_legit_functional + operator_name: _native_batch_norm_legit_functional + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: running_mean type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: input type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - - allocate: true - annotation: a! + name: running_mean + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double method_of: - Type - namespace @@ -170854,8 +172625,22 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_mean_out + name: running_mean_out + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_var_out + name: running_var_out + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -171774,7 +173559,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172647,7 +174432,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172708,7 +174493,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173000,7 +174785,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173061,7 +174846,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173373,179 +175158,37 @@ with_gil: false deprecated: false has_math_kernel: false -- name: relu_out - operator_name: relu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_out - operator_name: prelu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::prelu.out(Tensor self, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_backward_out - operator_name: prelu_backward +- name: relu_out + operator_name: relu overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward.out(Tensor grad_output, Tensor self, Tensor weight, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & method_of: @@ -173555,10 +175198,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -173572,7 +175212,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173918,7 +175558,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -174183,7 +175823,7 @@ overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174251,7 +175891,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174382,7 +176022,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -174404,12 +176044,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -174430,12 +176072,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176060,7 +177704,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -176082,12 +177726,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176108,12 +177754,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -178691,7 +180339,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179528,7 +181176,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179542,13 +181190,57 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179577,7 +181269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179591,13 +181283,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179626,7 +181330,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csc.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179640,13 +181344,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179675,7 +181391,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179695,7 +181411,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179708,6 +181430,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179736,7 +181464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179756,7 +181484,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179769,6 +181503,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179858,7 +181598,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179899,7 +181639,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179933,6 +181679,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -181843,7 +183595,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) + schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!)) arguments: - allocate: true annotation: a! @@ -181880,6 +183632,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -181925,7 +183684,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182007,6 +183766,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & method_of: - Type - namespace @@ -182028,6 +183794,9 @@ - dynamic_type: at::Tensor name: out4 type: at::Tensor & + - dynamic_type: at::Tensor + name: out5 + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -182040,7 +183809,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () + schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () arguments: - allocate: true annotation: a! @@ -182093,6 +183862,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -182133,7 +183907,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) + schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182165,6 +183939,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -185866,92 +187645,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _symeig_helper_out - operator_name: _symeig_helper - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper.out(Tensor self, bool eigenvectors, bool upper, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _cholesky_solve_helper_out operator_name: _cholesky_solve_helper overload_name: out @@ -186531,7 +188224,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward.out(Tensor grad_in, int[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -187072,12 +188765,544 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub - overload_name: Scalar_out +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum_out + operator_name: _foreach_maximum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum_out + operator_name: _foreach_minimum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187092,11 +189317,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187104,10 +189329,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187128,12 +189353,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul - overload_name: Scalar_out +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187148,11 +189373,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187160,10 +189385,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187184,12 +189409,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div - overload_name: Scalar_out +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187204,11 +189429,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187216,10 +189441,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187240,12 +189465,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187264,14 +189489,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187283,13 +189501,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187310,12 +189521,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187334,14 +189545,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187353,13 +189557,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187380,12 +189577,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187436,12 +189633,124 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_div_out operator_name: _foreach_div - overload_name: List_out + overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187455,23 +189764,79 @@ is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187492,12 +189857,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187548,12 +189913,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187604,12 +189969,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187660,12 +190025,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189318,6 +191683,82 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_addcdiv_out + operator_name: _foreach_addcdiv + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_addcmul_out operator_name: _foreach_addcmul overload_name: ScalarList_out @@ -189394,12 +191835,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_out - operator_name: _foreach_maximum - overload_name: List_out +- name: _foreach_addcmul_out + operator_name: _foreach_addcmul + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189416,9 +191857,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189428,8 +191879,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -189450,12 +191911,70 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_out - operator_name: _foreach_minimum +- name: _foreach_norm_out + operator_name: _foreach_norm + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189472,9 +191991,14 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189484,7 +192008,12 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights type: at::TensorList - allocate: true annotation: a! @@ -189506,12 +192035,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm_out - operator_name: _foreach_norm +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189526,12 +192055,16 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189539,10 +192072,14 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - allocate: true annotation: a! @@ -189651,55 +192188,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op_out - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Scalar_out @@ -190345,7 +192833,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190460,12 +192948,161 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_out - operator_name: upsample_linear1d - overload_name: vec_out +- name: _slow_conv2d_backward_out + operator_name: _slow_conv2d_backward + overload_name: output_mask_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: conv_depthwise3d_out + operator_name: conv_depthwise3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190477,45 +193114,551 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: bias + type: const c10::optional & - annotation: null - dynamic_type: bool + dynamic_type: at::IntArrayRef is_nullable: false - name: align_corners - type: bool + name: stride + size: 3 + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated2d_out + operator_name: slow_conv_dilated2d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated3d_out + operator_name: slow_conv_dilated3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: isinf_out + operator_name: isinf + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: linalg_matrix_exp_out + operator_name: linalg_matrix_exp + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_intlist_out + operator_name: _test_optional_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_filled_intlist_out + operator_name: _test_optional_filled_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true - name: output_size + name: addends + size: 2 type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: align_corners - type: bool + name: values + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef is_nullable: true - name: scale_factors - type: c10::optional> + name: addends + size: 2 + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190539,12 +193682,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_backward_out - operator_name: upsample_linear1d_backward - overload_name: vec_out +- name: _test_optional_floatlist_out + operator_name: _test_optional_floatlist + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190556,54 +193699,24 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - allocate: true annotation: a! @@ -190628,12 +193741,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_out - operator_name: upsample_bilinear2d - overload_name: vec_out +- name: _test_warn_in_autograd_out + operator_name: _test_warn_in_autograd + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190645,45 +193758,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190707,12 +193790,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_backward_out - operator_name: upsample_bilinear2d_backward - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_out + operator_name: _test_autograd_multiple_dispatch + overload_name: fullcoverage_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190724,55 +193807,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190796,12 +193839,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_out - operator_name: _upsample_bilinear2d_aa - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_view_copy_out + operator_name: _test_autograd_multiple_dispatch_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190813,45 +193856,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190875,12 +193888,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward_out - operator_name: _upsample_bilinear2d_aa_backward - overload_name: vec_out +- name: segment_reduce_out + operator_name: segment_reduce + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190892,55 +193905,109 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190964,12 +194031,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_out - operator_name: upsample_trilinear3d - overload_name: vec_out +- name: _segment_reduce_backward_out + operator_name: _segment_reduce_backward + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190981,45 +194048,101 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191043,12 +194166,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_backward_out - operator_name: upsample_trilinear3d_backward - overload_name: vec_out +- name: _nested_tensor_from_tensor_list_out + operator_name: _nested_tensor_from_tensor_list + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191058,57 +194181,65 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: pin_memory + type: c10::optional + schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> + name: pin_memory + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191132,12 +194263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_out - operator_name: upsample_bicubic2d - overload_name: vec_out +- name: _fw_primal_copy_out + operator_name: _fw_primal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191149,45 +194280,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191211,12 +194322,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_backward_out - operator_name: upsample_bicubic2d_backward - overload_name: vec_out +- name: _make_dual_copy_out + operator_name: _make_dual_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191228,55 +194339,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191300,12 +194391,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_out - operator_name: _upsample_bicubic2d_aa - overload_name: vec_out +- name: view_as_real_copy_out + operator_name: view_as_real_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191317,45 +194408,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191379,12 +194440,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward_out - operator_name: _upsample_bicubic2d_aa_backward - overload_name: vec_out +- name: view_as_complex_copy_out + operator_name: view_as_complex_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191396,55 +194457,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191468,12 +194489,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_out - operator_name: upsample_nearest1d - overload_name: vec_out +- name: _conj_copy_out + operator_name: _conj_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191485,35 +194506,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191537,12 +194538,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_out - operator_name: _upsample_nearest_exact1d - overload_name: vec_out +- name: _neg_view_copy_out + operator_name: _neg_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191554,35 +194555,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191606,12 +194587,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_backward_out - operator_name: upsample_nearest1d_backward - overload_name: vec_out +- name: as_strided_copy_out + operator_name: as_strided_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191623,45 +194604,47 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: storage_offset + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: storage_offset + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191685,12 +194668,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_backward_out - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec_out +- name: _sparse_broadcast_to_copy_out + operator_name: _sparse_broadcast_to_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191702,45 +194685,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191764,12 +194727,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_out - operator_name: upsample_nearest2d - overload_name: vec_out +- name: diagonal_copy_out + operator_name: diagonal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191781,35 +194744,51 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191833,12 +194812,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_out - operator_name: _upsample_nearest_exact2d - overload_name: vec_out +- name: expand_copy_out + operator_name: expand_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191850,35 +194829,39 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191902,12 +194885,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_backward_out - operator_name: upsample_nearest2d_backward - overload_name: vec_out +- name: permute_copy_out + operator_name: permute_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191919,45 +194902,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191981,12 +194944,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_backward_out - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec_out +- name: _reshape_alias_copy_out + operator_name: _reshape_alias_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191998,45 +194961,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192060,12 +195013,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_out - operator_name: upsample_nearest3d - overload_name: vec_out +- name: select_copy_out + operator_name: select_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192077,35 +195030,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: self + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192129,12 +195082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_out - operator_name: _upsample_nearest_exact3d - overload_name: vec_out +- name: detach_copy_out + operator_name: detach_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192146,35 +195099,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192198,12 +195131,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_backward_out - operator_name: upsample_nearest3d_backward - overload_name: vec_out +- name: slice_copy_out + operator_name: slice_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192215,45 +195148,63 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192277,12 +195228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_backward_out - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192294,45 +195245,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192356,131 +195277,47 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _slow_conv2d_backward_out - operator_name: _slow_conv2d_backward - overload_name: output_mask_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dim_out manual_kernel_registration: false category_override: '' - schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & method_of: @@ -192490,13 +195327,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out2 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -192505,12 +195336,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: conv_depthwise3d_out - operator_name: conv_depthwise3d - overload_name: out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dims_out manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.dims_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192524,80 +195355,22 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - allocate: true annotation: a! @@ -192622,12 +195395,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated2d_out - operator_name: slow_conv_dilated2d +- name: t_copy_out + operator_name: t_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192641,89 +195414,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192747,12 +195444,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated3d_out - operator_name: slow_conv_dilated3d - overload_name: out +- name: transpose_copy_out + operator_name: transpose_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192767,44 +195464,16 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: dim1 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -192812,43 +195481,15 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef + name: dim1 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192872,12 +195513,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: isinf_out - operator_name: isinf +- name: unsqueeze_copy_out + operator_name: unsqueeze_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192891,13 +195532,23 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192921,12 +195572,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: linalg_matrix_exp_out - operator_name: linalg_matrix_exp +- name: _indices_copy_out + operator_name: _indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192970,12 +195621,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_intlist_out - operator_name: _test_optional_intlist +- name: _values_copy_out + operator_name: _values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192987,25 +195638,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193029,12 +195670,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_filled_intlist_out - operator_name: _test_optional_filled_intlist +- name: indices_copy_out + operator_name: indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193046,27 +195687,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193090,12 +195719,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_floatlist_out - operator_name: _test_optional_floatlist +- name: values_copy_out + operator_name: values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193107,25 +195736,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193149,12 +195768,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_warn_in_autograd_out - operator_name: _test_warn_in_autograd +- name: crow_indices_copy_out + operator_name: crow_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193198,12 +195817,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_out - operator_name: _test_autograd_multiple_dispatch - overload_name: fullcoverage_out +- name: col_indices_copy_out + operator_name: col_indices_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193247,12 +195866,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_view_copy_out - operator_name: _test_autograd_multiple_dispatch_view_copy +- name: ccol_indices_copy_out + operator_name: ccol_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193296,12 +195915,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: segment_reduce_out - operator_name: segment_reduce +- name: row_indices_copy_out + operator_name: row_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193313,109 +195932,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193439,12 +195964,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _segment_reduce_backward_out - operator_name: _segment_reduce_backward +- name: view_copy_out + operator_name: view_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193456,101 +195981,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & + name: size + type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193574,12 +196023,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_from_tensor_list_out - operator_name: _nested_tensor_from_tensor_list - overload_name: out +- name: view_copy_out + operator_name: view_copy + overload_name: dtype_out manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193589,65 +196038,27 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional - schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) + type: at::ScalarType + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional + type: at::ScalarType - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193671,12 +196082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: ccol_indices_copy_out - operator_name: ccol_indices_copy +- name: unfold_copy_out + operator_name: unfold_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193690,13 +196101,43 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193720,12 +196161,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: row_indices_copy_out - operator_name: row_indices_copy +- name: alias_copy_out + operator_name: alias_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193774,7 +196215,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_padded_tensor.out(Tensor self, float padding, int[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193840,85 +196281,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_layer_norm_out - operator_name: _nested_tensor_layer_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_nested_tensor_layer_norm.out(Tensor self, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const c10::optional &, const c10::optional &, double, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_encoder_layer_fwd_out operator_name: _transformer_encoder_layer_fwd overload_name: out @@ -195616,3 +197978,425 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_out + operator_name: _fused_adamw + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _fused_adamw + operator_name: _fused_adamw + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + field_name: self_out + name: self_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: grads_out + name: grads_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avgs_out + name: exp_avgs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avg_sqs_out + name: exp_avg_sqs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: max_exp_avg_sqs_out + name: max_exp_avg_sqs_out + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false diff --git a/src/lantern/include/lantern/lantern.h b/src/lantern/include/lantern/lantern.h index 7a3706a453..4224b2ee4a 100644 --- a/src/lantern/include/lantern/lantern.h +++ b/src/lantern/include/lantern/lantern.h @@ -2865,6 +2865,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_affine_grid_generator_tensor_intarrayref_bool(void* theta, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_tensor_intarrayref_bool(theta, size, align_corners); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_affine_grid_generator_backward_tensor_intarrayref_bool)(void* grad, void* size, void* align_corners); HOST_API void* lantern_affine_grid_generator_backward_tensor_intarrayref_bool(void* grad, void* size, void* align_corners) { LANTERN_CHECK_LOADED void* ret = _lantern_affine_grid_generator_backward_tensor_intarrayref_bool(grad, size, align_corners); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_all_true_tensor)(void* self); + HOST_API void* lantern__is_all_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_all_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_all_true_tensor(void* self) { void* ret = _lantern_Tensor__is_all_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__is_any_true_tensor)(void* self); + HOST_API void* lantern__is_any_true_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor__is_any_true_tensor)(void* self); + HOST_API void* lantern_Tensor__is_any_true_tensor(void* self) { void* ret = _lantern_Tensor__is_any_true_tensor(self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__test_check_tensor_tensor)(void* self); + HOST_API void* lantern__test_check_tensor_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__test_check_tensor_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_all_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_all_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_all_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4279,10 +4289,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -4375,6 +4383,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -4401,10 +4413,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mm_out_tensor_tensor_tensor(void* out, void* self, void* mat2) { LANTERN_CHECK_LOADED void* ret = _lantern_mm_out_tensor_tensor_tensor(out, self, mat2); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor)(void* sparse, void* dense); HOST_API void* lantern__sparse_mm_tensor_tensor(void* sparse, void* dense) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor(sparse, dense); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_tensor_tensor_cstringview)(void* sparse, void* dense, void* reduce); + HOST_API void* lantern__sparse_mm_tensor_tensor_cstringview(void* sparse, void* dense, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_tensor_tensor_cstringview(sparse, dense, reduce); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_tensor_tensor)(void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_tensor_tensor)(void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_tensor_tensor(void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_tensor_tensor(t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_mode_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_mode_tensor_intt_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_mode_tensor_intt_bool)(void* self, void* dim, void* keepdim); @@ -4477,6 +4489,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); HOST_API void* lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out, save_mean, save_invstd, input, weight, bias, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_tensor_double)(void* input, void* eps); HOST_API void* lantern_batch_norm_stats_tensor_double(void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_tensor_double(input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double)(void* input, void* weight, void* bias, void* mean, void* invstd, void* eps); @@ -4715,6 +4735,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_reshape_tensor_intarrayref(void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_reshape_tensor_intarrayref)(void* self, void* shape); HOST_API void* lantern_Tensor_reshape_tensor_intarrayref(void* self, void* shape) { void* ret = _lantern_Tensor_reshape_tensor_intarrayref(self, shape); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_copy_tensor_intarrayref)(void* self, void* size); + HOST_API void* lantern__reshape_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); HOST_API void* lantern__reshape_alias_tensor_intarrayref_intarrayref(void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_tensor_intarrayref_intarrayref(self, size, stride); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref)(void* self, void* size, void* stride); @@ -4763,10 +4785,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_prelu_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_tensor_tensor)(void* self, void* weight); HOST_API void* lantern_Tensor_prelu_tensor_tensor(void* self, void* weight) { void* ret = _lantern_Tensor_prelu_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_prelu_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); - HOST_API void* lantern_Tensor_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { void* ret = _lantern_Tensor_prelu_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_tensor_tensor)(void* self, void* weight); + HOST_API void* lantern__prelu_kernel_tensor_tensor(void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_tensor_tensor(self, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__prelu_kernel_backward_tensor_tensor_tensor)(void* grad_output, void* self, void* weight); + HOST_API void* lantern__prelu_kernel_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__prelu_kernel_backward_tensor_tensor_tensor(grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu_out_tensor_tensor_cstringview)(void* out, void* self, void* approximate); HOST_API void* lantern_gelu_out_tensor_tensor_cstringview(void* out, void* self, void* approximate) { LANTERN_CHECK_LOADED void* ret = _lantern_gelu_out_tensor_tensor_cstringview(out, self, approximate); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_gelu__tensor_cstringview)(void* self, void* approximate); @@ -5003,10 +5025,16 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_tensor_dimname(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze_tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor)(void* self); HOST_API void* lantern_Tensor_squeeze__tensor(void* self) { void* ret = _lantern_Tensor_squeeze__tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intt)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_intt(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_Tensor_squeeze__tensor_intarrayref(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_squeeze__tensor_dimname)(void* self, void* dim); HOST_API void* lantern_Tensor_squeeze__tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_squeeze__tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5361,6 +5389,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_where_tensor_scalar_tensor(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_tensor(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_tensor_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_tensor_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_where_tensor_tensor_scalar)(void* condition, void* self, void* other); + HOST_API void* lantern_Tensor_where_tensor_tensor_scalar(void* condition, void* self, void* other) { void* ret = _lantern_Tensor_where_tensor_tensor_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor_scalar_scalar)(void* condition, void* self, void* other); HOST_API void* lantern_where_tensor_scalar_scalar(void* condition, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_where_tensor_scalar_scalar(condition, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_where_tensor)(void* condition); @@ -5471,8 +5501,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_frexp_tensor(void* self) { void* ret = _lantern_Tensor_frexp_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frexp_out_tensor_tensor_tensor)(void* mantissa, void* exponent, void* self); HOST_API void* lantern_frexp_out_tensor_tensor_tensor(void* mantissa, void* exponent, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frexp_out_tensor_tensor_tensor(mantissa, exponent, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor)(void* self); - HOST_API void* lantern_frobenius_norm_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_tensor_intarrayref_bool)(void* self, void* dim, void* keepdim); HOST_API void* lantern_frobenius_norm_tensor_intarrayref_bool(void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern_frobenius_norm_tensor_intarrayref_bool(self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* dim, void* keepdim); @@ -5551,6 +5579,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview)(void* self, void* other, void* reduce); + HOST_API void* lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(void* self, void* other, void* reduce) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(self, other, reduce); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool)(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask); + HOST_API void* lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(self, grad_out, weight, reduce, arg_out, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar)(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha); HOST_API void* lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(out, self, mat1, mat2, beta, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_addmm_tensor_tensor_tensor_scalar_scalar)(void* self, void* mat1, void* mat2, void* beta, void* alpha); @@ -5683,20 +5715,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_unbind_tensor_dimname(void* self, void* dim) { void* ret = _lantern_Tensor_unbind_tensor_dimname(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_intt)(void* self, void* sparse_dim); HOST_API void* lantern_Tensor_to_sparse_tensor_intt(void* self, void* sparse_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_intt(self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csr_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csr_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor)(void* self); - HOST_API void* lantern_Tensor_to_sparse_csc_tensor(void* self) { void* ret = _lantern_Tensor_to_sparse_csc_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref)(void* self, void* blocksize); - HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref(void* self, void* blocksize) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref(self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt)(void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(void* self, void* layout, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csr_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csr_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csr_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_csc_tensor_intt)(void* self, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_csc_tensor_intt(void* self, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_csc_tensor_intt(self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt)(void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { void* ret = _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_mkldnn_tensor_scalartype)(void* self, void* dtype); HOST_API void* lantern_Tensor_to_mkldnn_tensor_scalartype(void* self, void* dtype) { void* ret = _lantern_Tensor_to_mkldnn_tensor_scalartype(self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt)(void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_backward_tensor_tensor)(void* grad, void* input); @@ -5821,8 +5853,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__local_scalar_dense_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__local_scalar_dense_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); HOST_API void* lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor)(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor(input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool)(void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -6223,8 +6255,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_diag_tensor_intt(void* self, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_diag_tensor_intt)(void* self, void* diagonal); HOST_API void* lantern_Tensor_diag_tensor_intt(void* self, void* diagonal) { void* ret = _lantern_Tensor_diag_tensor_intt(self, diagonal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diag_backward_tensor_intarrayref_intt)(void* grad, void* input_sizes, void* diagonal); - HOST_API void* lantern_diag_backward_tensor_intarrayref_intt(void* grad, void* input_sizes, void* diagonal) { LANTERN_CHECK_LOADED void* ret = _lantern_diag_backward_tensor_intarrayref_intt(grad, input_sizes, diagonal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* dim); HOST_API void* lantern_cross_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_cross_out_tensor_tensor_tensor_intt(out, self, other, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_cross_tensor_tensor_intt)(void* self, void* other, void* dim); @@ -6521,14 +6551,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(void* self, void* B, void* upper, void* left, void* unitriangular) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool(self, B, upper, left, unitriangular); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_linalg_vander_tensor_intt)(void* x, void* N); HOST_API void* lantern_linalg_vander_tensor_intt(void* x, void* N) { LANTERN_CHECK_LOADED void* ret = _lantern_linalg_vander_tensor_intt(x, N); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_out_tensor_tensor_tensor_bool_bool)(void* e, void* V, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_out_tensor_tensor_tensor_bool_bool(void* e, void* V, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_out_tensor_tensor_tensor_bool_bool(e, V, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor_symeig_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern_Tensor_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { void* ret = _lantern_Tensor_symeig_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_tensor_bool_bool)(void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_tensor_bool_bool(void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_tensor_bool_bool(self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool)(void* U, void* S, void* V, void* self, void* some, void* compute_uv); HOST_API void* lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(void* U, void* S, void* V, void* self, void* some, void* compute_uv) { LANTERN_CHECK_LOADED void* ret = _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(U, S, V, self, some, compute_uv); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_svd_tensor_bool_bool)(void* self, void* some, void* compute_uv); @@ -6819,6 +6841,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_Tensor_max_tensor_tensor(void* self, void* other) { void* ret = _lantern_Tensor_max_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern_max_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_max_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_max_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_minimum_tensor_tensor)(void* self, void* other); HOST_API void* lantern_minimum_tensor_tensor(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_minimum_tensor_tensor(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_minimum_tensor_tensor)(void* self, void* other); @@ -7007,6 +7031,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_scalar)(void* self, void* scalar); HOST_API void* lantern__foreach_div__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_maximum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_scalar)(void* self, void* scalar); + HOST_API void* lantern__foreach_minimum__tensorlist_scalar(void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_scalar(self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_tensorlist_scalar(self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_tensorlist_scalar)(void* self, void* other, void* alpha); @@ -7023,6 +7063,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div__tensorlist_tensorlist)(void* self, void* other); HOST_API void* lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_min__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_clamp_max__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); + HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add__tensorlist_arrayrefscalar)(void* self, void* scalars); @@ -7039,6 +7095,22 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul__tensorlist_arrayrefscalar)(void* self, void* scalars); HOST_API void* lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_maximum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_arrayrefscalar)(void* self, void* scalars); + HOST_API void* lantern__foreach_minimum__tensorlist_arrayrefscalar(void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_arrayrefscalar(self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_tensorlist)(void* self); HOST_API void* lantern__foreach_exp_tensorlist(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_tensorlist(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero__tensorlist)(void* self); @@ -7159,26 +7231,34 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar)(void* self, void* tensor1, void* tensor2, void* value); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar(self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum__tensorlist_tensorlist)(void* self, void* other); - HOST_API void* lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum__tensorlist_tensorlist(self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor)(void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_tensorlist_scalar)(void* self, void* ord); HOST_API void* lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_tensorlist_scalar(self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist)(void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp__tensorlist_tensorlist_scalar)(void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp__tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp__tensorlist_tensorlist_scalar(self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_tensor_tensor_bool_bool)(void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_tensor_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_tensor_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_tensor_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); @@ -7187,8 +7267,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_bucketize_scalar_tensor_bool_bool(void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_scalar_tensor_bool_bool(self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_tensor)(void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor)(void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); @@ -7529,52 +7607,28 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_pad_tensor_intarrayref_cstringview_double(void* self, void* pad, void* mode, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern_pad_tensor_intarrayref_cstringview_double(self, pad, mode, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble)(void* input, void* output_size, void* align_corners, void* scale_factors); HOST_API void* lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble)(void* input, void* output_size, void* scale_factors); HOST_API void* lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble)(void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double)(void* out, void* self, void* output_size, void* align_corners, void* scales); HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(void* out, void* self, void* output_size, void* align_corners, void* scales) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(out, self, output_size, align_corners, scales); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_tensor_intarrayref_bool_double)(void* self, void* output_size, void* align_corners, void* scales); @@ -8309,6 +8363,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_squeeze_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_squeeze_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_tensor_intarrayref)(void* self, void* dim); + HOST_API void* lantern_squeeze_copy_tensor_intarrayref(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_tensor_intarrayref(self, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_t_copy_tensor)(void* self); HOST_API void* lantern_t_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_tensor_intt_intt)(void* self, void* dim0, void* dim1); @@ -8333,6 +8389,12 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_row_indices_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_tensor_intt)(void* self, void* dim); HOST_API void* lantern_unbind_copy_tensor_intt(void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_tensor_intt(self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); + HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); + HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_intarrayref)(void* self, void* size); HOST_API void* lantern_view_copy_tensor_intarrayref(void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_tensor_intarrayref(self, size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_view_copy_tensor_scalartype)(void* self, void* dtype); @@ -8341,88 +8403,40 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_unfold_copy_tensor_intt_intt_intt(void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_tensor_intt_intt_intt(self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_tensor)(void* self); HOST_API void* lantern_alias_copy_tensor(void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_tensor(self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); - HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); - HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); - HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); - HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); - HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); - HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); - HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); - HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); - HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_copy_out_tensorlist_tensor_intt_intt)(void* out, void* self, void* split_size, void* dim); - HOST_API void* lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_copy_out_tensorlist_tensor_intt_intt(out, self, split_size, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt)(void* out, void* self, void* split_sizes, void* dim); - HOST_API void* lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(out, self, split_sizes, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); - HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unbind_copy_out_tensorlist_tensor_intt)(void* out, void* self, void* dim); - HOST_API void* lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unbind_copy_out_tensorlist_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); - HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); - HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); - HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref)(void* self, void* padding, void* output_size); HOST_API void* lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) { void* ret = _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(self, padding, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_softmax_with_shape_tensor_tensor)(void* self, void* query); HOST_API void* lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_softmax_with_shape_tensor_tensor(self, query); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double)(void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(void* self, void* weight, void* bias, void* eps) { void* ret = _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); HOST_API void* lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(query, key, value, embed_dim, num_head, qkv_weight, qkv_bias, proj_weight, proj_bias, mask, need_weights, average_attn_weights, mask_type); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); HOST_API void* lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal); - HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(query, key, value, attn_mask, dropout_p, need_attn_weights, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal); + HOST_API void* lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(query, key, value, attn_mask, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor)(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask); + HOST_API void* lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(query, key, value, attn_mask, dropout_p, is_causal, dropout_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool)(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(query, key, value, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal); + HOST_API void* lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(query, key, value, compute_log_sumexp, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool)(void* query, void* key, void* value, void* is_causal); + HOST_API void* lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(void* query, void* key, void* value, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(query, key, value, is_causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask); + HOST_API void* lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, return_debug_mask); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt)(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset); + HOST_API void* lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(grad_out, query, key, value, out, logsumexp, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal, philox_seed, philox_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool)(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal); + HOST_API void* lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(query, key, value, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, compute_log_sumexp, causal); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs); + HOST_API void* lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_CHECK_LOADED void* ret = _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(grad_out_, query, key, value, out, logsumexp, is_causal, chunk_grad_outputs); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double)(void* q, void* k, void* v, void* dropout_p); HOST_API void* lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) { LANTERN_CHECK_LOADED void* ret = _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(q, k, v, dropout_p); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask); @@ -8431,8 +8445,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_special_airy_ai_tensor(void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_tensor(x); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_special_airy_ai_out_tensor_tensor)(void* out, void* x); HOST_API void* lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) { LANTERN_CHECK_LOADED void* ret = _lantern_special_airy_ai_out_tensor_tensor(out, x); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool)(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal); - HOST_API void* lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal) { LANTERN_CHECK_LOADED void* ret = _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(query, key, value, cum_seq_q, cum_seq_k, max_q, max_k, dropout_p, is_causal); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value); HOST_API void* lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, incr_key, incr_value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool)(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights); @@ -8629,6 +8641,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foobar_tensor_bool_bool_bool(void* self, void* arg1, void* arg2, void* arg3) { LANTERN_CHECK_LOADED void* ret = _lantern__foobar_tensor_bool_bool_bool(self, arg1, arg2, arg3); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt)(void* out, void* self, void* other, void* self_num_batch_dims); HOST_API void* lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* self_num_batch_dims) { LANTERN_CHECK_LOADED void* ret = _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(out, self, other, self_num_batch_dims); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* deterministic, void* zero_infinity); @@ -8729,6 +8743,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* self, void* grid, void* grad_output) { LANTERN_CHECK_LOADED void* ret = _lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, self, grid, grad_output); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity); + HOST_API void* lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(out0, out1, log_probs, targets, input_lengths, target_lengths, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool)(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity); HOST_API void* lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity) { LANTERN_CHECK_LOADED void* ret = _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(out, grad, log_probs, targets, input_lengths, target_lengths, neg_log_likelihood, log_alpha, blank, zero_infinity); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_diag_embed_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); @@ -8855,10 +8871,8 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__aminmax_out_tensor_tensor_tensor(void* out0, void* out1, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor(out0, out1, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__aminmax_out_tensor_tensor_tensor_intt_bool)(void* out0, void* out1, void* self, void* dim, void* keepdim); HOST_API void* lantern__aminmax_out_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* self, void* dim, void* keepdim) { LANTERN_CHECK_LOADED void* ret = _lantern__aminmax_out_tensor_tensor_tensor_intt_bool(out0, out1, self, dim, keepdim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); - HOST_API void* lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); + HOST_API void* lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, grad_output, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); HOST_API void* lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(out, self, kernel_size, stride, padding, dilation, ceil_mode); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool)(void* out, void* grad_output, void* output, void* input, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode); @@ -8881,6 +8895,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(void* out0, void* out1, void* out2, void* self, void* grad_output, void* weight, void* padding, void* stride, void* dilation, void* groups, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool(out0, out1, out2, self, grad_output, weight, padding, stride, dilation, groups, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* weight, void* bias, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, weight, bias, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train); + HOST_API void* lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(out0, out1, out2, out3, input, weight0, weight1, weight2, weight3, hx_, cx_, reverse, batch_sizes, mode, hidden_size, num_layers, has_biases, bidirectional, batch_first, train); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace); + HOST_API void* lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(out0, out1, out2, out3, out4, out5, out6, input, weight1, weight2, weight3, weight4, hx_, cx_tmp, output, hy_, cy_, grad_output, grad_hy, grad_cy, reverse, mode, hidden_size, num_layers, has_biases, train, bidirectional, batch_sizes, batch_first, workspace); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon); HOST_API void* lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(out0, out1, out2, input, weight, bias, running_mean, running_var, training, exponential_average_factor, epsilon); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double)(void* out0, void* out1, void* out2, void* input, void* grad_output, void* weight, void* running_mean, void* running_var, void* save_mean, void* save_var, void* epsilon); @@ -8897,10 +8915,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight, void* weight_stride0, void* weight_buf, void* hx, void* cx, void* output, void* grad_output, void* grad_hy, void* grad_cy, void* mode, void* hidden_size, void* num_layers, void* batch_first, void* dropout, void* train, void* bidirectional, void* batch_sizes, void* dropout_state, void* reserve, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool(out0, out1, out2, out3, input, weight, weight_stride0, weight_buf, hx, cx, output, grad_output, grad_hy, grad_cy, mode, hidden_size, num_layers, batch_first, dropout, train, bidirectional, batch_sizes, dropout_state, reserve, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor)(void* out, void* self, void* other); HOST_API void* lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__sparse_mask_helper_out_tensor_tensor_tensor)(void* out, void* t, void* mask_indices); - HOST_API void* lantern__sparse_mask_helper_out_tensor_tensor_tensor(void* out, void* t, void* mask_indices) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_mask_helper_out_tensor_tensor_tensor(out, t, mask_indices); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mul_out_tensor_tensor_scalar)(void* out, void* self, void* other); HOST_API void* lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern_mul_out_tensor_tensor_scalar(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double)(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps); + HOST_API void* lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(input, weight, bias, running_mean, running_var, training, momentum, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_stats_out_tensor_tensor_tensor_double)(void* out0, void* out1, void* input, void* eps); HOST_API void* lantern_batch_norm_stats_out_tensor_tensor_tensor_double(void* out0, void* out1, void* input, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern_batch_norm_stats_out_tensor_tensor_tensor_double(out0, out1, input, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt)(void* out0, void* out1, void* input, void* mean, void* invstd, void* running_mean, void* running_var, void* momentum, void* eps, void* count); @@ -8965,10 +8983,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(void* out, void* self, void* shape) { LANTERN_CHECK_LOADED void* ret = _lantern__mkldnn_reshape_out_tensor_tensor_intarrayref(out, self, shape); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_relu_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_relu_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_relu_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_out_tensor_tensor_tensor)(void* out, void* self, void* weight); - HOST_API void* lantern_prelu_out_tensor_tensor_tensor(void* out, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_out_tensor_tensor_tensor(out, self, weight); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* grad_output, void* self, void* weight); - HOST_API void* lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* grad_output, void* self, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(out0, out1, grad_output, self, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt)(void* out, void* grad_output, void* input_sizes, void* dim, void* index); HOST_API void* lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(void* out, void* grad_output, void* input_sizes, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(out, grad_output, input_sizes, dim, index); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_celu_out_tensor_tensor_scalar)(void* out, void* self, void* alpha); @@ -9131,20 +9145,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_copy_sparse_to_sparse_tensor_tensor_bool(void* self, void* src, void* non_blocking) { LANTERN_CHECK_LOADED void* ret = _lantern_copy_sparse_to_sparse_tensor_tensor_bool(self, src, non_blocking); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_intt)(void* out, void* self, void* sparse_dim); HOST_API void* lantern_to_sparse_out_tensor_tensor_intt(void* out, void* self, void* sparse_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_intt(out, self, sparse_dim); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csr_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern_to_sparse_csc_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref)(void* out, void* self, void* blocksize); - HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(out, self, blocksize); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt)(void* out, void* self, void* layout, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(void* out, void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(out, self, layout, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csr_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csr_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csr_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_csc_out_tensor_tensor_intt)(void* out, void* self, void* dense_dim); + HOST_API void* lantern_to_sparse_csc_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_csc_out_tensor_tensor_intt(out, self, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt)(void* out, void* self, void* blocksize, void* dense_dim); + HOST_API void* lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_CHECK_LOADED void* ret = _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(out, self, blocksize, dense_dim); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_mkldnn_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); HOST_API void* lantern_to_mkldnn_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_to_mkldnn_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); - HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size); + HOST_API void* lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(out, self, padding, stride, dilation, groups, input_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt)(void* out, void* self, void* padding, void* stride, void* dilation, void* groups); HOST_API void* lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) { LANTERN_CHECK_LOADED void* ret = _lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(out, self, padding, stride, dilation, groups); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool)(void* out, void* self, void* dtype, void* reduce_range); @@ -9187,10 +9201,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(void* self, void* observer_on, void* fake_quant_on, void* running_min, void* running_max, void* scale, void* zero_point, void* averaging_const, void* quant_min, void* quant_max, void* ch_axis, void* per_row_fake_quant, void* symmetric_quant) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool(self, observer_on, fake_quant_on, running_min, running_max, scale, zero_point, averaging_const, quant_min, quant_max, ch_axis, per_row_fake_quant, symmetric_quant); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__to_copy_out_tensor_tensor_bool_memoryformat)(void* out, void* self, void* non_blocking, void* memory_format); HOST_API void* lantern__to_copy_out_tensor_tensor_bool_memoryformat(void* out, void* self, void* non_blocking, void* memory_format) { LANTERN_CHECK_LOADED void* ret = _lantern__to_copy_out_tensor_tensor_bool_memoryformat(out, self, non_blocking, memory_format); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); - HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, out3, out4, out5, input, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool)(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first); + HOST_API void* lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_CHECK_LOADED void* ret = _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(out0, out1, out2, grad_y, grad_hy, grad_cy, z_state, cell_state_fwd, input, layersOutputs, hx, params, has_biases, num_layers, dropout, train, bidirectional, batch_first); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor)(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias); HOST_API void* lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* out2, void* input_gates, void* hidden_gates, void* cx, void* input_bias, void* hidden_bias) { LANTERN_CHECK_LOADED void* ret = _lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(out0, out1, out2, input_gates, hidden_gates, cx, input_bias, hidden_bias); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool)(void* out0, void* out1, void* out2, void* grad_hy, void* grad_cy, void* cx, void* cy, void* workspace, void* has_bias); @@ -9293,8 +9307,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern_triu_indices_out_tensor_intt_intt_intt(void* out, void* row, void* col, void* offset) { LANTERN_CHECK_LOADED void* ret = _lantern_triu_indices_out_tensor_intt_intt_intt(out, row, col, offset); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_trace_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_trace_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_trace_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool)(void* out0, void* out1, void* self, void* eigenvectors, void* upper); - HOST_API void* lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(void* out0, void* out1, void* self, void* eigenvectors, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(out0, out1, self, eigenvectors, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool)(void* out, void* self, void* A, void* upper); HOST_API void* lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(void* out, void* self, void* A, void* upper) { LANTERN_CHECK_LOADED void* ret = _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(out, self, A, upper); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_dist_out_tensor_tensor_tensor_scalar)(void* out, void* self, void* other, void* p); @@ -9329,6 +9341,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* scalar); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(out, self, scalar); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(out, self, other, alpha); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* other, void* alpha); @@ -9337,6 +9357,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); @@ -9345,6 +9373,14 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); HOST_API void* lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* scalars); + HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(out, self, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_exp_out_tensorlist_tensorlist)(void* out, void* self); HOST_API void* lantern__foreach_exp_out_tensorlist_tensorlist(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_exp_out_tensorlist_tensorlist(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_zero_out_tensorlist_tensorlist)(void* out, void* self); @@ -9411,18 +9447,20 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensor1, void* tensor2, void* value) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar(out, self, tensor1, tensor2, value); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* other); - HOST_API void* lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(out, self, other); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor)(void* out, void* self, void* tensor1, void* tensor2, void* scalars); + HOST_API void* lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(out, self, tensor1, tensor2, scalars); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__foreach_norm_out_tensorlist_tensorlist_scalar)(void* out, void* self, void* ord); HOST_API void* lantern__foreach_norm_out_tensorlist_tensorlist_scalar(void* out, void* self, void* ord) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_norm_out_tensorlist_tensorlist_scalar(out, self, ord); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist)(void* out, void* self, void* tensors1, void* weights); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(void* out, void* self, void* tensors1, void* weights) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(out, self, tensors1, weights); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar)(void* out, void* self, void* tensors1, void* weight); + HOST_API void* lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensors1, void* weight) { LANTERN_CHECK_LOADED void* ret = _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(out, self, tensors1, weight); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_bucketize_out_tensor_scalar_tensor_bool_bool)(void* out, void* self, void* boundaries, void* out_int32, void* right); HOST_API void* lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) { LANTERN_CHECK_LOADED void* ret = _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(out, self, boundaries, out_int32, right); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor)(void* out, void* self); - HOST_API void* lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor)(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter); HOST_API void* lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_CHECK_LOADED void* ret = _lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor(out, sorted_sequence, self, out_int32, right, side, sorter); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt)(void* out, void* glu, void* x, void* dx, void* dim); @@ -9443,54 +9481,6 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(void* out, void* self, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref(out, self, output_size); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor)(void* out, void* grad_output, void* self); HOST_API void* lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(void* out, void* grad_output, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(out, grad_output, self); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble)(void* out, void* input, void* output_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(out, input, output_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors); - HOST_API void* lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(out, grad_output, output_size, input_size, align_corners, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble)(void* out, void* input, void* output_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(out, input, output_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble)(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors); - HOST_API void* lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) { LANTERN_CHECK_LOADED void* ret = _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(out, grad_output, output_size, input_size, scale_factors); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool)(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask); HOST_API void* lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) { LANTERN_CHECK_LOADED void* ret = _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(out0, out1, out2, grad_output, self, weight, kernel_size, stride, padding, output_mask); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref)(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation); @@ -9521,14 +9511,74 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) { LANTERN_CHECK_LOADED void* ret = _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(out, grad, output, data, reduce, lengths, offsets, axis, initial); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool)(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory); HOST_API void* lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(out, list, dtype, layout, device, pin_memory); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fw_primal_copy_out_tensor_tensor_intt)(void* out, void* self, void* level); + HOST_API void* lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__fw_primal_copy_out_tensor_tensor_intt(out, self, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__make_dual_copy_out_tensor_tensor_tensor_intt)(void* out, void* primal, void* tangent, void* level); + HOST_API void* lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_CHECK_LOADED void* ret = _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(out, primal, tangent, level); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_real_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_real_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_as_complex_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_view_as_complex_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__conj_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__conj_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__neg_view_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__neg_view_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt)(void* out, void* self, void* size, void* stride, void* storage_offset); + HOST_API void* lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_CHECK_LOADED void* ret = _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(out, self, size, stride, storage_offset); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* offset, void* dim1, void* dim2); + HOST_API void* lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_CHECK_LOADED void* ret = _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(out, self, offset, dim1, dim2); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_expand_copy_out_tensor_tensor_intarrayref_bool)(void* out, void* self, void* size, void* implicit); + HOST_API void* lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_CHECK_LOADED void* ret = _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(out, self, size, implicit); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_permute_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dims); + HOST_API void* lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_CHECK_LOADED void* ret = _lantern_permute_copy_out_tensor_tensor_intarrayref(out, self, dims); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref)(void* out, void* self, void* size, void* stride); + HOST_API void* lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_CHECK_LOADED void* ret = _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(out, self, size, stride); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_select_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim, void* index); + HOST_API void* lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_CHECK_LOADED void* ret = _lantern_select_copy_out_tensor_tensor_intt_intt(out, self, dim, index); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_detach_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_detach_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt)(void* out, void* self, void* dim, void* start, void* end, void* step); + HOST_API void* lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(out, self, dim, start, end, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_squeeze_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* dim); + HOST_API void* lantern_squeeze_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_squeeze_copy_out_tensor_tensor_intarrayref(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_t_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_t_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_transpose_copy_out_tensor_tensor_intt_intt)(void* out, void* self, void* dim0, void* dim1); + HOST_API void* lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_CHECK_LOADED void* ret = _lantern_transpose_copy_out_tensor_tensor_intt_intt(out, self, dim0, dim1); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unsqueeze_copy_out_tensor_tensor_intt)(void* out, void* self, void* dim); + HOST_API void* lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_CHECK_LOADED void* ret = _lantern_unsqueeze_copy_out_tensor_tensor_intt(out, self, dim); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern__values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_values_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_values_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_crow_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_crow_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_col_indices_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_col_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_ccol_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_ccol_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_ccol_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_row_indices_copy_out_tensor_tensor)(void* out, void* self); HOST_API void* lantern_row_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_row_indices_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_intarrayref)(void* out, void* self, void* size); + HOST_API void* lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_intarrayref(out, self, size); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_view_copy_out_tensor_tensor_scalartype)(void* out, void* self, void* dtype); + HOST_API void* lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) { LANTERN_CHECK_LOADED void* ret = _lantern_view_copy_out_tensor_tensor_scalartype(out, self, dtype); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt)(void* out, void* self, void* dimension, void* size, void* step); + HOST_API void* lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_CHECK_LOADED void* ret = _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(out, self, dimension, size, step); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern_alias_copy_out_tensor_tensor)(void* out, void* self); + HOST_API void* lantern_alias_copy_out_tensor_tensor(void* out, void* self) { LANTERN_CHECK_LOADED void* ret = _lantern_alias_copy_out_tensor_tensor(out, self); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref)(void* out, void* self, void* padding, void* output_size); HOST_API void* lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) { LANTERN_CHECK_LOADED void* ret = _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(out, self, padding, output_size); LANTERN_HOST_HANDLER return ret; } - LANTERN_API void* (LANTERN_PTR _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double)(void* out, void* self, void* weight, void* bias, void* eps); - HOST_API void* lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(void* out, void* self, void* weight, void* bias, void* eps) { LANTERN_CHECK_LOADED void* ret = _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(out, self, weight, bias, eps); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt)(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type); HOST_API void* lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* out, void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_CHECK_LOADED void* ret = _lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(out, src, embed_dim, num_heads, qkv_weight, qkv_bias, proj_weight, proj_bias, use_gelu, norm_first, eps, norm_weight_1, norm_bias_1, norm_weight_2, norm_bias_2, ffn_weight_1, ffn_bias_1, ffn_weight_2, ffn_bias_2, mask, mask_type); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt)(void* out0, void* out1, void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type); @@ -9547,6 +9597,10 @@ HOST_API void lantern_buffer_from_tensor (void* tensor, void* buffer, int n) HOST_API void* lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } LANTERN_API void* (LANTERN_PTR _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); HOST_API void* lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(out, self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } + LANTERN_API void* (LANTERN_PTR _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor)(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf); + HOST_API void* lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) { LANTERN_CHECK_LOADED void* ret = _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(self, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, lr, beta1, beta2, weight_decay, eps, amsgrad, maximize, grad_scale, found_inf); LANTERN_HOST_HANDLER return ret; } /* Autogen Headers -- End */ #ifdef __cplusplus @@ -10309,6 +10363,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_addr_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_affine_grid_generator_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_affine_grid_generator_backward_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern__is_all_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_all_true_tensor) + LOAD_SYMBOL(_lantern__is_any_true_tensor) + LOAD_SYMBOL(_lantern_Tensor__is_any_true_tensor) + LOAD_SYMBOL(_lantern__test_check_tensor_tensor) LOAD_SYMBOL(_lantern_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_all_tensor_intt_bool) LOAD_SYMBOL(_lantern_all_out_tensor_tensor_intt_bool) @@ -11016,8 +11075,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_pool1d_with_indices_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool1d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -11064,6 +11122,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -11077,8 +11137,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_mm_tensor_tensor) LOAD_SYMBOL(_lantern_mm_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor) + LOAD_SYMBOL(_lantern__sparse_mm_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_tensor_tensor) LOAD_SYMBOL(_lantern_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_Tensor_mode_tensor_intt_bool) LOAD_SYMBOL(_lantern_mode_out_tensor_tensor_tensor_intt_bool) @@ -11115,6 +11175,10 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_narrow_tensor_intt_tensor_intt) LOAD_SYMBOL(_lantern_native_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_elemt_out_tensor_tensor_tensor_tensor_tensor_tensor_double) @@ -11234,6 +11298,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_repeat_interleave_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_reshape_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_reshape_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_Tensor__reshape_alias_tensor_intarrayref_intarrayref) LOAD_SYMBOL(_lantern__mkldnn_reshape_tensor_intarrayref) @@ -11258,8 +11323,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_relu6__tensor) LOAD_SYMBOL(_lantern_prelu_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_prelu_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor_prelu_backward_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_tensor_tensor) + LOAD_SYMBOL(_lantern__prelu_kernel_backward_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_gelu_out_tensor_tensor_cstringview) LOAD_SYMBOL(_lantern_gelu__tensor_cstringview) LOAD_SYMBOL(_lantern_gelu_tensor_cstringview) @@ -11378,8 +11443,11 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intt) LOAD_SYMBOL(_lantern_squeeze_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_dimname) + LOAD_SYMBOL(_lantern_squeeze_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_squeeze_tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_intarrayref) LOAD_SYMBOL(_lantern_Tensor_squeeze__tensor_dimname) LOAD_SYMBOL(_lantern_sspaddmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_sspaddmm_tensor_tensor_tensor_scalar_scalar) @@ -11557,6 +11625,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_where_out_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_where_tensor_scalar_tensor) LOAD_SYMBOL(_lantern_where_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern_Tensor_where_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_where_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_where_tensor) LOAD_SYMBOL(_lantern_norm_except_dim_tensor_intt_intt) @@ -11612,7 +11681,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_frexp_tensor) LOAD_SYMBOL(_lantern_Tensor_frexp_tensor) LOAD_SYMBOL(_lantern_frexp_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_frobenius_norm_tensor) LOAD_SYMBOL(_lantern_frobenius_norm_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_frobenius_norm_out_tensor_tensor_intarrayref_bool) LOAD_SYMBOL(_lantern_nuclear_norm_tensor_bool) @@ -11652,6 +11720,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__sparse_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview) + LOAD_SYMBOL(_lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool) LOAD_SYMBOL(_lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_addmm_tensor_tensor_tensor_scalar_scalar) LOAD_SYMBOL(_lantern_Tensor_addmm_tensor_tensor_tensor_scalar_scalar) @@ -11718,13 +11788,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_unbind_tensor_dimname) LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_intt) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref) - LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csr_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_csc_tensor_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_Tensor_to_mkldnn_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_backward_tensor_tensor) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_tensor_scalartype_bool) @@ -11787,7 +11857,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_promote_types_scalartype_scalartype) LOAD_SYMBOL(_lantern__local_scalar_dense_tensor) LOAD_SYMBOL(_lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_tensor_tensor_tensor_tensor_tensor_bool) @@ -11988,7 +12058,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_diag_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern_diag_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_diag_tensor_intt) - LOAD_SYMBOL(_lantern_diag_backward_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_cross_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_cross_tensor_tensor_intt) LOAD_SYMBOL(_lantern_Tensor_cross_tensor_tensor_intt) @@ -12137,10 +12206,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_linalg_solve_triangular_out_tensor_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_solve_triangular_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern_linalg_vander_tensor_intt) - LOAD_SYMBOL(_lantern_symeig_out_tensor_tensor_tensor_bool_bool) - LOAD_SYMBOL(_lantern_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern_Tensor_symeig_tensor_bool_bool) - LOAD_SYMBOL(_lantern__symeig_helper_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_svd_tensor_bool_bool) LOAD_SYMBOL(_lantern_Tensor_svd_tensor_bool_bool) @@ -12286,6 +12351,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_max_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_max_tensor_tensor) LOAD_SYMBOL(_lantern_max_out_tensor_tensor_tensor) + LOAD_SYMBOL(_lantern_max_out_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_minimum_tensor_tensor) LOAD_SYMBOL(_lantern_minimum_out_tensor_tensor_tensor) @@ -12380,6 +12446,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_tensorlist_scalar) @@ -12388,6 +12462,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_add__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_tensorlist_arrayrefscalar) @@ -12396,6 +12478,14 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_div__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero__tensorlist) LOAD_SYMBOL(_lantern__foreach_exp__tensorlist) @@ -12456,21 +12546,24 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_maximum__tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum__tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp__tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_bucketize_scalar_tensor_bool_bool) LOAD_SYMBOL(_lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_searchsorted_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern__convert_indices_from_coo_to_csr_tensor_intt_bool) @@ -12641,29 +12734,17 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__pad_enum_tensor_intarrayref_intt_double) LOAD_SYMBOL(_lantern_pad_tensor_intarrayref_cstringview_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_tensor_intarrayref_bool_double) LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_double) @@ -13031,6 +13112,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_split_with_sizes_copy_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_squeeze_copy_tensor) LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_t_copy_tensor) LOAD_SYMBOL(_lantern_transpose_copy_tensor_intt_intt) LOAD_SYMBOL(_lantern_unsqueeze_copy_tensor_intt) @@ -13043,56 +13125,34 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_ccol_indices_copy_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_tensor) LOAD_SYMBOL(_lantern_unbind_copy_tensor_intt) + LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) + LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) + LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_view_copy_tensor_intarrayref) LOAD_SYMBOL(_lantern_view_copy_tensor_scalartype) LOAD_SYMBOL(_lantern_unfold_copy_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_alias_copy_tensor) - LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) - LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) - LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) - LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) - LOAD_SYMBOL(_lantern_split_copy_out_tensorlist_tensor_intt_intt) - LOAD_SYMBOL(_lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) - LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) - LOAD_SYMBOL(_lantern_unbind_copy_out_tensorlist_tensor_intt) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) - LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_Tensor_to_padded_tensor_tensor_double_intarrayref) LOAD_SYMBOL(_lantern__nested_tensor_softmax_with_shape_tensor_tensor) - LOAD_SYMBOL(_lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) + LOAD_SYMBOL(_lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool) LOAD_SYMBOL(_lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool) - LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) + LOAD_SYMBOL(_lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool) + LOAD_SYMBOL(_lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool) + LOAD_SYMBOL(_lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt) + LOAD_SYMBOL(_lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool) + LOAD_SYMBOL(_lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_tensor) LOAD_SYMBOL(_lantern_special_airy_ai_out_tensor_tensor) - LOAD_SYMBOL(_lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool) LOAD_SYMBOL(_lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern_special_bessel_j0_tensor) @@ -13191,6 +13251,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_special_spherical_bessel_j0_out_tensor_tensor) LOAD_SYMBOL(_lantern__foobar_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__cudnn_ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool_bool) LOAD_SYMBOL(_lantern__cudnn_rnn_flatten_weight_out_tensor_tensorlist_intt_intt_intt_intt_intt_intt_bool_bool) @@ -13241,6 +13302,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_cudnn_grid_sampler_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_cudnn_grid_sampler_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intt_bool) + LOAD_SYMBOL(_lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool) LOAD_SYMBOL(_lantern_diag_embed_out_tensor_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_diagonal_backward_out_tensor_tensor_intarrayref_intt_intt_intt) @@ -13304,8 +13366,7 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_matmul_backward_out_tensor_tensor_tensor_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__aminmax_out_tensor_tensor_tensor_intt_bool) - LOAD_SYMBOL(_lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) - LOAD_SYMBOL(_lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) + LOAD_SYMBOL(_lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool2d_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) LOAD_SYMBOL(_lantern_mkldnn_max_pool3d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool) @@ -13317,6 +13378,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__mps_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_mps_convolution_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_stdarraybool) LOAD_SYMBOL(_lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool) + LOAD_SYMBOL(_lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor) LOAD_SYMBOL(_lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_miopen_batch_norm_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_miopen_convolution_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_bool_bool) @@ -13325,8 +13388,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_miopen_rnn_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_intt_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor) LOAD_SYMBOL(_lantern_miopen_rnn_backward_out_tensor_tensor_tensor_tensorlist_tensor_tensorlist_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_intt_bool_double_bool_bool_intarrayref_tensor_tensor_stdarraybool) LOAD_SYMBOL(_lantern__sparse_sparse_matmul_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern__sparse_mask_helper_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_mul_out_tensor_tensor_scalar) + LOAD_SYMBOL(_lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double) LOAD_SYMBOL(_lantern_batch_norm_stats_out_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_intt) LOAD_SYMBOL(_lantern_batch_norm_gather_stats_with_counts_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_double_tensor) @@ -13359,8 +13422,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_repeat_interleave_out_tensor_tensor_intt) LOAD_SYMBOL(_lantern__mkldnn_reshape_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern_relu_out_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt) LOAD_SYMBOL(_lantern_celu_out_tensor_tensor_scalar) LOAD_SYMBOL(_lantern_slice_backward_out_tensor_tensor_intarrayref_intt_intt_intt_intt) @@ -13442,13 +13503,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_copy_sparse_to_sparse_tensor_tensor_bool) LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_intt) - LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor) - LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref) - LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_csr_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_csc_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt) + LOAD_SYMBOL(_lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt) LOAD_SYMBOL(_lantern_to_mkldnn_out_tensor_tensor_scalartype) - LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref) LOAD_SYMBOL(_lantern_mkldnn_reorder_conv3d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt) LOAD_SYMBOL(_lantern_quantize_per_tensor_dynamic_out_tensor_tensor_scalartype_bool) LOAD_SYMBOL(_lantern_quantize_per_tensor_out_tensor_tensor_double_intt_scalartype) @@ -13470,8 +13531,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__fused_moving_avg_obs_fq_helper_functional_tensor_tensor_tensor_tensor_tensor_tensor_tensor_double_intt_intt_intt_bool_bool) LOAD_SYMBOL(_lantern__to_copy_out_tensor_tensor_bool_memoryformat) - LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) - LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) + LOAD_SYMBOL(_lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__thnn_fused_lstm_cell_backward_impl_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern__thnn_fused_gru_cell_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor) @@ -13523,7 +13584,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_tril_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_triu_indices_out_tensor_intt_intt_intt) LOAD_SYMBOL(_lantern_trace_out_tensor_tensor) - LOAD_SYMBOL(_lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool) LOAD_SYMBOL(_lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool) LOAD_SYMBOL(_lantern_dist_out_tensor_tensor_tensor_scalar) LOAD_SYMBOL(_lantern__histogramdd_bin_edges_out_tensorlist_tensor_intarrayref_arrayrefdouble_tensor_bool) @@ -13541,14 +13601,26 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_sub_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_div_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar) LOAD_SYMBOL(_lantern__foreach_exp_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_out_tensorlist_tensorlist) LOAD_SYMBOL(_lantern__foreach_zero_tensorlist) @@ -13582,12 +13654,13 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) + LOAD_SYMBOL(_lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar) - LOAD_SYMBOL(_lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist) - LOAD_SYMBOL(_lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor) LOAD_SYMBOL(_lantern__foreach_norm_out_tensorlist_tensorlist_scalar) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist) + LOAD_SYMBOL(_lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar) LOAD_SYMBOL(_lantern_bucketize_out_tensor_scalar_tensor_bool_bool) - LOAD_SYMBOL(_lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor) LOAD_SYMBOL(_lantern_searchsorted_out_tensor_tensor_scalar_bool_bool_cstringview_tensor) LOAD_SYMBOL(_lantern_glu_jvp_out_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern_glu_backward_jvp_out_tensor_tensor_tensor_tensor_tensor_tensor_intt) @@ -13598,30 +13671,6 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__adaptive_avg_pool2d_backward_out_tensor_tensor_tensor) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_out_tensor_tensor_intarrayref) LOAD_SYMBOL(_lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor) - LOAD_SYMBOL(_lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) - LOAD_SYMBOL(_lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble) LOAD_SYMBOL(_lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool) LOAD_SYMBOL(_lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) LOAD_SYMBOL(_lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref) @@ -13637,10 +13686,40 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar) LOAD_SYMBOL(_lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar) LOAD_SYMBOL(_lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool) + LOAD_SYMBOL(_lantern__fw_primal_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__make_dual_copy_out_tensor_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_view_as_real_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_as_complex_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__conj_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__neg_view_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt) + LOAD_SYMBOL(_lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_expand_copy_out_tensor_tensor_intarrayref_bool) + LOAD_SYMBOL(_lantern_permute_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref) + LOAD_SYMBOL(_lantern_select_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_detach_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern_squeeze_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_t_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_transpose_copy_out_tensor_tensor_intt_intt) + LOAD_SYMBOL(_lantern_unsqueeze_copy_out_tensor_tensor_intt) + LOAD_SYMBOL(_lantern__indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern__values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_values_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_crow_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_col_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_ccol_indices_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_row_indices_copy_out_tensor_tensor) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_intarrayref) + LOAD_SYMBOL(_lantern_view_copy_out_tensor_tensor_scalartype) + LOAD_SYMBOL(_lantern_unfold_copy_out_tensor_tensor_intt_intt_intt) + LOAD_SYMBOL(_lantern_alias_copy_out_tensor_tensor) LOAD_SYMBOL(_lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref) - LOAD_SYMBOL(_lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double) LOAD_SYMBOL(_lantern__transformer_encoder_layer_fwd_out_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt) LOAD_SYMBOL(_lantern__native_multi_head_attention_out_tensor_tensor_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt) LOAD_SYMBOL(_lantern__triton_scaled_dot_attention_out_tensor_tensor_tensor_tensor_double) @@ -13650,6 +13729,8 @@ LOAD_SYMBOL(_lantern_buffer_from_tensor); LOAD_SYMBOL(_lantern__foobar_out_tensor_tensor_bool_bool_bool) LOAD_SYMBOL(_lantern__fused_adam_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) LOAD_SYMBOL(_lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) + LOAD_SYMBOL(_lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor) /* Autogen Symbols -- End */ return true; diff --git a/src/lantern/src/AllocatorMPS.cpp b/src/lantern/src/AllocatorMPS.cpp index 0c465570da..c95e376ab0 100644 --- a/src/lantern/src/AllocatorMPS.cpp +++ b/src/lantern/src/AllocatorMPS.cpp @@ -9,14 +9,14 @@ namespace at { namespace mps { - class IMpsAllocatorCallback { - public: +public: enum class EventType { ALLOCATED, // buffer got allocated to be used immediately RECYCLED, // buffer pulled from free list to be reused FREED, // buffer put to free list for future recycling RELEASED, // buffer memory released + ALLOCATION_FAILED // buffer allocation failed }; virtual ~IMpsAllocatorCallback() = default; virtual void executeMPSAllocatorCallback(void* ptr, EventType event) = 0; @@ -25,11 +25,7 @@ class IMpsAllocatorCallback { // MPS allocator will execute every registered callback when a block of memory is freed. C10_DECLARE_REGISTRY(MPSAllocatorCallbacksRegistry, IMpsAllocatorCallback); #define REGISTER_MPS_ALLOCATOR_CALLBACK(name, ...) \ - C10_REGISTER_CLASS(MPSAllocatorCallbacksRegistry, name, __VA_ARGS__); - -at::Allocator* getMPSStaticAllocator(); - -int free_calls = 0; +C10_REGISTER_CLASS(MPSAllocatorCallbacksRegistry, name, __VA_ARGS__); class MPSGarbageCollectorCallback : virtual public at::mps::IMpsAllocatorCallback { public: @@ -48,8 +44,11 @@ class MPSGarbageCollectorCallback : virtual public at::mps::IMpsAllocatorCallbac // caling gc here will deadlock. break; case EventType::RELEASED: + // this is never used currently. + break; + case EventType::ALLOCATION_FAILED: // we want to call the gc in this situation: - // https://github.com/pytorch/pytorch/blob/664058fa83f1d8eede5d66418abff6e20bd76ca8/aten/src/ATen/mps/MPSAllocator.mm#L215 + // https://github.com/pytorch/pytorch/blob/b37a50afda55c5b73298016d10fca1f8c6f65055/aten/src/ATen/mps/MPSAllocator.mm#L211C44-L211C78 (*call_r_gc)(true); wait_for_gc(); break; @@ -61,6 +60,5 @@ class MPSGarbageCollectorCallback : virtual public at::mps::IMpsAllocatorCallbac REGISTER_MPS_ALLOCATOR_CALLBACK("gc", MPSGarbageCollectorCallback); -} -} +}} diff --git a/src/lantern/src/Indexing.cpp b/src/lantern/src/Indexing.cpp index b3bae84bb4..be2cdf458e 100644 --- a/src/lantern/src/Indexing.cpp +++ b/src/lantern/src/Indexing.cpp @@ -66,6 +66,15 @@ void _lantern_TensorIndex_append_int64(void *self, int64_t x) { LANTERN_FUNCTION_END_VOID } +c10::optional symint_from_optional_int (c10::optional x) { + if (x == c10::nullopt) { + return c10::nullopt; + } + else { + return c10::SymInt(*x); + } +} + void *_lantern_Slice(void *start, void *end, void *step) { LANTERN_FUNCTION_START auto start_ = from_raw::optional::int64_t(start); @@ -83,7 +92,10 @@ void *_lantern_Slice(void *start, void *end, void *step) { step_ = None; } - auto out = torch::indexing::Slice(start_, end_, step_); + + + + auto out = torch::indexing::Slice(symint_from_optional_int(start_), symint_from_optional_int(end_), symint_from_optional_int(step_)); return make_ptr(out); LANTERN_FUNCTION_END } diff --git a/src/lantern/src/Pickler.cpp b/src/lantern/src/Pickler.cpp index 3ec4d43c2b..e4bf753b74 100644 --- a/src/lantern/src/Pickler.cpp +++ b/src/lantern/src/Pickler.cpp @@ -108,7 +108,7 @@ class DeserializationStorageContext; // deleted at some point, the Pickler doesn't produce it and it's only around to // support models saved before 1.1 class LANTERN_API LanternUnpickler { - TH_DISALLOW_COPY_AND_ASSIGN(LanternUnpickler); + AT_DISALLOW_COPY_AND_ASSIGN(LanternUnpickler); using TypeParserT = c10::TypePtr (*)(const std::string&); diff --git a/src/lantern/src/Tensor.cpp b/src/lantern/src/Tensor.cpp index 9facf5f23f..cf122e8d80 100644 --- a/src/lantern/src/Tensor.cpp +++ b/src/lantern/src/Tensor.cpp @@ -384,8 +384,8 @@ void _lantern_tensor_set_pyobj(void *x, void *ptr) { LANTERN_FUNCTION_START PyObject *ptr_ = reinterpret_cast(ptr); auto t = from_raw::Tensor(x); - t.unsafeGetTensorImpl()->init_pyobj( - &lantern_interpreter, ptr_, + t.unsafeGetTensorImpl()->pyobj_slot()->init_pyobj( + nullptr, ptr_, c10::impl::PyInterpreterStatus::DEFINITELY_UNINITIALIZED); LANTERN_FUNCTION_END_VOID } @@ -393,12 +393,8 @@ void _lantern_tensor_set_pyobj(void *x, void *ptr) { void *_lantern_tensor_get_pyobj(void *x) { LANTERN_FUNCTION_START auto t = from_raw::Tensor(x); - auto pyobj = t.unsafeGetTensorImpl()->check_pyobj(&lantern_interpreter); - if (pyobj.has_value()) { - return (void *)pyobj.value(); - } else { - return nullptr; - } + auto pyobj = (void*) t.unsafeGetTensorImpl()->pyobj_slot()->_unchecked_untagged_pyobj(); + return pyobj; LANTERN_FUNCTION_END } diff --git a/src/lantern/src/lantern.cpp b/src/lantern/src/lantern.cpp index 04194b7b7f..72edf9ce88 100644 --- a/src/lantern/src/lantern.cpp +++ b/src/lantern/src/lantern.cpp @@ -1119,6 +1119,46 @@ void* _lantern_affine_grid_generator_backward_tensor_intarrayref_bool(void* grad LANTERN_FUNCTION_END } +void* _lantern__is_all_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_is_all_true( + from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + +void* _lantern_Tensor__is_all_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self)._is_all_true( + )); + LANTERN_FUNCTION_END +} + +void* _lantern__is_any_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_is_any_true( + from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + +void* _lantern_Tensor__is_any_true_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self)._is_any_true( + )); + LANTERN_FUNCTION_END +} + +void* _lantern__test_check_tensor_tensor(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_test_check_tensor( + from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + void* _lantern_all_tensor_intt_bool(void* self, void* dim, void* keepdim) { LANTERN_FUNCTION_START @@ -6791,18 +6831,10 @@ void* _lantern_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref LANTERN_FUNCTION_END } -void* _lantern__mps_max_pool2d_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_mps_max_pool2d( - from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); - LANTERN_FUNCTION_END -} - -void* _lantern_mps_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) +void* _lantern_max_pool2d_backward_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::mps_max_pool2d_backward( + return make_raw::Tensor(torch::max_pool2d_backward( from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); LANTERN_FUNCTION_END } @@ -7175,6 +7207,22 @@ void* _lantern_mkldnn_convolution_tensor_tensor_tensor_intarrayref_intarrayref_i LANTERN_FUNCTION_END } +void* _lantern_mkldnn_rnn_layer_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer( + from_raw::Tensor(input), from_raw::Tensor(weight0), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(hx_), from_raw::Tensor(cx_), from_raw::bool_t(reverse), from_raw::IntArrayRef(batch_sizes), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first), from_raw::bool_t(train))); + LANTERN_FUNCTION_END +} + +void* _lantern_mkldnn_rnn_layer_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer_backward( + from_raw::Tensor(input), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(weight4), from_raw::Tensor(hx_), from_raw::Tensor(cx_tmp), from_raw::Tensor(output), from_raw::Tensor(hy_), from_raw::Tensor(cy_), from_raw::optional::Tensor(grad_output), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::bool_t(reverse), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::IntArrayRef(batch_sizes), from_raw::bool_t(batch_first), from_raw::Tensor(workspace))); + LANTERN_FUNCTION_END +} + void* _lantern_miopen_batch_norm_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_FUNCTION_START @@ -7279,19 +7327,19 @@ void* _lantern__sparse_mm_tensor_tensor(void* sparse, void* dense) LANTERN_FUNCTION_END } -void* _lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) +void* _lantern__sparse_mm_tensor_tensor_cstringview(void* sparse, void* dense, void* reduce) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_sparse_matmul( - from_raw::Tensor(self), from_raw::Tensor(other))); + return make_raw::Tensor(torch::_sparse_mm( + from_raw::Tensor(sparse), from_raw::Tensor(dense), from_raw::string_view(reduce))); LANTERN_FUNCTION_END } -void* _lantern__sparse_mask_helper_tensor_tensor(void* t, void* mask_indices) +void* _lantern__sparse_sparse_matmul_tensor_tensor(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_mask_helper( - from_raw::Tensor(t), from_raw::Tensor(mask_indices))); + return make_raw::Tensor(torch::_sparse_sparse_matmul( + from_raw::Tensor(self), from_raw::Tensor(other))); LANTERN_FUNCTION_END } @@ -7583,6 +7631,38 @@ void* _lantern_native_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_t LANTERN_FUNCTION_END } +void* _lantern__native_batch_norm_legit_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit( + from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::Tensor(running_mean), from_raw::Tensor(running_var), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + +void* _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit_out( + from_raw::Tensor(out), from_raw::Tensor(save_mean), from_raw::Tensor(save_invstd), from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::Tensor(running_mean), from_raw::Tensor(running_var), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + +void* _lantern__native_batch_norm_legit_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit( + from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + +void* _lantern__native_batch_norm_legit_out_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out, void* save_mean, void* save_invstd, void* input, void* weight, void* bias, void* training, void* momentum, void* eps) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_native_batch_norm_legit_out( + from_raw::Tensor(out), from_raw::Tensor(save_mean), from_raw::Tensor(save_invstd), from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); + LANTERN_FUNCTION_END +} + void* _lantern_batch_norm_stats_tensor_double(void* input, void* eps) { LANTERN_FUNCTION_START @@ -8535,6 +8615,14 @@ void* _lantern_Tensor_reshape_tensor_intarrayref(void* self, void* shape) LANTERN_FUNCTION_END } +void* _lantern__reshape_copy_tensor_intarrayref(void* self, void* size) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_reshape_copy( + from_raw::Tensor(self), from_raw::IntArrayRef(size))); + LANTERN_FUNCTION_END +} + void* _lantern__reshape_alias_tensor_intarrayref_intarrayref(void* self, void* size, void* stride) { LANTERN_FUNCTION_START @@ -8727,19 +8815,19 @@ void* _lantern_Tensor_prelu_tensor_tensor(void* self, void* weight) LANTERN_FUNCTION_END } -void* _lantern_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) +void* _lantern__prelu_kernel_tensor_tensor(void* self, void* weight) { LANTERN_FUNCTION_START - return make_raw::tuple(torch::prelu_backward( - from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight))); + return make_raw::Tensor(torch::_prelu_kernel( + from_raw::Tensor(self), from_raw::Tensor(weight))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_prelu_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) +void* _lantern__prelu_kernel_backward_tensor_tensor_tensor(void* grad_output, void* self, void* weight) { LANTERN_FUNCTION_START - return make_raw::tuple(from_raw::Tensor(grad_output).prelu_backward( - from_raw::Tensor(self), from_raw::Tensor(weight))); + return make_raw::tuple(torch::_prelu_kernel_backward( + from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight))); LANTERN_FUNCTION_END } @@ -9687,6 +9775,22 @@ void* _lantern_Tensor_squeeze_tensor_dimname(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_squeeze_tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::squeeze( + from_raw::Tensor(self), from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + +void* _lantern_Tensor_squeeze_tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self).squeeze( + from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + void* _lantern_Tensor_squeeze__tensor(void* self) { LANTERN_FUNCTION_START @@ -9703,6 +9807,14 @@ void* _lantern_Tensor_squeeze__tensor_intt(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_Tensor_squeeze__tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(self).squeeze_( + from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + void* _lantern_Tensor_squeeze__tensor_dimname(void* self, void* dim) { LANTERN_FUNCTION_START @@ -11119,6 +11231,14 @@ void* _lantern_where_tensor_tensor_scalar(void* condition, void* self, void* oth LANTERN_FUNCTION_END } +void* _lantern_Tensor_where_tensor_tensor_scalar(void* condition, void* self, void* other) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(from_raw::Tensor(condition).where( + from_raw::Tensor(self), from_raw::Scalar(other))); + LANTERN_FUNCTION_END +} + void* _lantern_where_tensor_scalar_scalar(void* condition, void* self, void* other) { LANTERN_FUNCTION_START @@ -11559,14 +11679,6 @@ void* _lantern_frexp_out_tensor_tensor_tensor(void* mantissa, void* exponent, vo LANTERN_FUNCTION_END } -void* _lantern_frobenius_norm_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::frobenius_norm( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - void* _lantern_frobenius_norm_tensor_intarrayref_bool(void* self, void* dim, void* keepdim) { LANTERN_FUNCTION_START @@ -11879,6 +11991,22 @@ void* _lantern_sparse_sampled_addmm_tensor_tensor_tensor_scalar_scalar(void* sel LANTERN_FUNCTION_END } +void* _lantern__sparse_mm_reduce_impl_tensor_tensor_cstringview(void* self, void* other, void* reduce) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_sparse_mm_reduce_impl( + from_raw::Tensor(self), from_raw::Tensor(other), from_raw::string_view(reduce))); + LANTERN_FUNCTION_END +} + +void* _lantern__sparse_mm_reduce_impl_backward_tensor_tensor_tensor_cstringview_tensor_stdarraybool(void* self, void* grad_out, void* weight, void* reduce, void* arg_out, void* output_mask) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_sparse_mm_reduce_impl_backward( + from_raw::Tensor(self), from_raw::Tensor(grad_out), from_raw::Tensor(weight), from_raw::string_view(reduce), from_raw::Tensor(arg_out), from_raw::vector::bool_t(output_mask))); + LANTERN_FUNCTION_END +} + void* _lantern_addmm_out_tensor_tensor_tensor_tensor_scalar_scalar(void* out, void* self, void* mat1, void* mat2, void* beta, void* alpha) { LANTERN_FUNCTION_START @@ -12407,43 +12535,43 @@ void* _lantern_Tensor_to_sparse_tensor_intt(void* self, void* sparse_dim) LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_tensor(void* self) +void* _lantern_Tensor_to_sparse_tensor_layout_intarrayref_intt(void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse( - )); + from_raw::optional::Layout(layout), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_csr_tensor(void* self) +void* _lantern_Tensor_to_sparse_csr_tensor_intt(void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_csr( - )); + from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_csc_tensor(void* self) +void* _lantern_Tensor_to_sparse_csc_tensor_intt(void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_csc( - )); + from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_bsr_tensor_intarrayref(void* self, void* blocksize) +void* _lantern_Tensor_to_sparse_bsr_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_bsr( - from_raw::IntArrayRef(blocksize))); + from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_Tensor_to_sparse_bsc_tensor_intarrayref(void* self, void* blocksize) +void* _lantern_Tensor_to_sparse_bsc_tensor_intarrayref_intt(void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(from_raw::Tensor(self).to_sparse_bsc( - from_raw::IntArrayRef(blocksize))); + from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } @@ -12455,11 +12583,11 @@ void* _lantern_Tensor_to_mkldnn_tensor_scalartype(void* self, void* dtype) LANTERN_FUNCTION_END } -void* _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt(void* self, void* padding, void* stride, void* dilation, void* groups) +void* _lantern_mkldnn_reorder_conv2d_weight_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::mkldnn_reorder_conv2d_weight( - from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups))); + from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups), from_raw::IntArrayRef(input_size))); LANTERN_FUNCTION_END } @@ -12959,11 +13087,11 @@ void* _lantern__lstm_mps_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool LANTERN_FUNCTION_END } -void* _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) +void* _lantern_lstm_mps_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_FUNCTION_START return make_raw::tuple(torch::lstm_mps_backward( - from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); + from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::Tensor(layersOutputs), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); LANTERN_FUNCTION_END } @@ -14567,14 +14695,6 @@ void* _lantern_Tensor_diag_tensor_intt(void* self, void* diagonal) LANTERN_FUNCTION_END } -void* _lantern_diag_backward_tensor_intarrayref_intt(void* grad, void* input_sizes, void* diagonal) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::diag_backward( - from_raw::Tensor(grad), from_raw::IntArrayRef(input_sizes), from_raw::int64_t(diagonal))); - LANTERN_FUNCTION_END -} - void* _lantern_cross_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* dim) { LANTERN_FUNCTION_START @@ -15759,38 +15879,6 @@ void* _lantern_linalg_vander_tensor_intt(void* x, void* N) LANTERN_FUNCTION_END } -void* _lantern_symeig_out_tensor_tensor_tensor_bool_bool(void* e, void* V, void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::symeig_out( - from_raw::Tensor(e), from_raw::Tensor(V), from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - -void* _lantern_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::symeig( - from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - -void* _lantern_Tensor_symeig_tensor_bool_bool(void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(from_raw::Tensor(self).symeig( - from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - -void* _lantern__symeig_helper_tensor_bool_bool(void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_symeig_helper( - from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - void* _lantern_svd_out_tensor_tensor_tensor_tensor_bool_bool(void* U, void* S, void* V, void* self, void* some, void* compute_uv) { LANTERN_FUNCTION_START @@ -16951,6 +17039,14 @@ void* _lantern_max_out_tensor_tensor_tensor(void* out, void* self, void* other) LANTERN_FUNCTION_END } +void* _lantern_max_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::max_out( + from_raw::Tensor(out), from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + void* _lantern_minimum_tensor_tensor(void* self, void* other) { LANTERN_FUNCTION_START @@ -17703,186 +17799,378 @@ void* _lantern__foreach_div__tensorlist_scalar(void* self, void* scalar) LANTERN_FUNCTION_END } -void* _lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_min_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_add( - from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); + return make_raw::TensorList(torch::_foreach_clamp_min( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_add__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_min__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_add_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_min_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sub_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_max_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_sub( - from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); + return make_raw::TensorList(torch::_foreach_clamp_max( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_sub__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_max__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_sub_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_max_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_mul_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_maximum_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_mul( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_maximum( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_mul__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_maximum__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_mul_(from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_minimum_tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_div( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_minimum( + from_raw::TensorList(self), from_raw::Scalar(scalar))); LANTERN_FUNCTION_END } -void* _lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_minimum__tensorlist_scalar(void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_div_(from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_add_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START return make_raw::TensorList(torch::_foreach_add( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); LANTERN_FUNCTION_END } -void* _lantern__foreach_add__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_add__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START - torch::_foreach_add_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_add_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sub_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_sub_tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START return make_raw::TensorList(torch::_foreach_sub( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha))); LANTERN_FUNCTION_END } -void* _lantern__foreach_sub__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_sub__tensorlist_tensorlist_scalar(void* self, void* other, void* alpha) { LANTERN_FUNCTION_START - torch::_foreach_sub_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_sub_(from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_div_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_mul_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_div( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + return make_raw::TensorList(torch::_foreach_mul( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_div__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_mul__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_div_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_mul_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_div_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_mul( - from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + return make_raw::TensorList(torch::_foreach_div( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) +void* _lantern__foreach_div__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_mul_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_div_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_exp_tensorlist(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_exp( - from_raw::TensorList(self))); - LANTERN_FUNCTION_END -} - -void* _lantern__foreach_zero__tensorlist(void* self) +void* _lantern__foreach_clamp_min_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_zero_(from_raw::TensorList(self)); - return NULL; + return make_raw::TensorList(torch::_foreach_clamp_min( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_exp__tensorlist(void* self) +void* _lantern__foreach_clamp_min__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_exp_(from_raw::TensorList(self)); + torch::_foreach_clamp_min_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sqrt_tensorlist(void* self) +void* _lantern__foreach_clamp_max_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_sqrt( - from_raw::TensorList(self))); + return make_raw::TensorList(torch::_foreach_clamp_max( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_sqrt__tensorlist(void* self) +void* _lantern__foreach_clamp_max__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_sqrt_(from_raw::TensorList(self)); + torch::_foreach_clamp_max_(from_raw::TensorList(self), from_raw::TensorList(other)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_abs_tensorlist(void* self) +void* _lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_abs( - from_raw::TensorList(self))); + return make_raw::TensorList(torch::_foreach_maximum( + from_raw::TensorList(self), from_raw::TensorList(other))); LANTERN_FUNCTION_END } -void* _lantern__foreach_abs__tensorlist(void* self) +void* _lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) { LANTERN_FUNCTION_START - torch::_foreach_abs_(from_raw::TensorList(self)); + torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_minimum( + from_raw::TensorList(self), from_raw::TensorList(other))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_add_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_add( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_add__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_add_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sub_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_sub( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sub__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_sub_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_div_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_div( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_div__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_div_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_mul_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_mul( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_mul__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_mul_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_min_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_clamp_min( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_min__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_min_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_clamp_max( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_max_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_maximum( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_minimum( + from_raw::TensorList(self), from_raw::vector::Scalar(scalars))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum__tensorlist_arrayrefscalar(void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_exp_tensorlist(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_exp( + from_raw::TensorList(self))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_zero__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_zero_(from_raw::TensorList(self)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_exp__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_exp_(from_raw::TensorList(self)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sqrt_tensorlist(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_sqrt( + from_raw::TensorList(self))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sqrt__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_sqrt_(from_raw::TensorList(self)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_abs_tensorlist(void* self) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_abs( + from_raw::TensorList(self))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_abs__tensorlist(void* self) +{ + LANTERN_FUNCTION_START + torch::_foreach_abs_(from_raw::TensorList(self)); return NULL; LANTERN_FUNCTION_END } @@ -18311,6 +18599,14 @@ void* _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_arrayrefscalar LANTERN_FUNCTION_END } +void* _lantern__foreach_addcdiv__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_addcdiv_(from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START @@ -18319,6 +18615,14 @@ void* _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_arrayrefscalar LANTERN_FUNCTION_END } +void* _lantern__foreach_addcmul__tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_addcmul_(from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_scalar(void* self, void* tensor1, void* tensor2, void* value) { LANTERN_FUNCTION_START @@ -18343,6 +18647,14 @@ void* _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_arrayrefscalar( LANTERN_FUNCTION_END } +void* _lantern__foreach_addcdiv_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) +{ + LANTERN_FUNCTION_START + return make_raw::TensorList(torch::_foreach_addcdiv( + from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars))); + LANTERN_FUNCTION_END +} + void* _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START @@ -18351,43 +18663,51 @@ void* _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_arrayrefscalar( LANTERN_FUNCTION_END } -void* _lantern__foreach_maximum_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_addcmul_tensorlist_tensorlist_tensorlist_tensor(void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_maximum( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_addcmul( + from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars))); LANTERN_FUNCTION_END } -void* _lantern__foreach_maximum__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) { LANTERN_FUNCTION_START - torch::_foreach_maximum_(from_raw::TensorList(self), from_raw::TensorList(other)); - return NULL; + return make_raw::TensorList(torch::_foreach_norm( + from_raw::TensorList(self), from_raw::Scalar(ord))); LANTERN_FUNCTION_END } -void* _lantern__foreach_minimum_tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_lerp_tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_minimum( - from_raw::TensorList(self), from_raw::TensorList(other))); + return make_raw::TensorList(torch::_foreach_lerp( + from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::TensorList(weights))); LANTERN_FUNCTION_END } -void* _lantern__foreach_minimum__tensorlist_tensorlist(void* self, void* other) +void* _lantern__foreach_lerp__tensorlist_tensorlist_tensorlist(void* self, void* tensors1, void* weights) { LANTERN_FUNCTION_START - torch::_foreach_minimum_(from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_lerp_(from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::TensorList(weights)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_norm_tensorlist_scalar(void* self, void* ord) +void* _lantern__foreach_lerp_tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) { LANTERN_FUNCTION_START - return make_raw::TensorList(torch::_foreach_norm( - from_raw::TensorList(self), from_raw::Scalar(ord))); + return make_raw::TensorList(torch::_foreach_lerp( + from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::Scalar(weight))); + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_lerp__tensorlist_tensorlist_scalar(void* self, void* tensors1, void* weight) +{ + LANTERN_FUNCTION_START + torch::_foreach_lerp_(from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::Scalar(weight)); + return NULL; LANTERN_FUNCTION_END } @@ -18423,14 +18743,6 @@ void* _lantern_searchsorted_tensor_tensor_bool_bool_cstringview_tensor(void* sor LANTERN_FUNCTION_END } -void* _lantern__torch_cuda_cu_linker_symbol_op_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_torch_cuda_cu_linker_symbol_op( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - void* _lantern_searchsorted_out_tensor_tensor_tensor_bool_bool_cstringview_tensor(void* out, void* sorted_sequence, void* self, void* out_int32, void* right, void* side, void* sorter) { LANTERN_FUNCTION_START @@ -19791,14 +20103,6 @@ void* _lantern_upsample_linear1d_tensor_intarrayref_bool_arrayrefdouble(void* in LANTERN_FUNCTION_END } -void* _lantern_upsample_linear1d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_linear1d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START @@ -19807,78 +20111,38 @@ void* _lantern_upsample_bilinear2d_tensor_intarrayref_bool_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_bilinear2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bilinear2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_upsample_bilinear2d_aa( + from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa( + return make_raw::Tensor(torch::upsample_trilinear3d( from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::upsample_bicubic2d( + from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d( + return make_raw::Tensor(torch::_upsample_bicubic2d_aa( from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern_upsample_bicubic2d_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d( - from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern_upsample_bicubic2d_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_bicubic2d_aa_tensor_intarrayref_bool_arrayrefdouble(void* input, void* output_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa( - from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_bicubic2d_aa_backward_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_nearest1d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_FUNCTION_START @@ -19895,22 +20159,6 @@ void* _lantern__upsample_nearest_exact1d_tensor_intarrayref_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest1d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_nearest_exact1d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact1d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_nearest2d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_FUNCTION_START @@ -19927,22 +20175,6 @@ void* _lantern__upsample_nearest_exact2d_tensor_intarrayref_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_nearest_exact2d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact2d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_nearest3d_tensor_intarrayref_arrayrefdouble(void* input, void* output_size, void* scale_factors) { LANTERN_FUNCTION_START @@ -19959,22 +20191,6 @@ void* _lantern__upsample_nearest_exact3d_tensor_intarrayref_arrayrefdouble(void* LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest3d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - -void* _lantern__upsample_nearest_exact3d_backward_tensor_intarrayref_intarrayref_arrayrefdouble(void* grad_output, void* output_size, void* input_size, void* scale_factors) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact3d_backward( - from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); - LANTERN_FUNCTION_END -} - void* _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_double(void* out, void* self, void* output_size, void* align_corners, void* scales) { LANTERN_FUNCTION_START @@ -22911,6 +23127,14 @@ void* _lantern_squeeze_copy_tensor_intt(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_squeeze_copy_tensor_intarrayref(void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::squeeze_copy( + from_raw::Tensor(self), from_raw::IntArrayRef(dim))); + LANTERN_FUNCTION_END +} + void* _lantern_t_copy_tensor(void* self) { LANTERN_FUNCTION_START @@ -23007,6 +23231,30 @@ void* _lantern_unbind_copy_tensor_intt(void* self, void* dim) LANTERN_FUNCTION_END } +void* _lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) +{ + LANTERN_FUNCTION_START + torch::unbind_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(dim)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) +{ + LANTERN_FUNCTION_START + torch::split_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(split_size), from_raw::int64_t(dim)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) +{ + LANTERN_FUNCTION_START + torch::split_with_sizes_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::IntArrayRef(split_sizes), from_raw::int64_t(dim)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern_view_copy_tensor_intarrayref(void* self, void* size) { LANTERN_FUNCTION_START @@ -23039,463 +23287,263 @@ void* _lantern_alias_copy_tensor(void* self) LANTERN_FUNCTION_END } -void* _lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) +void* _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_fw_primal_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(level))); + return make_raw::Tensor(from_raw::Tensor(self).to_padded_tensor( + from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); LANTERN_FUNCTION_END } -void* _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) +void* _lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_make_dual_copy_out( - from_raw::Tensor(out), from_raw::Tensor(primal), from_raw::Tensor(tangent), from_raw::int64_t(level))); + return make_raw::Tensor(torch::_nested_tensor_softmax_with_shape( + from_raw::Tensor(self), from_raw::Tensor(query))); LANTERN_FUNCTION_END } -void* _lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_as_real_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::_transformer_encoder_layer_fwd( + from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::int64_t(mask_type))); LANTERN_FUNCTION_END } -void* _lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_as_complex_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_native_multi_head_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights), from_raw::optional::int64_t(mask_type))); LANTERN_FUNCTION_END } -void* _lantern__conj_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_conj_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::scaled_dot_product_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_neg_view_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_scaled_dot_product_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) +void* _lantern__fused_sdp_choice_tensor_tensor_tensor_tensor_double_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::as_strided_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride), from_raw::optional::int64_t(storage_offset))); + return make_raw::int64_t(torch::_fused_sdp_choice( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) +void* _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_tensor(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* is_causal, void* dropout_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_broadcast_to_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); + return make_raw::tuple(torch::_scaled_dot_product_attention_math( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::optional::Tensor(dropout_mask))); LANTERN_FUNCTION_END } -void* _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) +void* _lantern__scaled_dot_product_flash_attention_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::diagonal_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(offset), from_raw::int64_t(dim1), from_raw::int64_t(dim2))); + return make_raw::tuple(torch::_scaled_dot_product_flash_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::bool_t(return_debug_mask))); LANTERN_FUNCTION_END } -void* _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) +void* _lantern__scaled_dot_product_flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::expand_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::bool_t(implicit))); + return make_raw::tuple(torch::_scaled_dot_product_flash_attention_backward( + from_raw::Tensor(grad_out), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::int64_t(philox_seed), from_raw::int64_t(philox_offset))); LANTERN_FUNCTION_END } -void* _lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) +void* _lantern__scaled_dot_product_efficient_attention_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* compute_log_sumexp, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::permute_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(dims))); + return make_raw::tuple(torch::_scaled_dot_product_efficient_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::bool_t(compute_log_sumexp), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) +void* _lantern__scaled_dot_product_efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_reshape_alias_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride))); + return make_raw::tuple(torch::_scaled_dot_product_efficient_attention_backward( + from_raw::Tensor(grad_out_), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::bool_t(is_causal), from_raw::bool_t(chunk_grad_outputs))); LANTERN_FUNCTION_END } -void* _lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) +void* _lantern__chunk_grad_outputs_efficient_attention_tensor_tensor_tensor_bool(void* query, void* key, void* value, void* is_causal) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::select_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::int64_t(index))); + return make_raw::bool_t(torch::_chunk_grad_outputs_efficient_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::bool_t(is_causal))); LANTERN_FUNCTION_END } -void* _lantern_detach_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__flash_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* return_debug_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::detach_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_flash_attention_forward( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::bool_t(return_debug_mask))); LANTERN_FUNCTION_END } -void* _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) +void* _lantern__flash_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool_intt_intt(void* grad_out, void* query, void* key, void* value, void* out, void* logsumexp, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal, void* philox_seed, void* philox_offset) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::slice_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::optional::int64_t(start), from_raw::optional::int64_t(end), from_raw::int64_t(step))); + return make_raw::tuple(torch::_flash_attention_backward( + from_raw::Tensor(grad_out), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal), from_raw::int64_t(philox_seed), from_raw::int64_t(philox_offset))); LANTERN_FUNCTION_END } -void* _lantern_split_copy_out_tensorlist_tensor_intt_intt(void* out, void* self, void* split_size, void* dim) +void* _lantern__efficient_attention_forward_tensor_tensor_tensor_tensor_tensor_intt_bool_bool(void* query, void* key, void* value, void* cu_seqlens_q, void* cu_seqlens_k, void* max_seqlen_q, void* compute_log_sumexp, void* causal) { LANTERN_FUNCTION_START - torch::split_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(split_size), from_raw::int64_t(dim)); - return NULL; + return make_raw::tuple(torch::_efficient_attention_forward( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(cu_seqlens_q), from_raw::optional::Tensor(cu_seqlens_k), from_raw::optional::int64_t(max_seqlen_q), from_raw::bool_t(compute_log_sumexp), from_raw::bool_t(causal))); LANTERN_FUNCTION_END } -void* _lantern_split_with_sizes_copy_out_tensorlist_tensor_intarrayref_intt(void* out, void* self, void* split_sizes, void* dim) +void* _lantern__efficient_attention_backward_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* grad_out_, void* query, void* key, void* value, void* out, void* logsumexp, void* is_causal, void* chunk_grad_outputs) { LANTERN_FUNCTION_START - torch::split_with_sizes_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::IntArrayRef(split_sizes), from_raw::int64_t(dim)); - return NULL; + return make_raw::tuple(torch::_efficient_attention_backward( + from_raw::Tensor(grad_out_), from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(out), from_raw::Tensor(logsumexp), from_raw::bool_t(is_causal), from_raw::bool_t(chunk_grad_outputs))); LANTERN_FUNCTION_END } -void* _lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::squeeze_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::_triton_scaled_dot_attention( + from_raw::Tensor(q), from_raw::Tensor(k), from_raw::Tensor(v), from_raw::double_t(dropout_p))); LANTERN_FUNCTION_END } -void* _lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) +void* _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::squeeze_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); + return make_raw::Tensor(torch::_triton_multi_head_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask))); LANTERN_FUNCTION_END } -void* _lantern_t_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_airy_ai_tensor(void* x) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::t_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_airy_ai( + from_raw::Tensor(x))); LANTERN_FUNCTION_END } -void* _lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) +void* _lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::transpose_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim0), from_raw::int64_t(dim1))); + return make_raw::Tensor(torch::special_airy_ai_out( + from_raw::Tensor(out), from_raw::Tensor(x))); LANTERN_FUNCTION_END } -void* _lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) +void* _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::unsqueeze_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); + return make_raw::tuple(torch::_transformer_decoder_only_layer_fwd( + from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value))); LANTERN_FUNCTION_END } -void* _lantern__indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_indices_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::tuple(torch::_native_decoder_only_multi_head_attention( + from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights))); LANTERN_FUNCTION_END } -void* _lantern__values_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j0_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_values_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_bessel_j0( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j0_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::indices_copy_out( + return make_raw::Tensor(torch::special_bessel_j0_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_values_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j1_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::values_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_bessel_j1( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_j1_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::crow_indices_copy_out( + return make_raw::Tensor(torch::special_bessel_j1_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_special_bessel_y0_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::col_indices_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + return make_raw::Tensor(torch::special_bessel_y0( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_unbind_copy_out_tensorlist_tensor_intt(void* out, void* self, void* dim) +void* _lantern_special_bessel_y0_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - torch::unbind_copy_out(from_raw::TensorList(out), from_raw::Tensor(self), from_raw::int64_t(dim)); - return NULL; + return make_raw::Tensor(torch::special_bessel_y0_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) +void* _lantern_special_bessel_y1_tensor(void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); + return make_raw::Tensor(torch::special_bessel_y1( + from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) +void* _lantern_special_bessel_y1_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::view_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::ScalarType(dtype))); + return make_raw::Tensor(torch::special_bessel_y1_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) +void* _lantern_special_chebyshev_polynomial_t_tensor_tensor(void* x, void* n) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::unfold_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dimension), from_raw::int64_t(size), from_raw::int64_t(step))); + return make_raw::Tensor(torch::special_chebyshev_polynomial_t( + from_raw::Tensor(x), from_raw::Tensor(n))); LANTERN_FUNCTION_END } -void* _lantern_alias_copy_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::alias_copy_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_Tensor_to_padded_tensor_tensor_double_intarrayref(void* self, void* padding, void* output_size) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(from_raw::Tensor(self).to_padded_tensor( - from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); - LANTERN_FUNCTION_END -} - -void* _lantern__nested_tensor_softmax_with_shape_tensor_tensor(void* self, void* query) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_nested_tensor_softmax_with_shape( - from_raw::Tensor(self), from_raw::Tensor(query))); - LANTERN_FUNCTION_END -} - -void* _lantern_Tensor__nested_tensor_layer_norm_tensor_tensor_tensor_double(void* self, void* weight, void* bias, void* eps) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(from_raw::Tensor(self)._nested_tensor_layer_norm( - from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::double_t(eps))); - LANTERN_FUNCTION_END -} - -void* _lantern__transformer_encoder_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_intt(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* mask_type) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_transformer_encoder_layer_fwd( - from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::int64_t(mask_type))); - LANTERN_FUNCTION_END -} - -void* _lantern__native_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_bool_bool_intt(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* need_weights, void* average_attn_weights, void* mask_type) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_native_multi_head_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights), from_raw::optional::int64_t(mask_type))); - LANTERN_FUNCTION_END -} - -void* _lantern__scaled_dot_product_attention_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_scaled_dot_product_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__scaled_dot_product_attention_forward_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_scaled_dot_product_attention_forward( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__scaled_dot_product_attention_math_tensor_tensor_tensor_tensor_double_bool_bool(void* query, void* key, void* value, void* attn_mask, void* dropout_p, void* need_attn_weights, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_scaled_dot_product_attention_math( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::optional::Tensor(attn_mask), from_raw::double_t(dropout_p), from_raw::bool_t(need_attn_weights), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__triton_scaled_dot_attention_tensor_tensor_tensor_double(void* q, void* k, void* v, void* dropout_p) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_triton_scaled_dot_attention( - from_raw::Tensor(q), from_raw::Tensor(k), from_raw::Tensor(v), from_raw::double_t(dropout_p))); - LANTERN_FUNCTION_END -} - -void* _lantern__triton_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_triton_multi_head_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_airy_ai_tensor(void* x) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_airy_ai( - from_raw::Tensor(x))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_airy_ai_out_tensor_tensor(void* out, void* x) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_airy_ai_out( - from_raw::Tensor(out), from_raw::Tensor(x))); - LANTERN_FUNCTION_END -} - -void* _lantern__flash_scaled_dot_product_attention_tensor_tensor_tensor_tensor_tensor_intt_intt_double_bool(void* query, void* key, void* value, void* cum_seq_q, void* cum_seq_k, void* max_q, void* max_k, void* dropout_p, void* is_causal) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_flash_scaled_dot_product_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::Tensor(cum_seq_q), from_raw::Tensor(cum_seq_k), from_raw::int64_t(max_q), from_raw::int64_t(max_k), from_raw::double_t(dropout_p), from_raw::bool_t(is_causal))); - LANTERN_FUNCTION_END -} - -void* _lantern__transformer_decoder_only_layer_fwd_tensor_intt_intt_tensor_tensor_tensor_tensor_bool_bool_double_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor(void* src, void* embed_dim, void* num_heads, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* use_gelu, void* norm_first, void* eps, void* norm_weight_1, void* norm_bias_1, void* norm_weight_2, void* norm_bias_2, void* ffn_weight_1, void* ffn_bias_1, void* ffn_weight_2, void* ffn_bias_2, void* mask, void* incr_key, void* incr_value) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_transformer_decoder_only_layer_fwd( - from_raw::Tensor(src), from_raw::int64_t(embed_dim), from_raw::int64_t(num_heads), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::bool_t(use_gelu), from_raw::bool_t(norm_first), from_raw::double_t(eps), from_raw::Tensor(norm_weight_1), from_raw::Tensor(norm_bias_1), from_raw::Tensor(norm_weight_2), from_raw::Tensor(norm_bias_2), from_raw::Tensor(ffn_weight_1), from_raw::Tensor(ffn_bias_1), from_raw::Tensor(ffn_weight_2), from_raw::Tensor(ffn_bias_2), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value))); - LANTERN_FUNCTION_END -} - -void* _lantern__native_decoder_only_multi_head_attention_tensor_tensor_tensor_intt_intt_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_bool(void* query, void* key, void* value, void* embed_dim, void* num_head, void* qkv_weight, void* qkv_bias, void* proj_weight, void* proj_bias, void* mask, void* incr_key, void* incr_value, void* need_weights, void* average_attn_weights) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_native_decoder_only_multi_head_attention( - from_raw::Tensor(query), from_raw::Tensor(key), from_raw::Tensor(value), from_raw::int64_t(embed_dim), from_raw::int64_t(num_head), from_raw::Tensor(qkv_weight), from_raw::Tensor(qkv_bias), from_raw::Tensor(proj_weight), from_raw::Tensor(proj_bias), from_raw::optional::Tensor(mask), from_raw::optional::Tensor(incr_key), from_raw::optional::Tensor(incr_value), from_raw::bool_t(need_weights), from_raw::bool_t(average_attn_weights))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j0_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j0( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j0_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j0_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j1_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j1( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_j1_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_j1_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y0_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y0( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y0_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y0_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y1_tensor(void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y1( - from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_bessel_y1_out_tensor_tensor(void* out, void* self) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_bessel_y1_out( - from_raw::Tensor(out), from_raw::Tensor(self))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_chebyshev_polynomial_t_tensor_tensor(void* x, void* n) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::special_chebyshev_polynomial_t( - from_raw::Tensor(x), from_raw::Tensor(n))); - LANTERN_FUNCTION_END -} - -void* _lantern_special_chebyshev_polynomial_t_scalar_tensor(void* x, void* n) +void* _lantern_special_chebyshev_polynomial_t_scalar_tensor(void* x, void* n) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::special_chebyshev_polynomial_t( @@ -24191,6 +24239,14 @@ void* _lantern__fused_adam__tensorlist_tensorlist_tensorlist_tensorlist_tensorli LANTERN_FUNCTION_END } +void* _lantern__fused_adamw__tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) +{ + LANTERN_FUNCTION_START + torch::_fused_adamw_(from_raw::TensorList(self), from_raw::TensorList(grads), from_raw::TensorList(exp_avgs), from_raw::TensorList(exp_avg_sqs), from_raw::TensorList(max_exp_avg_sqs), from_raw::TensorList(state_steps), from_raw::double_t(lr), from_raw::double_t(beta1), from_raw::double_t(beta2), from_raw::double_t(weight_decay), from_raw::double_t(eps), from_raw::bool_t(amsgrad), from_raw::bool_t(maximize), from_raw::optional::Tensor(grad_scale), from_raw::optional::Tensor(found_inf)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__new_zeros_with_same_feature_meta_out_tensor_tensor_tensor_intt(void* out, void* self, void* other, void* self_num_batch_dims) { LANTERN_FUNCTION_START @@ -24591,6 +24647,14 @@ void* _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref LANTERN_FUNCTION_END } +void* _lantern__ctc_loss_out_tensor_tensor_tensor_tensor_tensor_tensor_intt_bool(void* out0, void* out1, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* blank, void* zero_infinity) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_ctc_loss_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(log_probs), from_raw::Tensor(targets), from_raw::Tensor(input_lengths), from_raw::Tensor(target_lengths), from_raw::int64_t(blank), from_raw::bool_t(zero_infinity))); + LANTERN_FUNCTION_END +} + void* _lantern__ctc_loss_backward_out_tensor_tensor_tensor_tensor_intarrayref_intarrayref_tensor_tensor_intt_bool(void* out, void* grad, void* log_probs, void* targets, void* input_lengths, void* target_lengths, void* neg_log_likelihood, void* log_alpha, void* blank, void* zero_infinity) { LANTERN_FUNCTION_START @@ -25095,18 +25159,10 @@ void* _lantern__aminmax_out_tensor_tensor_tensor_intt_bool(void* out0, void* out LANTERN_FUNCTION_END } -void* _lantern__mps_max_pool2d_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_mps_max_pool2d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); - LANTERN_FUNCTION_END -} - -void* _lantern_mps_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) +void* _lantern_max_pool2d_backward_out_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_intarrayref_bool(void* out, void* grad_output, void* self, void* kernel_size, void* stride, void* padding, void* dilation, void* ceil_mode) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::mps_max_pool2d_backward_out( + return make_raw::Tensor(torch::max_pool2d_backward_out( from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation), from_raw::bool_t(ceil_mode))); LANTERN_FUNCTION_END } @@ -25199,6 +25255,22 @@ void* _lantern_mkldnn_convolution_out_tensor_tensor_tensor_tensor_intarrayref_in LANTERN_FUNCTION_END } +void* _lantern_mkldnn_rnn_layer_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intarrayref_intt_intt_intt_bool_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* input, void* weight0, void* weight1, void* weight2, void* weight3, void* hx_, void* cx_, void* reverse, void* batch_sizes, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* bidirectional, void* batch_first, void* train) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(input), from_raw::Tensor(weight0), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(hx_), from_raw::Tensor(cx_), from_raw::bool_t(reverse), from_raw::IntArrayRef(batch_sizes), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first), from_raw::bool_t(train))); + LANTERN_FUNCTION_END +} + +void* _lantern_mkldnn_rnn_layer_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_intt_intt_intt_bool_bool_bool_intarrayref_bool_tensor(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* out6, void* input, void* weight1, void* weight2, void* weight3, void* weight4, void* hx_, void* cx_tmp, void* output, void* hy_, void* cy_, void* grad_output, void* grad_hy, void* grad_cy, void* reverse, void* mode, void* hidden_size, void* num_layers, void* has_biases, void* train, void* bidirectional, void* batch_sizes, void* batch_first, void* workspace) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::mkldnn_rnn_layer_backward_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(out4), from_raw::Tensor(out5), from_raw::Tensor(out6), from_raw::Tensor(input), from_raw::Tensor(weight1), from_raw::Tensor(weight2), from_raw::Tensor(weight3), from_raw::Tensor(weight4), from_raw::Tensor(hx_), from_raw::Tensor(cx_tmp), from_raw::Tensor(output), from_raw::Tensor(hy_), from_raw::Tensor(cy_), from_raw::optional::Tensor(grad_output), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::bool_t(reverse), from_raw::int64_t(mode), from_raw::int64_t(hidden_size), from_raw::int64_t(num_layers), from_raw::bool_t(has_biases), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::IntArrayRef(batch_sizes), from_raw::bool_t(batch_first), from_raw::Tensor(workspace))); + LANTERN_FUNCTION_END +} + void* _lantern_miopen_batch_norm_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* out0, void* out1, void* out2, void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* exponential_average_factor, void* epsilon) { LANTERN_FUNCTION_START @@ -25263,19 +25335,19 @@ void* _lantern__sparse_sparse_matmul_out_tensor_tensor_tensor(void* out, void* s LANTERN_FUNCTION_END } -void* _lantern__sparse_mask_helper_out_tensor_tensor_tensor(void* out, void* t, void* mask_indices) +void* _lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_sparse_mask_helper_out( - from_raw::Tensor(out), from_raw::Tensor(t), from_raw::Tensor(mask_indices))); + return make_raw::Tensor(torch::mul_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Scalar(other))); LANTERN_FUNCTION_END } -void* _lantern_mul_out_tensor_tensor_scalar(void* out, void* self, void* other) +void* _lantern__native_batch_norm_legit_functional_tensor_tensor_tensor_tensor_tensor_bool_double_double(void* input, void* weight, void* bias, void* running_mean, void* running_var, void* training, void* momentum, void* eps) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::mul_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Scalar(other))); + return make_raw::tuple(torch::_native_batch_norm_legit_functional( + from_raw::Tensor(input), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::Tensor(running_mean), from_raw::Tensor(running_var), from_raw::bool_t(training), from_raw::double_t(momentum), from_raw::double_t(eps))); LANTERN_FUNCTION_END } @@ -25535,22 +25607,6 @@ void* _lantern_relu_out_tensor_tensor(void* out, void* self) LANTERN_FUNCTION_END } -void* _lantern_prelu_out_tensor_tensor_tensor(void* out, void* self, void* weight) -{ - LANTERN_FUNCTION_START - return make_raw::Tensor(torch::prelu_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight))); - LANTERN_FUNCTION_END -} - -void* _lantern_prelu_backward_out_tensor_tensor_tensor_tensor_tensor(void* out0, void* out1, void* grad_output, void* self, void* weight) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::prelu_backward_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight))); - LANTERN_FUNCTION_END -} - void* _lantern_select_backward_out_tensor_tensor_intarrayref_intt_intt(void* out, void* grad_output, void* input_sizes, void* dim, void* index) { LANTERN_FUNCTION_START @@ -26199,43 +26255,43 @@ void* _lantern_to_sparse_out_tensor_tensor_intt(void* out, void* self, void* spa LANTERN_FUNCTION_END } -void* _lantern_to_sparse_out_tensor_tensor(void* out, void* self) +void* _lantern_to_sparse_out_tensor_tensor_layout_intarrayref_intt(void* out, void* self, void* layout, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::Layout(layout), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_csr_out_tensor_tensor(void* out, void* self) +void* _lantern_to_sparse_csr_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_csr_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_csc_out_tensor_tensor(void* out, void* self) +void* _lantern_to_sparse_csc_out_tensor_tensor_intt(void* out, void* self, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_csc_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) +void* _lantern_to_sparse_bsr_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_bsr_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } -void* _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref(void* out, void* self, void* blocksize) +void* _lantern_to_sparse_bsc_out_tensor_tensor_intarrayref_intt(void* out, void* self, void* blocksize, void* dense_dim) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::to_sparse_bsc_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(blocksize), from_raw::optional::int64_t(dense_dim))); LANTERN_FUNCTION_END } @@ -26247,11 +26303,11 @@ void* _lantern_to_mkldnn_out_tensor_tensor_scalartype(void* out, void* self, voi LANTERN_FUNCTION_END } -void* _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt(void* out, void* self, void* padding, void* stride, void* dilation, void* groups) +void* _lantern_mkldnn_reorder_conv2d_weight_out_tensor_tensor_intarrayref_intarrayref_intarrayref_intt_intarrayref(void* out, void* self, void* padding, void* stride, void* dilation, void* groups, void* input_size) { LANTERN_FUNCTION_START return make_raw::Tensor(torch::mkldnn_reorder_conv2d_weight_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups))); + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(dilation), from_raw::int64_t(groups), from_raw::IntArrayRef(input_size))); LANTERN_FUNCTION_END } @@ -26423,18 +26479,18 @@ void* _lantern__to_copy_out_tensor_tensor_bool_memoryformat(void* out, void* sel LANTERN_FUNCTION_END } -void* _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) +void* _lantern__lstm_mps_out_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* out3, void* out4, void* out5, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_FUNCTION_START return make_raw::tuple(torch::_lstm_mps_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(out4), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(out3), from_raw::Tensor(out4), from_raw::Tensor(out5), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first))); LANTERN_FUNCTION_END } -void* _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) +void* _lantern_lstm_mps_backward_out_tensor_tensorlist_tensorlist_tensor_tensor_tensor_tensor_tensor_tensor_tensor_tensorlist_tensorlist_bool_intt_double_bool_bool_bool(void* out0, void* out1, void* out2, void* grad_y, void* grad_hy, void* grad_cy, void* z_state, void* cell_state_fwd, void* input, void* layersOutputs, void* hx, void* params, void* has_biases, void* num_layers, void* dropout, void* train, void* bidirectional, void* batch_first) { LANTERN_FUNCTION_START - torch::lstm_mps_backward_out(from_raw::Tensor(out0), from_raw::TensorList(out1), from_raw::TensorList(out2), from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first)); + torch::lstm_mps_backward_out(from_raw::Tensor(out0), from_raw::TensorList(out1), from_raw::TensorList(out2), from_raw::Tensor(grad_y), from_raw::optional::Tensor(grad_hy), from_raw::optional::Tensor(grad_cy), from_raw::Tensor(z_state), from_raw::Tensor(cell_state_fwd), from_raw::Tensor(input), from_raw::Tensor(layersOutputs), from_raw::TensorList(hx), from_raw::TensorList(params), from_raw::bool_t(has_biases), from_raw::int64_t(num_layers), from_raw::double_t(dropout), from_raw::bool_t(train), from_raw::bool_t(bidirectional), from_raw::bool_t(batch_first)); return NULL; LANTERN_FUNCTION_END } @@ -26847,14 +26903,6 @@ void* _lantern_trace_out_tensor_tensor(void* out, void* self) LANTERN_FUNCTION_END } -void* _lantern__symeig_helper_out_tensor_tensor_tensor_bool_bool(void* out0, void* out1, void* self, void* eigenvectors, void* upper) -{ - LANTERN_FUNCTION_START - return make_raw::tuple(torch::_symeig_helper_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(self), from_raw::bool_t(eigenvectors), from_raw::bool_t(upper))); - LANTERN_FUNCTION_END -} - void* _lantern__cholesky_solve_helper_out_tensor_tensor_tensor_bool(void* out, void* self, void* A, void* upper) { LANTERN_FUNCTION_START @@ -26991,42 +27039,106 @@ void* _lantern__foreach_div_out_tensorlist_tensorlist_scalar(void* out, void* se LANTERN_FUNCTION_END } -void* _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_min_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_min_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) +void* _lantern__foreach_clamp_max_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_sub_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + torch::_foreach_clamp_max_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_maximum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_mul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_minimum_out_tensorlist_tensorlist_scalar(void* out, void* self, void* scalar) { LANTERN_FUNCTION_START - torch::_foreach_div_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::Scalar(scalar)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +void* _lantern__foreach_add_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) { LANTERN_FUNCTION_START - torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_sub_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* other, void* alpha) +{ + LANTERN_FUNCTION_START + torch::_foreach_sub_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other), from_raw::Scalar(alpha)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_mul_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_mul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_div_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_div_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_min_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_min_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_max_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_add_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_add_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); return NULL; LANTERN_FUNCTION_END } @@ -27055,6 +27167,38 @@ void* _lantern__foreach_mul_out_tensorlist_tensorlist_arrayrefscalar(void* out, LANTERN_FUNCTION_END } +void* _lantern__foreach_clamp_min_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_min_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_clamp_max_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_clamp_max_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_maximum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__foreach_minimum_out_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* scalars) +{ + LANTERN_FUNCTION_START + torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::vector::Scalar(scalars)); + return NULL; + LANTERN_FUNCTION_END +} + void* _lantern__foreach_exp_out_tensorlist_tensorlist(void* out, void* self) { LANTERN_FUNCTION_START @@ -27319,26 +27463,26 @@ void* _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_ LANTERN_FUNCTION_END } -void* _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) +void* _lantern__foreach_addcdiv_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - torch::_foreach_addcmul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::vector::Scalar(scalars)); + torch::_foreach_addcdiv_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_maximum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_arrayrefscalar(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - torch::_foreach_maximum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_addcmul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::vector::Scalar(scalars)); return NULL; LANTERN_FUNCTION_END } -void* _lantern__foreach_minimum_out_tensorlist_tensorlist_tensorlist(void* out, void* self, void* other) +void* _lantern__foreach_addcmul_out_tensorlist_tensorlist_tensorlist_tensorlist_tensor(void* out, void* self, void* tensor1, void* tensor2, void* scalars) { LANTERN_FUNCTION_START - torch::_foreach_minimum_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(other)); + torch::_foreach_addcmul_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensor1), from_raw::TensorList(tensor2), from_raw::Tensor(scalars)); return NULL; LANTERN_FUNCTION_END } @@ -27351,19 +27495,27 @@ void* _lantern__foreach_norm_out_tensorlist_tensorlist_scalar(void* out, void* s LANTERN_FUNCTION_END } -void* _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) +void* _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_tensorlist(void* out, void* self, void* tensors1, void* weights) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::bucketize_out( - from_raw::Tensor(out), from_raw::Scalar(self), from_raw::Tensor(boundaries), from_raw::bool_t(out_int32), from_raw::bool_t(right))); + torch::_foreach_lerp_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::TensorList(weights)); + return NULL; LANTERN_FUNCTION_END } -void* _lantern__torch_cuda_cu_linker_symbol_op_out_tensor_tensor(void* out, void* self) +void* _lantern__foreach_lerp_out_tensorlist_tensorlist_tensorlist_scalar(void* out, void* self, void* tensors1, void* weight) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_torch_cuda_cu_linker_symbol_op_out( - from_raw::Tensor(out), from_raw::Tensor(self))); + torch::_foreach_lerp_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(tensors1), from_raw::Scalar(weight)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern_bucketize_out_tensor_scalar_tensor_bool_bool(void* out, void* self, void* boundaries, void* out_int32, void* right) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::bucketize_out( + from_raw::Tensor(out), from_raw::Scalar(self), from_raw::Tensor(boundaries), from_raw::bool_t(out_int32), from_raw::bool_t(right))); LANTERN_FUNCTION_END } @@ -27447,315 +27599,339 @@ void* _lantern__adaptive_avg_pool3d_backward_out_tensor_tensor_tensor(void* out, LANTERN_FUNCTION_END } -void* _lantern_upsample_linear1d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_linear1d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::tuple(torch::_slow_conv2d_backward_out( + from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::vector::bool_t(output_mask))); LANTERN_FUNCTION_END } -void* _lantern_upsample_linear1d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_linear1d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::conv_depthwise3d_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bilinear2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bilinear2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::slow_conv_dilated2d_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bilinear2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bilinear2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::slow_conv_dilated3d_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern_isinf_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::isinf_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bilinear2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern_linalg_matrix_exp_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bilinear2d_aa_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::linalg_matrix_exp_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__test_optional_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_optional_intlist_out( + from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); LANTERN_FUNCTION_END } -void* _lantern_upsample_trilinear3d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_trilinear3d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_optional_filled_intlist_out( + from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bicubic2d_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(void* out, void* values, void* addends) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_optional_floatlist_out( + from_raw::Tensor(out), from_raw::Tensor(values), from_raw::optional::DoubleArrayRef(addends))); LANTERN_FUNCTION_END } -void* _lantern_upsample_bicubic2d_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__test_warn_in_autograd_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_bicubic2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_warn_in_autograd_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bicubic2d_aa_out_tensor_tensor_intarrayref_bool_arrayrefdouble(void* out, void* input, void* output_size, void* align_corners, void* scale_factors) +void* _lantern__test_autograd_multiple_dispatch_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_bicubic2d_aa_backward_out_tensor_tensor_intarrayref_intarrayref_bool_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* align_corners, void* scale_factors) +void* _lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_bicubic2d_aa_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::bool_t(align_corners), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(void* out, void* data, void* reduce, void* lengths, void* indices, void* offsets, void* axis, void* unsafe, void* initial) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest1d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::segment_reduce_out( + from_raw::Tensor(out), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(indices), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::bool_t(unsafe), from_raw::optional::Scalar(initial))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact1d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact1d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_segment_reduce_backward_out( + from_raw::Tensor(out), from_raw::Tensor(grad), from_raw::Tensor(output), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::optional::Scalar(initial))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest1d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_nested_tensor_from_tensor_list_out( + from_raw::Tensor(out), from_raw::TensorList(list), from_raw::optional::ScalarType(dtype), from_raw::optional::Layout(layout), from_raw::optional::Device(device), from_raw::optional::bool_t(pin_memory))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact1d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__fw_primal_copy_out_tensor_tensor_intt(void* out, void* self, void* level) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact1d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_fw_primal_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(level))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern__make_dual_copy_out_tensor_tensor_tensor_intt(void* out, void* primal, void* tangent, void* level) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_make_dual_copy_out( + from_raw::Tensor(out), from_raw::Tensor(primal), from_raw::Tensor(tangent), from_raw::int64_t(level))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact2d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern_view_as_real_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact2d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::view_as_real_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern_view_as_complex_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::view_as_complex_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact2d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__conj_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact2d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_conj_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern__neg_view_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest3d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_neg_view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact3d_out_tensor_tensor_intarrayref_arrayrefdouble(void* out, void* input, void* output_size, void* scale_factors) +void* _lantern_as_strided_copy_out_tensor_tensor_intarrayref_intarrayref_intt(void* out, void* self, void* size, void* stride, void* storage_offset) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact3d_out( - from_raw::Tensor(out), from_raw::Tensor(input), from_raw::IntArrayRef(output_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::as_strided_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride), from_raw::optional::int64_t(storage_offset))); LANTERN_FUNCTION_END } -void* _lantern_upsample_nearest3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern__sparse_broadcast_to_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::upsample_nearest3d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::_sparse_broadcast_to_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); LANTERN_FUNCTION_END } -void* _lantern__upsample_nearest_exact3d_backward_out_tensor_tensor_intarrayref_intarrayref_arrayrefdouble(void* out, void* grad_output, void* output_size, void* input_size, void* scale_factors) +void* _lantern_diagonal_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* offset, void* dim1, void* dim2) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_upsample_nearest_exact3d_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad_output), from_raw::IntArrayRef(output_size), from_raw::IntArrayRef(input_size), from_raw::optional::DoubleArrayRef(scale_factors))); + return make_raw::Tensor(torch::diagonal_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(offset), from_raw::int64_t(dim1), from_raw::int64_t(dim2))); LANTERN_FUNCTION_END } -void* _lantern__slow_conv2d_backward_out_tensor_tensor_tensor_tensor_tensor_tensor_intarrayref_intarrayref_intarrayref_stdarraybool(void* out0, void* out1, void* out2, void* grad_output, void* self, void* weight, void* kernel_size, void* stride, void* padding, void* output_mask) +void* _lantern_expand_copy_out_tensor_tensor_intarrayref_bool(void* out, void* self, void* size, void* implicit) { LANTERN_FUNCTION_START - return make_raw::tuple(torch::_slow_conv2d_backward_out( - from_raw::Tensor(out0), from_raw::Tensor(out1), from_raw::Tensor(out2), from_raw::Tensor(grad_output), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::vector::bool_t(output_mask))); + return make_raw::Tensor(torch::expand_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::bool_t(implicit))); LANTERN_FUNCTION_END } -void* _lantern_conv_depthwise3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) +void* _lantern_permute_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dims) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::conv_depthwise3d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); + return make_raw::Tensor(torch::permute_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(dims))); LANTERN_FUNCTION_END } -void* _lantern_slow_conv_dilated2d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) +void* _lantern__reshape_alias_copy_out_tensor_tensor_intarrayref_intarrayref(void* out, void* self, void* size, void* stride) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::slow_conv_dilated2d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); + return make_raw::Tensor(torch::_reshape_alias_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size), from_raw::IntArrayRef(stride))); LANTERN_FUNCTION_END } -void* _lantern_slow_conv_dilated3d_out_tensor_tensor_tensor_intarrayref_tensor_intarrayref_intarrayref_intarrayref(void* out, void* self, void* weight, void* kernel_size, void* bias, void* stride, void* padding, void* dilation) +void* _lantern_select_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim, void* index) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::slow_conv_dilated3d_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::Tensor(weight), from_raw::IntArrayRef(kernel_size), from_raw::optional::Tensor(bias), from_raw::IntArrayRef(stride), from_raw::IntArrayRef(padding), from_raw::IntArrayRef(dilation))); + return make_raw::Tensor(torch::select_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::int64_t(index))); LANTERN_FUNCTION_END } -void* _lantern_isinf_out_tensor_tensor(void* out, void* self) +void* _lantern_detach_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::isinf_out( + return make_raw::Tensor(torch::detach_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_linalg_matrix_exp_out_tensor_tensor(void* out, void* self) +void* _lantern_slice_copy_out_tensor_tensor_intt_intt_intt_intt(void* out, void* self, void* dim, void* start, void* end, void* step) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::linalg_matrix_exp_out( + return make_raw::Tensor(torch::slice_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim), from_raw::optional::int64_t(start), from_raw::optional::int64_t(end), from_raw::int64_t(step))); + LANTERN_FUNCTION_END +} + +void* _lantern_squeeze_copy_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::squeeze_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_optional_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) +void* _lantern_squeeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_optional_intlist_out( - from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); + return make_raw::Tensor(torch::squeeze_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); LANTERN_FUNCTION_END } -void* _lantern__test_optional_filled_intlist_out_tensor_tensor_intarrayref(void* out, void* values, void* addends) +void* _lantern_squeeze_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* dim) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_optional_filled_intlist_out( - from_raw::Tensor(out), from_raw::Tensor(values), from_raw::IntArrayRef(addends))); + return make_raw::Tensor(torch::squeeze_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(dim))); LANTERN_FUNCTION_END } -void* _lantern__test_optional_floatlist_out_tensor_tensor_arrayrefdouble(void* out, void* values, void* addends) +void* _lantern_t_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_optional_floatlist_out( - from_raw::Tensor(out), from_raw::Tensor(values), from_raw::optional::DoubleArrayRef(addends))); + return make_raw::Tensor(torch::t_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_warn_in_autograd_out_tensor_tensor(void* out, void* self) +void* _lantern_transpose_copy_out_tensor_tensor_intt_intt(void* out, void* self, void* dim0, void* dim1) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_warn_in_autograd_out( + return make_raw::Tensor(torch::transpose_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim0), from_raw::int64_t(dim1))); + LANTERN_FUNCTION_END +} + +void* _lantern_unsqueeze_copy_out_tensor_tensor_intt(void* out, void* self, void* dim) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::unsqueeze_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dim))); + LANTERN_FUNCTION_END +} + +void* _lantern__indices_copy_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::_indices_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_autograd_multiple_dispatch_out_tensor_tensor(void* out, void* self) +void* _lantern__values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_out( + return make_raw::Tensor(torch::_values_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__test_autograd_multiple_dispatch_view_copy_out_tensor_tensor(void* out, void* self) +void* _lantern_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_test_autograd_multiple_dispatch_view_copy_out( + return make_raw::Tensor(torch::indices_copy_out( from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern_segment_reduce_out_tensor_tensor_cstringview_tensor_tensor_tensor_intt_bool_scalar(void* out, void* data, void* reduce, void* lengths, void* indices, void* offsets, void* axis, void* unsafe, void* initial) +void* _lantern_values_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::segment_reduce_out( - from_raw::Tensor(out), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(indices), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::bool_t(unsafe), from_raw::optional::Scalar(initial))); + return make_raw::Tensor(torch::values_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__segment_reduce_backward_out_tensor_tensor_tensor_tensor_cstringview_tensor_tensor_intt_scalar(void* out, void* grad, void* output, void* data, void* reduce, void* lengths, void* offsets, void* axis, void* initial) +void* _lantern_crow_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_segment_reduce_backward_out( - from_raw::Tensor(out), from_raw::Tensor(grad), from_raw::Tensor(output), from_raw::Tensor(data), from_raw::string_view(reduce), from_raw::optional::Tensor(lengths), from_raw::optional::Tensor(offsets), from_raw::int64_t(axis), from_raw::optional::Scalar(initial))); + return make_raw::Tensor(torch::crow_indices_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } -void* _lantern__nested_tensor_from_tensor_list_out_tensor_tensorlist_scalartype_layout_device_bool(void* out, void* list, void* dtype, void* layout, void* device, void* pin_memory) +void* _lantern_col_indices_copy_out_tensor_tensor(void* out, void* self) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_nested_tensor_from_tensor_list_out( - from_raw::Tensor(out), from_raw::TensorList(list), from_raw::optional::ScalarType(dtype), from_raw::optional::Layout(layout), from_raw::optional::Device(device), from_raw::optional::bool_t(pin_memory))); + return make_raw::Tensor(torch::col_indices_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); LANTERN_FUNCTION_END } @@ -27775,19 +27951,43 @@ void* _lantern_row_indices_copy_out_tensor_tensor(void* out, void* self) LANTERN_FUNCTION_END } -void* _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) +void* _lantern_view_copy_out_tensor_tensor_intarrayref(void* out, void* self, void* size) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::to_padded_tensor_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); + return make_raw::Tensor(torch::view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::IntArrayRef(size))); + LANTERN_FUNCTION_END +} + +void* _lantern_view_copy_out_tensor_tensor_scalartype(void* out, void* self, void* dtype) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::view_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::ScalarType(dtype))); LANTERN_FUNCTION_END } -void* _lantern__nested_tensor_layer_norm_out_tensor_tensor_tensor_tensor_double(void* out, void* self, void* weight, void* bias, void* eps) +void* _lantern_unfold_copy_out_tensor_tensor_intt_intt_intt(void* out, void* self, void* dimension, void* size, void* step) { LANTERN_FUNCTION_START - return make_raw::Tensor(torch::_nested_tensor_layer_norm_out( - from_raw::Tensor(out), from_raw::Tensor(self), from_raw::optional::Tensor(weight), from_raw::optional::Tensor(bias), from_raw::double_t(eps))); + return make_raw::Tensor(torch::unfold_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::int64_t(dimension), from_raw::int64_t(size), from_raw::int64_t(step))); + LANTERN_FUNCTION_END +} + +void* _lantern_alias_copy_out_tensor_tensor(void* out, void* self) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::alias_copy_out( + from_raw::Tensor(out), from_raw::Tensor(self))); + LANTERN_FUNCTION_END +} + +void* _lantern_to_padded_tensor_out_tensor_tensor_double_intarrayref(void* out, void* self, void* padding, void* output_size) +{ + LANTERN_FUNCTION_START + return make_raw::Tensor(torch::to_padded_tensor_out( + from_raw::Tensor(out), from_raw::Tensor(self), from_raw::double_t(padding), from_raw::IntArrayRef(output_size))); LANTERN_FUNCTION_END } @@ -27863,4 +28063,20 @@ void* _lantern__fused_adam_tensorlist_tensorlist_tensorlist_tensorlist_tensorlis LANTERN_FUNCTION_END } +void* _lantern__fused_adamw_out_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* out, void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) +{ + LANTERN_FUNCTION_START + torch::_fused_adamw_out(from_raw::TensorList(out), from_raw::TensorList(self), from_raw::TensorList(grads), from_raw::TensorList(exp_avgs), from_raw::TensorList(exp_avg_sqs), from_raw::TensorList(max_exp_avg_sqs), from_raw::TensorList(state_steps), from_raw::double_t(lr), from_raw::double_t(beta1), from_raw::double_t(beta2), from_raw::double_t(weight_decay), from_raw::double_t(eps), from_raw::bool_t(amsgrad), from_raw::bool_t(maximize), from_raw::optional::Tensor(grad_scale), from_raw::optional::Tensor(found_inf)); + return NULL; + LANTERN_FUNCTION_END +} + +void* _lantern__fused_adamw_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_tensorlist_double_double_double_double_double_bool_bool_tensor_tensor(void* self, void* grads, void* exp_avgs, void* exp_avg_sqs, void* max_exp_avg_sqs, void* state_steps, void* lr, void* beta1, void* beta2, void* weight_decay, void* eps, void* amsgrad, void* maximize, void* grad_scale, void* found_inf) +{ + LANTERN_FUNCTION_START + return make_raw::tuple(torch::_fused_adamw( + from_raw::TensorList(self), from_raw::TensorList(grads), from_raw::TensorList(exp_avgs), from_raw::TensorList(exp_avg_sqs), from_raw::TensorList(max_exp_avg_sqs), from_raw::TensorList(state_steps), from_raw::double_t(lr), from_raw::double_t(beta1), from_raw::double_t(beta2), from_raw::double_t(weight_decay), from_raw::double_t(eps), from_raw::bool_t(amsgrad), from_raw::bool_t(maximize), from_raw::optional::Tensor(grad_scale), from_raw::optional::Tensor(found_inf))); + LANTERN_FUNCTION_END +} + /* Autogen Body -- End */ diff --git a/tests/testthat/_snaps/device.md b/tests/testthat/_snaps/device.md new file mode 100644 index 0000000000..4fb4a3b6c1 --- /dev/null +++ b/tests/testthat/_snaps/device.md @@ -0,0 +1,4 @@ +# printer works + + torch_device(type='cpu') + diff --git a/tests/testthat/test-autocast.R b/tests/testthat/test-autocast.R index fcd31baa68..05b8097e5b 100644 --- a/tests/testthat/test-autocast.R +++ b/tests/testthat/test-autocast.R @@ -4,7 +4,7 @@ test_that("local_autocast works", { y <- torch_randn(5, 5, dtype = torch_float32()) foo <- function(x, y) { - local_autocast(device = "cpu") + local_autocast(device_type = "cpu") z <- torch_mm(x, y) w <- torch_mm(z, x) w @@ -132,7 +132,11 @@ test_that("scaling the loss works", { loss$backward() # gradients are so small that they become 0 - expect_true(all(as.matrix(model$weight$grad$cpu()) == 0)) + expect_equal( + as.matrix(model$weight$grad$cpu()), + array(rep(0, 4), dim = c(2,2)), + tolerance = 1e-6 + ) # now we scale the loss and gradients scaler <- cuda_amp_grad_scaler() @@ -231,6 +235,6 @@ test_that("grad scalers work correctly", { # got the same value as obtained from pytorch expect_equal( sprintf("%1.6f", loss$item()), - sprintf("%1.6f", 1.00434148311615) + sprintf("%1.6f", 1.003786) ) }) diff --git a/tests/testthat/test-autograd.R b/tests/testthat/test-autograd.R index 275271aa23..2ff0ec74cd 100644 --- a/tests/testthat/test-autograd.R +++ b/tests/testthat/test-autograd.R @@ -637,7 +637,7 @@ test_that("autograd_grad with non-leafs", { o <- autograd_grad( fn(x), x, - grad_output = grad_output, + grad_outputs = grad_output, create_graph = TRUE ) } @@ -872,13 +872,13 @@ test_that("local grad functions", { } with_no_grad({ - expect_error(fun(f, TRUE), regex = NA) + expect_error(fun(f, TRUE), regexp = NA) }) - expect_error(f(), regex = NA) + expect_error(f(), regexp = NA) with_enable_grad({ expect_error(fun(f, FALSE)) - expect_error(f(), regex = NA) + expect_error(f(), regexp = NA) }) }) diff --git a/tests/testthat/test-device.R b/tests/testthat/test-device.R index 087f2ff7b9..c523af7e5c 100644 --- a/tests/testthat/test-device.R +++ b/tests/testthat/test-device.R @@ -78,5 +78,8 @@ test_that("can modify the device temporarily", { }) test_that("printer works", { - expect_equal(capture.output(torch_device("cpu")), "torch_device(type='cpu')>\n") + local_edition(3) + expect_snapshot_output({ + print(torch_device("cpu")) + }) }) diff --git a/tests/testthat/test-distributions-bernoulli.R b/tests/testthat/test-distributions-bernoulli.R index 161b0dcdad..432ff0995b 100644 --- a/tests/testthat/test-distributions-bernoulli.R +++ b/tests/testthat/test-distributions-bernoulli.R @@ -99,7 +99,7 @@ test_that("log prob is correct", { result <- d$log_prob(x) expected <- dbinom(as.numeric(x), 1, prob = as.numeric(probs), log = TRUE) - expect_equal_to_r(result, expected, tol = 1e-6) + expect_equal_to_r(result, expected, tolerance = 1e-6) }) test_that("gradients are correct", { diff --git a/tests/testthat/test-distributions-mixture_same_family.R b/tests/testthat/test-distributions-mixture_same_family.R index e16e12d30d..0d54c915ac 100644 --- a/tests/testthat/test-distributions-mixture_same_family.R +++ b/tests/testthat/test-distributions-mixture_same_family.R @@ -27,7 +27,7 @@ test_that("log prob and cdf are equal to reference", { c(-0.9189383984, -1.4189383984) )) - expect_equal_to_tensor(result, expected, tol = 1e-5) + expect_equal_to_tensor(result, expected, tolerance = 1e-5) result <- d$cdf(torch_tensor(rbind(c(1, 2), c(0, -1)))) expected <- torch_tensor(rbind( @@ -35,7 +35,7 @@ test_that("log prob and cdf are equal to reference", { c(0.5000000000, 0.1586552560) )) - expect_equal_to_tensor(result, expected, tol = 1e-5) + expect_equal_to_tensor(result, expected, tolerance = 1e-5) }) test_that("gradients are similar to python", { @@ -51,7 +51,7 @@ test_that("gradients are similar to python", { loss <- d$log_prob(torch_tensor(rbind(c(1, 2), c(0, -1))))$mean() loss$backward() - expect_equal_to_r(probs$grad, c(-9.9341050941e-09, 1.4901161194e-08), tol = 1e-6) - expect_equal_to_r(loc$grad, c(0.3000000119, 0.1999999881), tol = 1e-6) - expect_equal_to_r(scale$grad, c(0.2999999523, 0.1999999881), tol = 1e-6) + expect_equal_to_r(probs$grad, c(-9.9341050941e-09, 1.4901161194e-08), tolerance = 1e-6) + expect_equal_to_r(loc$grad, c(0.3000000119, 0.1999999881), tolerance = 1e-6) + expect_equal_to_r(scale$grad, c(0.2999999523, 0.1999999881), tolerance = 1e-6) }) diff --git a/tests/testthat/test-fork.R b/tests/testthat/test-fork.R index 56cacb338a..362e884c24 100644 --- a/tests/testthat/test-fork.R +++ b/tests/testthat/test-fork.R @@ -5,8 +5,8 @@ test_that("Forking doesn't deadlock", { library(torch) testfun <- function (x) { lstm <- nn_lstm(50, 50) - in_data <- torch_tensor(matrix(rnorm(50),1), torch_float()) - out_data <- torch_tensor(array(rnorm(2500), c(1,50,50)), torch_float()) + in_data <- torch_randn(1,50,50) + out_data <- torch_randn(1,50,50) out_pred <- lstm(in_data)[[1]] loss <- nnf_mse_loss(out_pred, out_data) loss$backward() diff --git a/tests/testthat/test-gen-method.R b/tests/testthat/test-gen-method.R index c89a9fab01..ac1984c3f4 100644 --- a/tests/testthat/test-gen-method.R +++ b/tests/testthat/test-gen-method.R @@ -70,7 +70,21 @@ test_that("permute", { expect_error( x$permute(c(2, 1, 0)), - regex = "Indexing starts at 1 but found a 0.", + regexp = "Indexing starts at 1 but found a 0.", fixed = TRUE ) }) + +test_that("std works", { + x <- torch_randn(10) + s <- x$std() + r <- sd(as.numeric(x)) + expect_equal_to_r(s, r, tolerance = 1e-6) +}) + +test_that("var works", { + x <- torch_randn(10) + s <- x$var() + r <- var(as.numeric(x)) + expect_equal_to_r(s, r, tolerance = 1e-6) +}) diff --git a/tests/testthat/test-gen-namespace.R b/tests/testthat/test-gen-namespace.R index 1c44bb8ed4..58cb2831a2 100644 --- a/tests/testthat/test-gen-namespace.R +++ b/tests/testthat/test-gen-namespace.R @@ -211,10 +211,19 @@ test_that("logit works", { expect_equal_to_tensor( exp(torch_logit(x)) / (1 + exp(torch_logit(x))), x, - tol = 1e-6 + tolerance = 1e-6 ) }) +test_that("std works", { + x <- torch_randn(10) + + s <- torch_std(x) + r <- sd(as.numeric(x)) + + expect_equal_to_r(s, r, tolerance = 1e-6) +}) + test_that("tensordot", { a <- torch_arange(start = 1, end = 60)$reshape(c(3, 4, 5)) b <- torch_arange(start = 1, end = 24)$reshape(c(4, 3, 2)) diff --git a/tests/testthat/test-nn-activation.R b/tests/testthat/test-nn-activation.R index fafa2049f7..2cd8125562 100644 --- a/tests/testthat/test-nn-activation.R +++ b/tests/testthat/test-nn-activation.R @@ -63,10 +63,10 @@ test_that("Multihead attention works", { x <- torch_randn(1,1,2) out <- attn1(x, x, x) - expect_equal_to_r(out[[1]][1,1,], c(0.0736, -0.0599), tol = 1e-4) - expect_equal_to_r(out[[2]][1,1,], c(1), tol = 1e-4) - expect_equal_to_r(attn1$in_proj_weight[1,], c(-0.1782, 0.4406), tol = 1e-4) - expect_equal_to_r(attn1$out_proj$weight[1,], c(0.3643, -0.3121), tol = 1e-4) + expect_equal_to_r(out[[1]][1,1,], c(0.0736, -0.0599), tolerance = 1e-4) + expect_equal_to_r(out[[2]][1,1,], c(1), tolerance = 1e-4) + expect_equal_to_r(attn1$in_proj_weight[1,], c(-0.1782, 0.4406), tolerance = 1e-4) + expect_equal_to_r(attn1$out_proj$weight[1,], c(0.3643, -0.3121), tolerance = 1e-4) # raise error when embed_dim is not divisible by num_heads. expect_error(nn_multihead_attention(embed_dim = 512, num_heads = 10), regexp="divisible") diff --git a/tests/testthat/test-nn-loss.R b/tests/testthat/test-nn-loss.R index 8e2d6e7c66..d250bcfba9 100644 --- a/tests/testthat/test-nn-loss.R +++ b/tests/testthat/test-nn-loss.R @@ -55,7 +55,7 @@ test_that("multilabel margin loss", { # for target y, only consider labels 4 and 1, not after label -1 y <- torch_tensor(c(4, 1, -1, 2), dtype = torch_long())$view(c(1, 4)) o <- loss(x, y) - expect_equal(as.numeric(o), 0.85, tol = 1e-5) + expect_equal(as.numeric(o), 0.85, tolerance = 1e-5) expect_length(o$shape, 0) y <- torch_tensor(c(4, 0, -1, 2), dtype = torch_long())$view(c(1, 4)) diff --git a/tests/testthat/test-nn.R b/tests/testthat/test-nn.R index a152e3fb2c..1e3a6837e7 100644 --- a/tests/testthat/test-nn.R +++ b/tests/testthat/test-nn.R @@ -773,7 +773,7 @@ test_that("non persistent buffers work correctly", { initialize = function() { self$x <- nn_parameter(torch_tensor(1)) self$y <- nn_buffer(torch_tensor(2)) - self$z <- nn_buffer(torch_tensor(3), persist = FALSE) + self$z <- nn_buffer(torch_tensor(3), persistent = FALSE) }, forward = function() { self$x + self$y + self$z diff --git a/tests/testthat/test-optim-lr_scheduler.R b/tests/testthat/test-optim-lr_scheduler.R index bda3b48f13..c75e58b30a 100644 --- a/tests/testthat/test-optim-lr_scheduler.R +++ b/tests/testthat/test-optim-lr_scheduler.R @@ -42,7 +42,7 @@ test_that("lr_one_cycle", { } }) - expect_equal(o$param_groups[[1]]$lr, 0.1335607, tol = 1e-6) + expect_equal(o$param_groups[[1]]$lr, 0.1335607, tolerance = 1e-6) expect_error(scheduler$step()) }) diff --git a/tests/testthat/test-save.R b/tests/testthat/test-save.R index 4ab20b6a03..a1557b6303 100644 --- a/tests/testthat/test-save.R +++ b/tests/testthat/test-save.R @@ -37,8 +37,8 @@ test_that("save more complicated module", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -186,7 +186,9 @@ test_that("Can load a torch v0.2.1 model", { model <- torch_load(dest) x <- torch_randn(32, 1, 28, 28) - expect_error(o <- model(x), regexp = NA) + suppressWarnings({ + expect_error(o <- model(x), regexp = NA) + }) expect_tensor_shape(o, c(32, 10)) }) @@ -204,7 +206,9 @@ test_that("Can load a v0.10.0 model", { model <- torch_load(dest) x <- torch_randn(32, 1, 28, 28) - expect_error(o <- model(x), regexp = NA) + suppressWarnings({ + expect_error(o <- model(x), regexp = NA) + }) expect_tensor_shape(o, c(32, 10)) }) @@ -246,8 +250,10 @@ test_that("can save with a NULL device", { model <- nn_linear(10, 10)$cuda() tmp <- tempfile("model", fileext = "pt") torch_save(model, tmp) - model <- torch_load(tmp, device = NULL) - expect_equal(model$weight$device$type, "cuda") + + expect_error({ + model <- torch_load(tmp, device = NULL) + }, "Unexpected device") }) test_that("save on cuda and load on cpu", { diff --git a/tests/testthat/test-tensor.R b/tests/testthat/test-tensor.R index 12e1acaf98..bcced81cbd 100644 --- a/tests/testthat/test-tensor.R +++ b/tests/testthat/test-tensor.R @@ -62,7 +62,7 @@ test_that("Integer tensors", { expect_s3_class(o, "array") expect_equal(dim(o), dim(x)) - x <- as.integer64(.Machine$integer) * 2 + x <- as.integer64(.Machine$integer.max) * 2 y <- torch_tensor(x) z <- as.integer64(y) @@ -361,7 +361,7 @@ test_that("tensor identity works as expected", { gc() class(y) <- class(torch_tensor(1)) - expect_equal_to_r(y, v, tol = 1e-7) + expect_equal_to_r(y, v, tolerance = 1e-7) x <- y$abs_() @@ -467,7 +467,7 @@ test_that("create complex from and to R", { y <- as.array(x) z <- torch_tensor(y) expect_true(torch_allclose(x, z)) - expect_equal(as.complex(x), complex(real = 1,imag = 1)) + expect_equal(as.complex(x), complex(real = 1,imaginary = 1)) }) diff --git a/tests/testthat/test-trace.R b/tests/testthat/test-trace.R index 9755c1f85d..7e53314d59 100644 --- a/tests/testthat/test-trace.R +++ b/tests/testthat/test-trace.R @@ -26,8 +26,8 @@ test_that("modules are equivalent", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -313,8 +313,8 @@ test_that("trace a module", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -428,8 +428,8 @@ test_that("can save module for mobile", { initialize = function() { self$conv1 <- nn_conv2d(1, 32, 3, 1) self$conv2 <- nn_conv2d(32, 64, 3, 1) - self$dropout1 <- nn_dropout2d(0.25) - self$dropout2 <- nn_dropout2d(0.5) + self$dropout1 <- nn_dropout(0.25) + self$dropout2 <- nn_dropout(0.5) self$fc1 <- nn_linear(9216, 128) self$fc2 <- nn_linear(128, 10) }, @@ -462,7 +462,7 @@ test_that("can save module for mobile", { jit_save_for_mobile(tr_fn, tmp) f <- jit_load(tmp) - expect_equal_to_tensor(net(input), f(input), tol = 1e-6) + expect_equal_to_tensor(net(input), f(input), tolerance = 1e-6) }) test_that("can save function for mobile", { diff --git a/tests/testthat/test-translate.R b/tests/testthat/test-translate.R index 9f621058af..4bfbd670a2 100644 --- a/tests/testthat/test-translate.R +++ b/tests/testthat/test-translate.R @@ -20,7 +20,7 @@ test_that("out of bound error message", { for (f in funs) { expect_error( f(x, dim = 2), - regex = "Dimension out of range (expected to be in range of [-1, 1], but got 2)", + regexp = "Dimension out of range (expected to be in range of [-1, 1], but got 2)", fixed = TRUE ) } @@ -28,7 +28,7 @@ test_that("out of bound error message", { for (f in funs) { expect_error( f(x, dim = -2), - regex = "Dimension out of range (expected to be in range of [-1, 1], but got -2)", + regexp = "Dimension out of range (expected to be in range of [-1, 1], but got -2)", fixed = TRUE ) } @@ -38,7 +38,7 @@ test_that("out of bound error message", { for (f in funs) { expect_error( f(x, dim = 11), - regex = "Dimension out of range (expected to be in range of [-10, 10], but got 11)", + regexp = "Dimension out of range (expected to be in range of [-10, 10], but got 11)", fixed = TRUE ) } @@ -49,7 +49,7 @@ test_that("more than 1 dim", { expect_error( torch_sum(x, dim = c(1, 4)), - regex = "Dimension out of range (expected to be in range of [-3, 3], but got 4)", + regexp = "Dimension out of range (expected to be in range of [-3, 3], but got 4)", fixed = TRUE ) }) @@ -59,13 +59,13 @@ test_that("dim1 & dim2", { expect_error( torch_transpose(x, 3, 1), - regex = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", + regexp = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", fixed = TRUE ) expect_error( torch_transpose(x, 2, 3), - regex = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", + regexp = "Dimension out of range (expected to be in range of [-2, 2], but got 3)", fixed = TRUE ) @@ -88,7 +88,7 @@ test_that("dimension x does not have size y", { expect_error( torch_cross(a, b, dim = 1), - regex = "inputs dimension 1 must have length 3", + regexp = "inputs dimension 1 must have length 3", fixed = TRUE ) }) @@ -123,7 +123,7 @@ test_that("index argument", { expect_error( torch_select(x, 1, 4), - regex = "index 4 out of range for tensor of size [3] at dimension 1", + regexp = "index 4 out of range for tensor of size [3] at dimension 1", fixed = TRUE ) }) @@ -133,13 +133,13 @@ test_that("torch_nll_loss out of bound", { expect_error( torch_nll_loss(x, torch_tensor(0, dtype = torch_long())), - regex = "Indexing starts at 1 but found a 0.", + regexp = "Indexing starts at 1 but found a 0.", fixed = TRUE ) expect_error( torch_nll_loss(x, torch_tensor(6, dtype = torch_long())), - regex = "Target 6 is out of bounds.", + regexp = "Target 6 is out of bounds.", fixed = TRUE ) }) @@ -150,7 +150,7 @@ test_that("tensordot error message", { expect_error( torch_tensordot(a, b, list(c(2, 1), c(1, 3))), - regex = "contracted dimensions need to match, but first has size 3 in dim 1 and second has size 2 in dim 3", + regexp = "contracted dimensions need to match, but first has size 3 in dim 1 and second has size 2 in dim 3", fixed = TRUE ) }) @@ -161,7 +161,7 @@ test_that("embedding returns a better error message", { expect_error( e(x), - regex = "Indexing starts at 1 but found a 0." + regexp = "Indexing starts at 1 but found a 0." ) }) @@ -170,7 +170,7 @@ test_that("movedim", { expect_error( torch_movedim(x, 0, 1), - regex = "Dimension is 1-based, but found 0.", + regexp = "Dimension is 1-based, but found 0.", class = "value_error" ) @@ -217,7 +217,7 @@ test_that("cat", { expect_error( torch_cat(list(torch_randn(8, 2, 7), torch_randn(8, 3, 7)), dim = 1), - regex = "Sizes of tensors must match except in dimension 1. Expected size 2 but got size 3 for tensor number 2 in the list.", + regexp = "Sizes of tensors must match except in dimension 1. Expected size 2 but got size 3 for tensor number 2 in the list.", fixed = TRUE ) diff --git a/tests/testthat/test-utils-data.R b/tests/testthat/test-utils-data.R index d2ca53ca8d..301b07ef2a 100644 --- a/tests/testthat/test-utils-data.R +++ b/tests/testthat/test-utils-data.R @@ -131,7 +131,7 @@ test_that("datasets have a custom print method", { parent_env = .GlobalEnv ) - expect_output(print(data), regex = "dataset_generator") + expect_output(print(data), regexp = "dataset_generator") }) test_that("dataset subset adds more classes", { diff --git a/tests/testthat/test-wrapers.R b/tests/testthat/test-wrapers.R index 09771d8746..27b446fc5a 100644 --- a/tests/testthat/test-wrapers.R +++ b/tests/testthat/test-wrapers.R @@ -179,7 +179,8 @@ test_that("stft", { input = torch::torch_ones(3000), n_fft = 400, center = FALSE, - onesided = TRUE + onesided = TRUE, + return_complex = FALSE ) expect_tensor_shape(x, c(201, 27, 2)) @@ -189,7 +190,8 @@ test_that("stft", { x <- torch::torch_stft( input = torch::torch_ones(3000), n_fft = 400, - center = TRUE + center = TRUE, + return_complex = FALSE ) expect_tensor_shape(x, c(201, 31, 2)) @@ -209,7 +211,8 @@ test_that("stft", { input = torch::torch_ones(3000), n_fft = 400, window = torch_ones(400), - center = FALSE + center = FALSE, + return_complex = FALSE ) expect_tensor_shape(x, c(201, 27, 2)) diff --git a/tools/torchgen/R/utils.R b/tools/torchgen/R/utils.R index fa01dabb47..1030fd3e8d 100644 --- a/tools/torchgen/R/utils.R +++ b/tools/torchgen/R/utils.R @@ -7,7 +7,7 @@ #' @export declarations <- function() { - version <- getOption("torchgen.version", default = "1.13.1") + version <- getOption("torchgen.version", default = "2.0.1") path <- getOption("torchgen.path") if (is.null(path)) { @@ -42,7 +42,10 @@ declarations <- function() { s$method_of <- c(s$method_of, "Tensor") decls[[index]] <- s - decls + # remove argument from var + decls %>% + purrr::discard(~str_detect(.x$name, "var") && "correction" %in% map_chr(.x$arguments, ~.x$name)) %>% + purrr::discard(~str_detect(.x$name, "std") && "correction" %in% map_chr(.x$arguments, ~.x$name)) } memoised_declarations <- memoise::memoise(declarations) diff --git a/tools/torchgen/inst/declaration/Declarations-1.13.1.yaml b/tools/torchgen/inst/declaration/Declarations-2.0.1.yaml similarity index 97% rename from tools/torchgen/inst/declaration/Declarations-1.13.1.yaml rename to tools/torchgen/inst/declaration/Declarations-2.0.1.yaml index 30d70db719..88688e1499 100644 --- a/tools/torchgen/inst/declaration/Declarations-1.13.1.yaml +++ b/tools/torchgen/inst/declaration/Declarations-2.0.1.yaml @@ -6150,6 +6150,113 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _is_all_true + operator_name: _is_all_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_all_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _is_any_true + operator_name: _is_any_true + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_is_any_true(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_check_tensor + operator_name: _test_check_tensor + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_check_tensor(Tensor self) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: all operator_name: all overload_name: dim @@ -10177,11 +10284,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: bilinear operator_name: bilinear overload_name: '' @@ -11999,7 +12106,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::broadcast_to(Tensor(a) self, int[] size) -> Tensor(a) + schema_string: aten::broadcast_to(Tensor(a) self, SymInt[] size) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -13072,7 +13179,7 @@ type: ::std::vector inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: false with_gil: false deprecated: false @@ -13082,7 +13189,7 @@ overload_name: sections manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.sections(Tensor(a -> *) self, int sections, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.sections(Tensor(a -> *) self, SymInt sections, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -13140,7 +13247,7 @@ overload_name: indices manual_kernel_registration: false category_override: '' - schema_string: aten::tensor_split.indices(Tensor(a -> *) self, int[] indices, int dim=0) -> Tensor(a)[] + schema_string: aten::tensor_split.indices(Tensor(a -> *) self, SymInt[] indices, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -14875,7 +14982,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd(Tensor self, int[] pad, Scalar value=0) -> Tensor + schema_string: aten::constant_pad_nd(Tensor self, SymInt[] pad, Scalar value=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -14981,7 +15088,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups) -> Tensor + schema_string: aten::convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15096,7 +15203,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::convolution_backward(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -15486,7 +15593,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor + schema_string: aten::_convolution(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -15881,7 +15988,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) + schema_string: aten::_convolution_double_backward(Tensor? ggI, Tensor? ggW, Tensor? ggb, Tensor gO, Tensor weight, Tensor self, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask) -> (Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -17272,11 +17379,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: copy_ operator_name: copy_ overload_name: '' @@ -24191,7 +24298,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor + schema_string: aten::embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24272,7 +24379,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor + schema_string: aten::embedding_backward(Tensor grad, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, bool sparse) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -24357,7 +24464,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq) -> Tensor + schema_string: aten::embedding_dense_backward(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25234,7 +25341,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, bool sparse, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25381,7 +25488,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_sparse_backward(Tensor grad, Tensor indices, Tensor offsets, Tensor offset2bag, Tensor bag_size, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -25508,7 +25615,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor + schema_string: aten::_embedding_bag_dense_backward(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31728,7 +31835,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c(Tensor self, int[] dim, int normalization, bool forward) -> Tensor + schema_string: aten::_fft_c2c(Tensor self, SymInt[] dim, int normalization, bool forward) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -31793,7 +31900,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_fft_c2c.out(Tensor self, int[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fft_c2c.out(Tensor self, SymInt[] dim, int normalization, bool forward, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -34412,7 +34519,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::layer_norm(Tensor input, int[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor + schema_string: aten::layer_norm(Tensor input, SymInt[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -39598,7 +39705,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, int[] sizes, bool keepdim) -> Tensor + schema_string: aten::value_selecting_reduction_backward(Tensor grad, int dim, Tensor indices, SymInt[] sizes, bool keepdim) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40106,17 +40213,128 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: true -- name: _mps_max_pool2d - operator_name: _mps_max_pool2d +- name: max_pool2d_backward + operator_name: max_pool2d_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: ceil_mode + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_max_pool2d + operator_name: mkldnn_max_pool2d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40212,12 +40430,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mps_max_pool2d_backward - operator_name: mps_max_pool2d_backward +- name: mkldnn_max_pool2d_backward + operator_name: mkldnn_max_pool2d_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mps_max_pool2d_backward(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40227,7 +40445,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40262,7 +40485,7 @@ is_nullable: false name: ceil_mode type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -40272,7 +40495,12 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef @@ -40323,12 +40551,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mkldnn_max_pool2d - operator_name: mkldnn_max_pool2d +- name: mkldnn_max_pool3d + operator_name: mkldnn_max_pool3d overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_max_pool2d(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor + schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -40339,28 +40567,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -40379,250 +40607,28 @@ dynamic_type: at::IntArrayRef is_nullable: false name: kernel_size - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: '{}' dynamic_type: at::IntArrayRef is_nullable: false name: stride - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 0 dynamic_type: at::IntArrayRef is_nullable: false name: padding - size: 2 + size: 3 type: at::IntArrayRef - annotation: null default: 1 dynamic_type: at::IntArrayRef is_nullable: false name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool2d_backward - operator_name: mkldnn_max_pool2d_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool2d_backward(Tensor grad_output, Tensor output, Tensor input, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_max_pool3d - operator_name: mkldnn_max_pool3d - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_max_pool3d(Tensor self, int[3] kernel_size, int[3] stride=[], int[3] padding=0, int[3] dilation=1, bool ceil_mode=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + size: 3 type: at::IntArrayRef - annotation: null default: false @@ -42969,7 +42975,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups) -> Tensor + schema_string: aten::mkldnn_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43059,12 +43065,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: miopen_batch_norm - operator_name: miopen_batch_norm +- name: mkldnn_rnn_layer + operator_name: mkldnn_rnn_layer overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + schema_string: aten::mkldnn_rnn_layer(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train) -> (Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -43074,39 +43080,506 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: weight + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward + operator_name: mkldnn_rnn_layer_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: bias + name: grad_output type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_mean + name: grad_hy type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: true - name: running_var + name: grad_cy type: const c10::optional & - annotation: null dynamic_type: bool is_nullable: false - name: training + name: reverse type: bool - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: exponential_average_factor - type: double + name: mode + type: int64_t - annotation: null - dynamic_type: double + dynamic_type: int64_t is_nullable: false - name: epsilon - type: double - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + name: result3 + type: at::Tensor + - dynamic_type: at::Tensor + name: result4 + type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor + - dynamic_type: at::Tensor + name: result6 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: miopen_batch_norm + operator_name: miopen_batch_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::miopen_batch_norm(Tensor input, Tensor weight, Tensor? bias, Tensor? running_mean, Tensor? running_var, bool training, float exponential_average_factor, float epsilon) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_mean + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: running_var + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: exponential_average_factor + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: epsilon + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -43286,7 +43759,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43401,7 +43874,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_convolution_transpose(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -43526,7 +43999,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor + schema_string: aten::miopen_depthwise_convolution(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -44417,312 +44890,53 @@ with_gil: false deprecated: false has_math_kernel: true -- name: _sparse_sparse_matmul - operator_name: _sparse_sparse_matmul - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _sparse_mask_helper - operator_name: _sparse_mask_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_sparse_mask_helper(Tensor t, Tensor mask_indices) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: t - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: mask_indices - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: '' +- name: _sparse_mm + operator_name: _sparse_mm + overload_name: reduce manual_kernel_registration: false category_override: '' - schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + schema_string: aten::_sparse_mm.reduce(Tensor sparse, Tensor dense, str reduce) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode_out - operator_name: mode - overload_name: values - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + name: reduce + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: -1 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: mode - operator_name: mode - overload_name: dimname - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self + name: sparse type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: dense type: const at::Tensor & - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool + dynamic_type: c10::string_view is_nullable: false - name: keepdim - type: bool + name: reduce + type: c10::string_view method_of: - Type - - Tensor - namespace mode: native - python_module: '' + python_module: sparse returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: result type: at::Tensor inplace: false is_factory_method: false @@ -44731,106 +44945,375 @@ with_gil: false deprecated: false has_math_kernel: true -- name: mode_out - operator_name: mode - overload_name: dimname_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Dimname - is_nullable: false - name: dim - type: at::Dimname - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values - is_nullable: false - name: values - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: indices - is_nullable: false - name: indices - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: mul - operator_name: mul - overload_name: Tensor +- name: _sparse_sparse_matmul + operator_name: _sparse_sparse_matmul + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor + schema_string: aten::_sparse_sparse_matmul(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode(Tensor self, int dim=-1, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode_out + operator_name: mode + overload_name: values + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: mode + operator_name: mode + overload_name: dimname + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mode_out + operator_name: mode + overload_name: dimname_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::Dimname, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Dimname + is_nullable: false + name: dim + type: at::Dimname + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: mul + operator_name: mul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::mul.Tensor(Tensor self, Tensor other) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -45712,7 +46195,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::narrow(Tensor(a) self, int dim, int start, int length) -> Tensor(a) + schema_string: aten::narrow(Tensor(a) self, int dim, SymInt start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -45778,7 +46261,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, int length) -> Tensor(a) + schema_string: aten::narrow.Tensor(Tensor(a) self, int dim, Tensor start, SymInt length) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -46103,6 +46586,494 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.out(Tensor input, Tensor? weight, Tensor? bias, Tensor(a!) running_mean, Tensor(b!) running_var, bool training, float momentum, float eps, *, Tensor(d!) out, Tensor(e!) save_mean, Tensor(f!) save_invstd) -> (Tensor(d!), Tensor(e!), Tensor(f!)) + arguments: + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, at::Tensor &, at::Tensor &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: running_mean + type: at::Tensor & + - annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: running_var + type: at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit + operator_name: _native_batch_norm_legit + overload_name: no_stats + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _native_batch_norm_legit_out + operator_name: _native_batch_norm_legit + overload_name: no_stats_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_native_batch_norm_legit.no_stats_out(Tensor input, Tensor? weight, Tensor? bias, bool training, float momentum, float eps, *, Tensor(a!) out, Tensor(b!) save_mean, Tensor(c!) save_invstd) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, bool, double, double, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: save_mean + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: save_invstd + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_mean + type: at::Tensor & + - dynamic_type: at::Tensor + name: save_invstd + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: batch_norm_stats operator_name: batch_norm_stats overload_name: '' @@ -47024,7 +47995,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1) -> Tensor + schema_string: aten::_nnpack_spatial_convolution(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -49165,7 +50136,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49247,7 +50218,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49341,7 +50312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::rand(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49411,7 +50382,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::rand.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -49493,7 +50464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49542,7 +50513,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -49687,7 +50658,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randint(int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint(int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49767,7 +50738,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator(int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.generator(int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49859,7 +50830,7 @@ overload_name: low manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low(int low, int high, int[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low(int low, int high, SymInt[] size, *, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -49949,7 +50920,7 @@ overload_name: low_generator manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator(int low, int high, int[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randint.low_generator(int low, int high, SymInt[] size, *, Generator? generator, ScalarType? dtype=long, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -50051,7 +51022,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.out(int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.out(int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50110,7 +51081,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.generator_out(int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.generator_out(int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50181,7 +51152,7 @@ overload_name: low_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_out(int low, int high, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_out(int low, int high, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50250,7 +51221,7 @@ overload_name: low_generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randint.low_generator_out(int low, int high, int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randint.low_generator_out(int low, int high, SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50529,7 +51500,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::randn(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn(SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50599,7 +51570,7 @@ overload_name: generator manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator(int[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator(SymInt[] size, *, Generator? generator, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50681,7 +51652,7 @@ overload_name: names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names(int[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.names(SymInt[] size, *, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50763,7 +51734,7 @@ overload_name: generator_with_names manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names(int[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::randn.generator_with_names(SymInt[] size, *, Generator? generator, Dimname[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::IntArrayRef @@ -50857,7 +51828,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.out(int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.out(SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -50906,7 +51877,7 @@ overload_name: generator_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_out(int[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_out(SymInt[] size, *, Generator? generator, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -52180,7 +53151,7 @@ overload_name: self_int manual_kernel_registration: false category_override: '' - schema_string: aten::repeat_interleave.self_int(Tensor self, int repeats, int? dim=None, *, int? output_size=None) -> Tensor + schema_string: aten::repeat_interleave.self_int(Tensor self, SymInt repeats, int? dim=None, *, int? output_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -52293,6 +53264,51 @@ with_gil: false deprecated: false has_math_kernel: true +- name: _reshape_copy + operator_name: _reshape_copy + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_reshape_copy(Tensor self, SymInt[] size) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _reshape_alias operator_name: _reshape_alias overload_name: '' @@ -53066,17 +54082,62 @@ type: at::Tensor inplace: false is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: _prelu_kernel + operator_name: _prelu_kernel + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_prelu_kernel(Tensor self, Tensor weight) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: prelu_backward - operator_name: prelu_backward +- name: _prelu_kernel_backward + operator_name: _prelu_kernel_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) + schema_string: aten::_prelu_kernel_backward(Tensor grad_output, Tensor self, Tensor weight) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -53112,7 +54173,6 @@ type: const at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' @@ -53884,7 +54944,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select.int(Tensor(a) self, int dim, int index) -> Tensor(a) + schema_string: aten::select.int(Tensor(a) self, int dim, SymInt index) -> Tensor(a) arguments: - annotation: a dynamic_type: at::Tensor @@ -53940,7 +55000,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, int index) -> Tensor + schema_string: aten::select_backward(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -54005,7 +55065,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, int index) -> Tensor + schema_string: aten::_nested_select_backward(Tensor grad_output, Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -55688,7 +56748,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, int index) -> Tensor + schema_string: aten::select_scatter(Tensor self, Tensor src, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -56417,7 +57477,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56475,7 +57535,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split.Tensor(Tensor(a -> *) self, int split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.Tensor(Tensor(a -> *) self, SymInt split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56533,7 +57593,7 @@ overload_name: sizes manual_kernel_registration: false category_override: '' - schema_string: aten::split.sizes(Tensor(a -> *) self, int[] split_size, int dim=0) -> Tensor(a)[] + schema_string: aten::split.sizes(Tensor(a -> *) self, SymInt[] split_size, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -56591,7 +57651,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::unsafe_split_with_sizes(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -56649,7 +57709,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes(Tensor(a -> *) self, int[] split_sizes, int dim=0) -> Tensor(a)[] + schema_string: aten::split_with_sizes(Tensor(a -> *) self, SymInt[] split_sizes, int dim=0) -> Tensor(a)[] arguments: - annotation: a -> * dynamic_type: at::Tensor @@ -57106,6 +58166,52 @@ with_gil: false deprecated: false has_math_kernel: true +- name: squeeze + operator_name: squeeze + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze.dims(Tensor(a) self, int[] dim) -> Tensor(a) + arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: '' @@ -57186,6 +58292,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_ + operator_name: squeeze_ + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_.dims(Tensor(a!) self, int[] dim) -> Tensor(a!) + arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: self + type: at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - Tensor + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: self + type: at::Tensor & + inplace: true + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: squeeze_ operator_name: squeeze_ overload_name: dimname @@ -59391,7 +60542,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -59399,12 +60550,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59425,12 +60578,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59589,7 +60744,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59597,12 +60752,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59623,12 +60780,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59739,7 +60898,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::std_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -59753,6 +60912,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59779,6 +60939,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59900,7 +61061,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -59915,12 +61076,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -59941,12 +61104,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60144,7 +61309,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::std.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -60158,6 +61323,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60184,6 +61350,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60218,7 +61385,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::std.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -60239,6 +61406,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -60265,6 +61433,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64030,7 +65199,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64038,12 +65207,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64064,12 +65235,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64189,7 +65362,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64204,12 +65377,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64230,12 +65405,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64433,7 +65610,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> Tensor + schema_string: aten::var.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -64447,6 +65624,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64473,6 +65651,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64507,7 +65686,7 @@ overload_name: correction_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::var.correction_names_out(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -64528,6 +65707,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64554,6 +65734,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64718,7 +65899,7 @@ overload_name: correction manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64726,12 +65907,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64752,12 +65935,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64868,7 +66053,7 @@ overload_name: correction_names manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction, bool keepdim=False) -> (Tensor, Tensor) + schema_string: aten::var_mean.correction_names(Tensor self, Dimname[1] dim, *, int? correction=None, bool keepdim=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -64882,6 +66067,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -64908,6 +66094,7 @@ size: 1 type: at::DimnameList - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -65205,6 +66392,7 @@ type: const at::Scalar & method_of: - Type + - Tensor - namespace mode: native python_module: '' @@ -68219,23 +69407,47 @@ has_math_kernel: false - name: frobenius_norm operator_name: frobenius_norm - overload_name: '' + overload_name: dim manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm(Tensor self) -> Tensor + schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + size: 1 + type: at::IntArrayRef + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68252,13 +69464,20 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm +- name: frobenius_norm_out operator_name: frobenius_norm - overload_name: dim + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.dim(Tensor self, int[1] dim, bool keepdim=False) -> Tensor + schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -68276,7 +69495,7 @@ is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, bool) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -68295,6 +69514,60 @@ is_nullable: false name: keepdim type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nuclear_norm + operator_name: nuclear_norm + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool method_of: - Type - namespace @@ -68311,12 +69584,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: frobenius_norm_out - operator_name: frobenius_norm +- name: nuclear_norm_out + operator_name: nuclear_norm overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::frobenius_norm.out(Tensor self, int[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -68330,133 +69603,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - annotation: null default: false dynamic_type: bool is_nullable: false name: keepdim type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dim - size: 1 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm - operator_name: nuclear_norm - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm(Tensor self, bool keepdim=False) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: nuclear_norm_out - operator_name: nuclear_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::nuclear_norm.out(Tensor self, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -69995,20 +71148,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: addmm_out - operator_name: addmm - overload_name: out +- name: _sparse_mm_reduce_impl + operator_name: _sparse_mm_reduce_impl + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_mm_reduce_impl(Tensor self, Tensor other, str reduce) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, c10::string_view) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -70017,28 +71180,164 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat1 + name: other + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _sparse_mm_reduce_impl_backward + operator_name: _sparse_mm_reduce_impl_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_sparse_mm_reduce_impl_backward(Tensor self, Tensor grad_out, Tensor weight, str reduce, Tensor arg_out, bool[2] output_mask) -> (Tensor, Tensor) + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: mat2 + name: grad_out type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: beta - type: const at::Scalar & + name: weight + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: c10::string_view is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const at::Tensor &, ::std::array) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: arg_out + type: const at::Tensor & + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + method_of: + - Type + - namespace + mode: native + python_module: sparse + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: addmm_out + operator_name: addmm + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::addmm.out(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: mat2 + type: const at::Tensor & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: beta + type: const at::Scalar & + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Scalar &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -72152,7 +73451,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::_sparse_coo_tensor_unsafe(Tensor indices, Tensor values, SymInt[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -72703,7 +74002,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=False) -> Tensor arguments: - annotation: null dynamic_type: int64_t @@ -74066,20 +75365,64 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse(Tensor self) -> Tensor + schema_string: aten::to_sparse(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74101,20 +75444,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr(Tensor self) -> Tensor + schema_string: aten::to_sparse_csr(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74136,20 +75491,32 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc(Tensor self) -> Tensor + schema_string: aten::to_sparse_csc(Tensor self, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74171,7 +75538,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsr(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74184,7 +75551,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74197,6 +75570,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74218,7 +75597,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize) -> Tensor + schema_string: aten::to_sparse_bsc(Tensor self, int[2] blocksize, int? dense_dim=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74231,7 +75610,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74244,6 +75629,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional method_of: - Type - Tensor @@ -74312,7 +75703,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1) -> Tensor + schema_string: aten::mkldnn_reorder_conv2d_weight(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -74346,7 +75737,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -74380,6 +75777,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef method_of: - Type - namespace @@ -77882,7 +79285,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor) + schema_string: aten::_lstm_mps(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor, Tensor, Tensor, Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -77929,7 +79332,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -77997,6 +79400,9 @@ - dynamic_type: at::Tensor name: result4 type: at::Tensor + - dynamic_type: at::Tensor + name: result5 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -78009,7 +79415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) + schema_string: aten::lstm_mps_backward(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first) -> (Tensor, Tensor[], Tensor[]) arguments: - annotation: null dynamic_type: at::Tensor @@ -78041,6 +79447,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -78081,7 +79492,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) + schema_order_cpp_signature: ::std::tuple,::std::vector> (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -78113,6 +79524,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -80846,7 +82262,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pack_padded_sequence_backward(Tensor grad, int[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor + schema_string: aten::_pack_padded_sequence_backward(Tensor grad, SymInt[] input_size, Tensor batch_sizes, bool batch_first) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -88647,180 +90063,125 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag - operator_name: diag - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: diag_backward - operator_name: diag_backward - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::diag_backward(Tensor grad, SymInt[] input_sizes, int diagonal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_sizes - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: diagonal - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: true -- name: cross_out - operator_name: cross - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: diag + operator_name: diag + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::diag(Tensor self, int diagonal=0) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: diagonal + type: int64_t + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: cross_out + operator_name: cross + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::cross.out(Tensor self, Tensor other, int? dim=None, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false abstract: false device_guard: true with_gil: false @@ -89327,7 +90688,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::trace_backward(Tensor grad, int[] sizes) -> Tensor + schema_string: aten::trace_backward(Tensor grad, SymInt[] sizes) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -93066,7 +94427,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::index_select_backward(Tensor grad, int[] self_sizes, int dim, Tensor index) -> Tensor + schema_string: aten::index_select_backward(Tensor grad, SymInt[] self_sizes, int dim, Tensor index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94338,7 +95699,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, float label_smoothing=0.0) -> Tensor + schema_string: aten::cross_entropy_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, float label_smoothing=0.0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -94918,190 +96279,55 @@ with_gil: false deprecated: false has_math_kernel: true -- name: symeig_out - operator_name: symeig - overload_name: e +- name: svd_out + operator_name: svd + overload_name: U manual_kernel_registration: false category_override: '' - schema_string: aten::symeig.e(Tensor self, bool eigenvectors=False, bool upper=True, *, Tensor(a!) e, Tensor(b!) V) -> (Tensor(a!) eigenvalues, Tensor(b!) eigenvectors) + schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor - field_name: eigenvalues + field_name: U is_nullable: false - name: e + name: U output: true type: at::Tensor & - allocate: true annotation: b! dynamic_type: at::Tensor - field_name: eigenvectors - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: eigenvalues + field_name: S is_nullable: false - name: e + name: S output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: c! dynamic_type: at::Tensor - field_name: eigenvectors + field_name: V is_nullable: false name: V output: true type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: e - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: eigenvectors - name: V - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: symeig - operator_name: symeig - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::symeig(Tensor self, bool eigenvectors=False, bool upper=True) -> (Tensor eigenvalues, Tensor eigenvectors) - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - field_name: eigenvalues - name: eigenvalues - type: at::Tensor - - dynamic_type: at::Tensor - field_name: eigenvectors - name: eigenvectors_return - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _symeig_helper - operator_name: _symeig_helper - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper(Tensor self, bool eigenvectors, bool upper) -> (Tensor, Tensor) - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper + name: compute_uv type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -95109,100 +96335,16 @@ name: self type: const at::Tensor & - annotation: null + default: true dynamic_type: bool is_nullable: false - name: eigenvectors + name: some type: bool - annotation: null + default: true dynamic_type: bool is_nullable: false - name: upper - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result0 - type: at::Tensor - - dynamic_type: at::Tensor - name: result1 - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: svd_out - operator_name: svd - overload_name: U - manual_kernel_registration: false - category_override: '' - schema_string: aten::svd.U(Tensor self, bool some=True, bool compute_uv=True, *, Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) -> (Tensor(a!) U, Tensor(b!) S, Tensor(c!) V) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: U - is_nullable: false - name: U - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - field_name: S - is_nullable: false - name: S - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - field_name: V - is_nullable: false - name: V - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: some - type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: compute_uv + name: compute_uv type: bool - allocate: true annotation: a! @@ -101246,45 +102388,48 @@ with_gil: false deprecated: false has_math_kernel: true -- name: minimum - operator_name: minimum - overload_name: '' +- name: max_out + operator_name: max + overload_name: unary_out manual_kernel_registration: false category_override: '' - schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor + schema_string: aten::max.unary_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: self - type: const at::Tensor & + name: out + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: other + name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null + - allocate: true + annotation: a! dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Tensor & + name: out + output: true + type: at::Tensor & method_of: - Type - - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result - type: at::Tensor + name: out + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -101292,20 +102437,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: minimum_out +- name: minimum operator_name: minimum - overload_name: out + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum(Tensor self, Tensor other) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -101316,7 +102454,7 @@ is_nullable: false name: other type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101328,22 +102466,16 @@ is_nullable: false name: other type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type + - Tensor - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -101351,12 +102483,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: min_out - operator_name: min +- name: minimum_out + operator_name: minimum overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::minimum.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101405,147 +102537,17 @@ type: at::Tensor & inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: min + has_math_kernel: false +- name: min_out operator_name: min - overload_name: other - manual_kernel_registration: false - category_override: '' - schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: other - type: const at::Tensor & - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile - operator_name: quantile - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: q - type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - method_of: - - Type - - Tensor - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: false - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: true -- name: quantile_out - operator_name: quantile overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::min.out(Tensor self, Tensor other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101562,28 +102564,9 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101593,27 +102576,8 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: q + name: other type: const at::Tensor & - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: dim - type: c10::optional - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: keepdim - type: bool - - annotation: null - default: '"linear"' - dynamic_type: c10::string_view - is_nullable: false - kwarg_only: true - name: interpolation - type: c10::string_view - allocate: true annotation: a! dynamic_type: at::Tensor @@ -101637,12 +102601,58 @@ with_gil: false deprecated: false has_math_kernel: true +- name: min + operator_name: min + overload_name: other + manual_kernel_registration: false + category_override: '' + schema_string: aten::min.other(Tensor self, Tensor other) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: other + type: const at::Tensor & + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true - name: quantile operator_name: quantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101650,10 +102660,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101673,7 +102683,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101681,10 +102691,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101723,10 +102733,10 @@ has_math_kernel: true - name: quantile_out operator_name: quantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101741,10 +102751,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101764,7 +102774,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101772,10 +102782,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101818,12 +102828,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile - operator_name: nanquantile - overload_name: '' +- name: quantile + operator_name: quantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::quantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -101831,10 +102841,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101854,7 +102864,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101862,10 +102872,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101902,12 +102912,12 @@ with_gil: false deprecated: false has_math_kernel: true -- name: nanquantile_out - operator_name: nanquantile - overload_name: out +- name: quantile_out + operator_name: quantile + overload_name: scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::quantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -101922,10 +102932,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -101945,7 +102955,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -101953,10 +102963,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false name: q - type: const at::Tensor & + type: double - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102001,10 +103011,10 @@ has_math_kernel: true - name: nanquantile operator_name: nanquantile - overload_name: scalar + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor + schema_string: aten::nanquantile(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -102012,10 +103022,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102035,7 +103045,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102043,10 +103053,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102085,10 +103095,10 @@ has_math_kernel: true - name: nanquantile_out operator_name: nanquantile - overload_name: scalar_out + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nanquantile.out(Tensor self, Tensor q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -102103,10 +103113,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102126,7 +103136,7 @@ kwarg_only: true name: interpolation type: c10::string_view - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102134,10 +103144,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false name: q - type: double + type: const at::Tensor & - annotation: null default: c10::nullopt dynamic_type: int64_t @@ -102180,27 +103190,102 @@ with_gil: false deprecated: false has_math_kernel: true -- name: sort_out - operator_name: sort - overload_name: values +- name: nanquantile + operator_name: nanquantile + overload_name: scalar manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::nanquantile.scalar(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear') -> Tensor arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor - field_name: values is_nullable: false - name: values - output: true - type: at::Tensor & + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, c10::optional, bool, c10::string_view) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: double + is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dim + type: c10::optional + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: keepdim + type: bool + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + method_of: + - Type + - Tensor + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: false + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: true +- name: nanquantile_out + operator_name: nanquantile + overload_name: scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::nanquantile.scalar_out(Tensor self, float q, int? dim=None, bool keepdim=False, *, str interpolation='linear', Tensor(a!) out) -> Tensor(a!) + arguments: - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & - annotation: null @@ -102209,18 +103294,30 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view + is_nullable: false + kwarg_only: true + name: interpolation + type: c10::string_view + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, double, c10::optional, bool, c10::string_view, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -102228,31 +103325,34 @@ name: self type: const at::Tensor & - annotation: null - default: -1 - dynamic_type: int64_t + dynamic_type: double is_nullable: false + name: q + type: double + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true name: dim - type: int64_t + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: descending + name: keepdim type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - field_name: values + - annotation: null + default: '"linear"' + dynamic_type: c10::string_view is_nullable: false - name: values - output: true - type: at::Tensor & + kwarg_only: true + name: interpolation + type: c10::string_view - allocate: true - annotation: b! + annotation: a! dynamic_type: at::Tensor - field_name: indices is_nullable: false - name: indices + name: out output: true type: at::Tensor & method_of: @@ -102262,26 +103362,117 @@ python_module: '' returns: - dynamic_type: at::Tensor - field_name: values - name: values - type: at::Tensor & - - dynamic_type: at::Tensor - field_name: indices - name: indices + name: out type: at::Tensor & inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: sort_out operator_name: sort - overload_name: values_stable + overload_name: values manual_kernel_registration: false category_override: '' - schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + schema_string: aten::sort.values(Tensor self, int dim=-1, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + default: -1 + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: descending + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + field_name: values + is_nullable: false + name: values + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + field_name: indices + is_nullable: false + name: indices + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: values + name: values + type: at::Tensor & + - dynamic_type: at::Tensor + field_name: indices + name: indices + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: sort_out + operator_name: sort + overload_name: values_stable + manual_kernel_registration: false + category_override: '' + schema_string: aten::sort.values_stable(Tensor self, *, bool? stable, int dim=-1, bool descending=False, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices) arguments: - allocate: true annotation: a! @@ -103814,7 +105005,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward(Tensor grad_in, int[] input_sizes, int dim, int size, int step) -> Tensor + schema_string: aten::unfold_backward(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -105289,7 +106480,7 @@ overload_name: float_float manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float(float mean, float std, int[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor + schema_string: aten::normal.float_float(float mean, float std, SymInt[] size, *, Generator? generator=None, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor arguments: - annotation: null dynamic_type: double @@ -105393,7 +106584,7 @@ overload_name: float_float_out manual_kernel_registration: false category_override: '' - schema_string: aten::normal.float_float_out(float mean, float std, int[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::normal.float_float_out(float mean, float std, SymInt[] size, *, Generator? generator=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -105992,48 +107183,121 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: List +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_clamp_min.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106051,12 +107315,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: List +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_clamp_max_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106064,91 +107328,150 @@ name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: - - annotation: a! + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: List +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + schema_string: aten::_foreach_maximum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) - schema_order_arguments: + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar(Tensor[] self, Scalar scalar) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList - annotation: null - default: 1 dynamic_type: const at::Scalar & is_nullable: false - kwarg_only: true - name: alpha + name: scalar type: const at::Scalar & method_of: - Type @@ -106166,18 +107489,60 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: List +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + schema_string: aten::_foreach_minimum_.Scalar(Tensor(a!)[] self, Scalar scalar) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add + operator_name: _foreach_add + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -106190,9 +107555,68 @@ kwarg_only: true name: alpha type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -106222,12 +107646,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul +- name: _foreach_sub + operator_name: _foreach_sub overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_sub.List(Tensor[] self, Tensor[] other, *, Scalar alpha=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106239,7 +107663,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106251,6 +107682,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106267,12 +107705,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ +- name: _foreach_sub_ + operator_name: _foreach_sub_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_sub_.List(Tensor(a!)[] self, Tensor[] other, *, Scalar alpha=1) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106284,7 +107722,14 @@ is_nullable: false name: other type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106296,6 +107741,13 @@ is_nullable: false name: other type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & method_of: - Type - namespace @@ -106309,12 +107761,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div +- name: _foreach_mul + operator_name: _foreach_mul overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_mul.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106354,12 +107806,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ +- name: _foreach_mul_ + operator_name: _foreach_mul_ overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_mul_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106396,12 +107848,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add - operator_name: _foreach_add - overload_name: ScalarList +- name: _foreach_div + operator_name: _foreach_div + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_div.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106409,11 +107861,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106421,10 +107873,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106441,12 +107893,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_ - operator_name: _foreach_add_ - overload_name: ScalarList +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_div_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106454,11 +107906,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106466,10 +107918,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106483,12 +107935,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub - operator_name: _foreach_sub - overload_name: ScalarList +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_min.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106496,11 +107948,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106508,10 +107960,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106528,12 +107980,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_ - operator_name: _foreach_sub_ - overload_name: ScalarList +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_min_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106541,11 +107993,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106553,10 +108005,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106570,12 +108022,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div - operator_name: _foreach_div - overload_name: ScalarList +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_clamp_max.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106583,11 +108035,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106595,10 +108047,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106615,12 +108067,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_ - operator_name: _foreach_div_ - overload_name: ScalarList +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_clamp_max_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106628,11 +108080,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106640,10 +108092,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106657,12 +108109,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul - operator_name: _foreach_mul - overload_name: ScalarList +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -106670,11 +108122,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -106682,10 +108134,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106702,12 +108154,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_ - operator_name: _foreach_mul_ - overload_name: ScalarList +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () + schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -106715,11 +108167,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -106727,10 +108179,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: other + type: at::TensorList method_of: - Type - namespace @@ -106744,25 +108196,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_exp - operator_name: _foreach_exp - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList method_of: - Type - namespace @@ -106779,56 +108241,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_zero_ - operator_name: _foreach_zero_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: List manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_exp_ - operator_name: _foreach_exp_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () - arguments: + schema_order_cpp_signature: void (at::TensorList, at::TensorList) + schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false - name: self + name: other type: at::TensorList method_of: - Type @@ -106843,25 +108283,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt - operator_name: _foreach_sqrt - overload_name: '' +- name: _foreach_add + operator_name: _foreach_add + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_add.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106878,25 +108328,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sqrt_ - operator_name: _foreach_sqrt_ - overload_name: '' +- name: _foreach_add_ + operator_name: _foreach_add_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_add_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106910,25 +108370,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs - operator_name: _foreach_abs - overload_name: '' +- name: _foreach_sub + operator_name: _foreach_sub + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sub.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106945,25 +108415,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_abs_ - operator_name: _foreach_abs_ - overload_name: '' +- name: _foreach_sub_ + operator_name: _foreach_sub_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sub_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -106977,25 +108457,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos - operator_name: _foreach_acos - overload_name: '' +- name: _foreach_div + operator_name: _foreach_div + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_div.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107012,25 +108502,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_acos_ - operator_name: _foreach_acos_ - overload_name: '' +- name: _foreach_div_ + operator_name: _foreach_div_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_div_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107044,25 +108544,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin - operator_name: _foreach_asin - overload_name: '' +- name: _foreach_mul + operator_name: _foreach_mul + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_mul.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107079,25 +108589,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_asin_ - operator_name: _foreach_asin_ - overload_name: '' +- name: _foreach_mul_ + operator_name: _foreach_mul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_mul_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107111,25 +108631,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan - operator_name: _foreach_atan - overload_name: '' +- name: _foreach_clamp_min + operator_name: _foreach_clamp_min + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_min.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107146,25 +108676,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_atan_ - operator_name: _foreach_atan_ - overload_name: '' +- name: _foreach_clamp_min_ + operator_name: _foreach_clamp_min_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_min_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107178,25 +108718,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil - operator_name: _foreach_ceil - overload_name: '' +- name: _foreach_clamp_max + operator_name: _foreach_clamp_max + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_clamp_max.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107213,25 +108763,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_ceil_ - operator_name: _foreach_ceil_ - overload_name: '' +- name: _foreach_clamp_max_ + operator_name: _foreach_clamp_max_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_clamp_max_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107245,25 +108805,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos - operator_name: _foreach_cos - overload_name: '' +- name: _foreach_maximum + operator_name: _foreach_maximum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_maximum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107280,25 +108850,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cos_ - operator_name: _foreach_cos_ - overload_name: '' +- name: _foreach_maximum_ + operator_name: _foreach_maximum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_maximum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107312,25 +108892,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh - operator_name: _foreach_cosh - overload_name: '' +- name: _foreach_minimum + operator_name: _foreach_minimum + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_minimum.ScalarList(Tensor[] self, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107347,25 +108937,35 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_cosh_ - operator_name: _foreach_cosh_ - overload_name: '' +- name: _foreach_minimum_ + operator_name: _foreach_minimum_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_minimum_.ScalarList(Tensor(a!)[] self, Scalar[] scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -107379,12 +108979,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf - operator_name: _foreach_erf +- name: _foreach_exp + operator_name: _foreach_exp overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_exp(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107414,12 +109014,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erf_ - operator_name: _foreach_erf_ +- name: _foreach_zero_ + operator_name: _foreach_zero_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_zero_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107446,47 +109046,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_erfc - operator_name: _foreach_erfc - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_erfc_ - operator_name: _foreach_erfc_ +- name: _foreach_exp_ + operator_name: _foreach_exp_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_exp_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107513,12 +109078,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1 - operator_name: _foreach_expm1 +- name: _foreach_sqrt + operator_name: _foreach_sqrt overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_sqrt(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107548,12 +109113,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_expm1_ - operator_name: _foreach_expm1_ +- name: _foreach_sqrt_ + operator_name: _foreach_sqrt_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_sqrt_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107580,12 +109145,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor - operator_name: _foreach_floor +- name: _foreach_abs + operator_name: _foreach_abs overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_abs(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107615,12 +109180,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_floor_ - operator_name: _foreach_floor_ +- name: _foreach_abs_ + operator_name: _foreach_abs_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_abs_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107647,12 +109212,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log - operator_name: _foreach_log +- name: _foreach_acos + operator_name: _foreach_acos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_acos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107682,146 +109247,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log_ - operator_name: _foreach_log_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10 - operator_name: _foreach_log10 - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log10_ - operator_name: _foreach_log10_ - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () - arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: void (at::TensorList) - schema_order_arguments: - - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: true - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p - operator_name: _foreach_log1p - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] - arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList) - schema_order_arguments: - - annotation: null - dynamic_type: at::TensorList - is_nullable: false - name: self - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _foreach_log1p_ - operator_name: _foreach_log1p_ +- name: _foreach_acos_ + operator_name: _foreach_acos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_acos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107848,12 +109279,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2 - operator_name: _foreach_log2 +- name: _foreach_asin + operator_name: _foreach_asin overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_asin(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107883,12 +109314,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_log2_ - operator_name: _foreach_log2_ +- name: _foreach_asin_ + operator_name: _foreach_asin_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_asin_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107915,12 +109346,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg - operator_name: _foreach_neg +- name: _foreach_atan + operator_name: _foreach_atan overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_atan(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -107950,12 +109381,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_neg_ - operator_name: _foreach_neg_ +- name: _foreach_atan_ + operator_name: _foreach_atan_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_atan_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -107982,12 +109413,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan - operator_name: _foreach_tan +- name: _foreach_ceil + operator_name: _foreach_ceil overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_ceil(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108017,12 +109448,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tan_ - operator_name: _foreach_tan_ +- name: _foreach_ceil_ + operator_name: _foreach_ceil_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_ceil_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108049,12 +109480,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh - operator_name: _foreach_tanh +- name: _foreach_cos + operator_name: _foreach_cos overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cos(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108084,12 +109515,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_tanh_ - operator_name: _foreach_tanh_ +- name: _foreach_cos_ + operator_name: _foreach_cos_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cos_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108116,12 +109547,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin - operator_name: _foreach_sin +- name: _foreach_cosh + operator_name: _foreach_cosh overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_cosh(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108151,12 +109582,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sin_ - operator_name: _foreach_sin_ +- name: _foreach_cosh_ + operator_name: _foreach_cosh_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_cosh_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108183,12 +109614,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh - operator_name: _foreach_sinh +- name: _foreach_erf + operator_name: _foreach_erf overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erf(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108218,12 +109649,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sinh_ - operator_name: _foreach_sinh_ +- name: _foreach_erf_ + operator_name: _foreach_erf_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erf_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108250,12 +109681,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round - operator_name: _foreach_round +- name: _foreach_erfc + operator_name: _foreach_erfc overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_erfc(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108285,12 +109716,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_round_ - operator_name: _foreach_round_ +- name: _foreach_erfc_ + operator_name: _foreach_erfc_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_erfc_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108317,12 +109748,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma - operator_name: _foreach_lgamma +- name: _foreach_expm1 + operator_name: _foreach_expm1 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_expm1(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108352,12 +109783,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_lgamma_ - operator_name: _foreach_lgamma_ +- name: _foreach_expm1_ + operator_name: _foreach_expm1_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_expm1_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108384,12 +109815,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac - operator_name: _foreach_frac +- name: _foreach_floor + operator_name: _foreach_floor overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_floor(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108419,12 +109850,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_frac_ - operator_name: _foreach_frac_ +- name: _foreach_floor_ + operator_name: _foreach_floor_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_floor_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108451,12 +109882,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal - operator_name: _foreach_reciprocal +- name: _foreach_log + operator_name: _foreach_log overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108486,12 +109917,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_reciprocal_ - operator_name: _foreach_reciprocal_ +- name: _foreach_log_ + operator_name: _foreach_log_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108518,12 +109949,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid - operator_name: _foreach_sigmoid +- name: _foreach_log10 + operator_name: _foreach_log10 overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log10(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108553,12 +109984,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sigmoid_ - operator_name: _foreach_sigmoid_ +- name: _foreach_log10_ + operator_name: _foreach_log10_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log10_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108585,12 +110016,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc - operator_name: _foreach_trunc +- name: _foreach_log1p + operator_name: _foreach_log1p overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + schema_string: aten::_foreach_log1p(Tensor[] self) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -108620,12 +110051,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_trunc_ - operator_name: _foreach_trunc_ +- name: _foreach_log1p_ + operator_name: _foreach_log1p_ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + schema_string: aten::_foreach_log1p_(Tensor(a!)[] self) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -108652,57 +110083,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: Scalar +- name: _foreach_log2 + operator_name: _foreach_log2 + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_log2(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_log2_ + operator_name: _foreach_log2_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_log2_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg + operator_name: _foreach_neg + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_neg_ + operator_name: _foreach_neg_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_neg_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan + operator_name: _foreach_tan + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tan_ + operator_name: _foreach_tan_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tan_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108716,57 +110284,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: Scalar +- name: _foreach_tanh + operator_name: _foreach_tanh + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () + schema_string: aten::_foreach_tanh(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_tanh_ + operator_name: _foreach_tanh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_tanh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin + operator_name: _foreach_sin + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - default: 1 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sin_ + operator_name: _foreach_sin_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sin_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh + operator_name: _foreach_sinh + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sinh_ + operator_name: _foreach_sinh_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sinh_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: value - type: const at::Scalar & + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108780,55 +110485,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv_ - operator_name: _foreach_addcdiv_ - overload_name: ScalarList +- name: _foreach_round + operator_name: _foreach_round + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_round(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_round_ + operator_name: _foreach_round_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_round_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma + operator_name: _foreach_lgamma + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lgamma_ + operator_name: _foreach_lgamma_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lgamma_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac + operator_name: _foreach_frac + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_frac_ + operator_name: _foreach_frac_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_frac_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108842,55 +110686,194 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul_ - operator_name: _foreach_addcmul_ - overload_name: ScalarList +- name: _foreach_reciprocal + operator_name: _foreach_reciprocal + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () + schema_string: aten::_foreach_reciprocal(Tensor[] self) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_reciprocal_ + operator_name: _foreach_reciprocal_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_reciprocal_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid + operator_name: _foreach_sigmoid + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + name: self + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sigmoid_ + operator_name: _foreach_sigmoid_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sigmoid_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc + operator_name: _foreach_trunc + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc(Tensor[] self) -> Tensor[] + arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor1 + name: self type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: tensor2 + name: self type: at::TensorList - - annotation: null - dynamic_type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_trunc_ + operator_name: _foreach_trunc_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_trunc_(Tensor(a!)[] self) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList is_nullable: false - name: scalars - type: at::ArrayRef + name: self + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList method_of: - Type - namespace @@ -108904,14 +110887,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108932,9 +110915,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108960,25 +110943,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] + schema_string: aten::_foreach_addcmul_.Scalar(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -108999,9 +110979,9 @@ is_nullable: false name: value type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109027,25 +111007,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcdiv - operator_name: _foreach_addcdiv +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109065,9 +111042,9 @@ is_nullable: false name: scalars type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109092,25 +111069,22 @@ - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_addcmul - operator_name: _foreach_addcmul - overload_name: ScalarList +- name: _foreach_addcdiv_ + operator_name: _foreach_addcdiv_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + schema_string: aten::_foreach_addcdiv_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109126,13 +111100,13 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109148,34 +111122,31 @@ name: tensor2 type: at::TensorList - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::Tensor is_nullable: false name: scalars - type: at::ArrayRef + type: const at::Tensor & method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum - operator_name: _foreach_maximum - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcmul_.ScalarList(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> () arguments: - - annotation: null + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109183,11 +111154,21 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: a! dynamic_type: at::TensorList is_nullable: false name: self @@ -109195,30 +111176,37 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::TensorList - name: result - type: ::std::vector - inplace: false + returns: [] + inplace: true is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_ - operator_name: _foreach_maximum_ - overload_name: List +- name: _foreach_addcmul_ + operator_name: _foreach_addcmul_ + overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul_.Tensor(Tensor(a!)[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> () arguments: - annotation: a! dynamic_type: at::TensorList @@ -109228,9 +111216,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: a! dynamic_type: at::TensorList @@ -109240,8 +111238,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & method_of: - Type - namespace @@ -109255,12 +111263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum - operator_name: _foreach_minimum - overload_name: List +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List(Tensor[] self, Tensor[] other) -> Tensor[] + schema_string: aten::_foreach_addcdiv.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109270,9 +111278,20 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109282,8 +111301,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace @@ -109300,14 +111330,14 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_ - operator_name: _foreach_minimum_ - overload_name: List +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Scalar manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum_.List(Tensor(a!)[] self, Tensor[] other) -> () + schema_string: aten::_foreach_addcmul.Scalar(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar value=1) -> Tensor[] arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109315,11 +111345,22 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Scalar &) schema_order_arguments: - - annotation: a! + - annotation: null dynamic_type: at::TensorList is_nullable: false name: self @@ -109327,27 +111368,41 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + name: value + type: const at::Scalar & method_of: - Type - namespace mode: native python_module: '' - returns: [] - inplace: true + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false is_factory_method: false abstract: true device_guard: true with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm - operator_name: _foreach_norm - overload_name: Scalar +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv + overload_name: ScalarList manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + schema_string: aten::_foreach_addcdiv.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] arguments: - annotation: null dynamic_type: at::TensorList @@ -109355,12 +111410,21 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & - schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -109368,11 +111432,20 @@ name: self type: at::TensorList - annotation: null - default: 2 - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: ord - type: const at::Scalar & + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef method_of: - Type - namespace @@ -109389,41 +111462,497 @@ with_gil: false deprecated: false has_math_kernel: false -- name: bucketize - operator_name: bucketize +- name: _foreach_addcdiv + operator_name: _foreach_addcdiv overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + schema_string: aten::_foreach_addcdiv.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: self - type: const at::Tensor & + type: at::TensorList - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: boundaries - type: const at::Tensor & + name: tensor1 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::TensorList is_nullable: false - kwarg_only: true - name: out_int32 - type: bool + name: tensor2 + type: at::TensorList - annotation: null - default: false - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - kwarg_only: true - name: right - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: ScalarList + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.ScalarList(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Scalar[] scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, at::ArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_addcmul + operator_name: _foreach_addcmul + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcmul.Tensor(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_norm + operator_name: _foreach_norm + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar(Tensor[] self, Scalar ord=2) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.List(Tensor[] self, Tensor[] tensors1, Tensor[] weights) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: List + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.List(Tensor(a!)[] self, Tensor[] tensors1, Tensor[] weights) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp + operator_name: _foreach_lerp + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp.Scalar(Tensor[] self, Tensor[] tensors1, Scalar weight) -> Tensor[] + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: ::std::vector (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + name: result + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_ + operator_name: _foreach_lerp_ + overload_name: Scalar + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_lerp_.Scalar(Tensor(a!)[] self, Tensor[] tensors1, Scalar weight) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: weight + type: const at::Scalar & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: bucketize + operator_name: bucketize + overload_name: Tensor + manual_kernel_registration: false + category_override: '' + schema_string: aten::bucketize.Tensor(Tensor self, Tensor boundaries, *, bool out_int32=False, bool right=False) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: boundaries + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: out_int32 + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: right + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & @@ -109723,41 +112252,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Tensor_out @@ -111450,7 +113944,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -111545,7 +114039,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss_nd(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111626,7 +114120,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -111707,7 +114201,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -111813,7 +114307,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -111893,7 +114387,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112002,7 +114496,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112097,7 +114591,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::nll_loss2d.out(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112192,7 +114686,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, int ignore_index=-100) -> Tensor + schema_string: aten::nll_loss2d(Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, SymInt ignore_index=-100) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -112273,7 +114767,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::nll_loss2d_forward.output(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, *, Tensor(a!) output, Tensor(b!) total_weight) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -112379,7 +114873,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index) -> (Tensor output, Tensor total_weight) + schema_string: aten::nll_loss2d_forward(Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index) -> (Tensor output, Tensor total_weight) arguments: - annotation: null dynamic_type: at::Tensor @@ -112459,7 +114953,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::nll_loss2d_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -112568,7 +115062,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, int ignore_index, Tensor total_weight) -> Tensor + schema_string: aten::nll_loss2d_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight, int reduction, SymInt ignore_index, Tensor total_weight) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -116944,7 +119438,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -117005,7 +119499,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -117052,7 +119546,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d(Tensor self, int[3] output_size) -> Tensor + schema_string: aten::_adaptive_avg_pool3d(Tensor self, SymInt[3] output_size) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120595,7 +123089,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120656,7 +123150,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120703,7 +123197,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120774,7 +123268,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::reflection_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120831,7 +123325,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -120892,7 +123386,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -120939,7 +123433,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121010,7 +123504,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::reflection_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121067,7 +123561,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::reflection_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121128,7 +123622,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121175,7 +123669,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::reflection_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121246,7 +123740,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::reflection_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121303,7 +123797,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d.out(Tensor self, int[2] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad1d.out(Tensor self, SymInt[2] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121364,7 +123858,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d(Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d(Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121411,7 +123905,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, int[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad1d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[2] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121482,7 +123976,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, int[2] padding) -> Tensor + schema_string: aten::replication_pad1d_backward(Tensor grad_output, Tensor self, SymInt[2] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121539,7 +124033,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d.out(Tensor self, int[4] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad2d.out(Tensor self, SymInt[4] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121600,7 +124094,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d(Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d(Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121647,7 +124141,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, int[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad2d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[4] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121718,7 +124212,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, int[4] padding) -> Tensor + schema_string: aten::replication_pad2d_backward(Tensor grad_output, Tensor self, SymInt[4] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121775,7 +124269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d.out(Tensor self, int[6] padding, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::replication_pad3d.out(Tensor self, SymInt[6] padding, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121836,7 +124330,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d(Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d(Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -121883,7 +124377,7 @@ overload_name: grad_input manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, int[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) + schema_string: aten::replication_pad3d_backward.grad_input(Tensor grad_output, Tensor self, SymInt[6] padding, *, Tensor(a!) grad_input) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -121954,7 +124448,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, int[6] padding) -> Tensor + schema_string: aten::replication_pad3d_backward(Tensor grad_output, Tensor self, SymInt[6] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122011,7 +124505,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_circular(Tensor self, int[] pad) -> Tensor + schema_string: aten::_pad_circular(Tensor self, SymInt[] pad) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122056,7 +124550,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_pad_enum(Tensor self, int[] pad, int mode, float? value=None) -> Tensor + schema_string: aten::_pad_enum(Tensor self, SymInt[] pad, int mode, float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122123,7 +124617,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::pad(Tensor self, int[] pad, str mode="constant", float? value=None) -> Tensor + schema_string: aten::pad(Tensor self, SymInt[] pad, str mode="constant", float? value=None) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122247,86 +124741,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_linear1d_backward - operator_name: upsample_linear1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_linear1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_bilinear2d operator_name: upsample_bilinear2d overload_name: vec @@ -122387,33 +124806,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bilinear2d_backward - operator_name: upsample_bilinear2d_backward + has_math_kernel: true +- name: _upsample_bilinear2d_aa + operator_name: _upsample_bilinear2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122424,23 +124838,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122462,17 +124871,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa - operator_name: _upsample_bilinear2d_aa + has_math_kernel: true +- name: upsample_trilinear3d + operator_name: upsample_trilinear3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122527,33 +124936,28 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward - operator_name: _upsample_bilinear2d_aa_backward + has_math_kernel: true +- name: upsample_bicubic2d + operator_name: upsample_bicubic2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122564,23 +124968,18 @@ is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - annotation: null dynamic_type: bool is_nullable: false @@ -122602,17 +125001,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d - operator_name: upsample_trilinear3d + has_math_kernel: true +- name: _upsample_bicubic2d_aa + operator_name: _upsample_bicubic2d_aa overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122667,65 +125066,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_trilinear3d_backward - operator_name: upsample_trilinear3d_backward + has_math_kernel: true +- name: upsample_nearest1d + operator_name: upsample_nearest1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122742,17 +125121,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d - operator_name: upsample_bicubic2d + has_math_kernel: true +- name: _upsample_nearest_exact1d + operator_name: _upsample_nearest_exact1d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122764,17 +125143,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122786,11 +125160,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122807,65 +125176,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_bicubic2d_backward - operator_name: upsample_bicubic2d_backward + has_math_kernel: true +- name: upsample_nearest2d + operator_name: upsample_nearest2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122882,17 +125231,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa - operator_name: _upsample_bicubic2d_aa + has_math_kernel: true +- name: _upsample_nearest_exact2d + operator_name: _upsample_nearest_exact2d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -122904,17 +125253,12 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -122926,11 +125270,6 @@ is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -122947,65 +125286,45 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward - operator_name: _upsample_bicubic2d_aa_backward + has_math_kernel: true +- name: upsample_nearest3d + operator_name: upsample_nearest3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors) -> Tensor + schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true name: scale_factors type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: input type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true name: output_size type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true @@ -123022,17 +125341,17 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: upsample_nearest1d - operator_name: upsample_nearest1d + has_math_kernel: true +- name: _upsample_nearest_exact3d + operator_name: _upsample_nearest_exact3d overload_name: vec manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor + schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -123077,676 +125396,11 @@ type: at::Tensor inplace: false is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d - operator_name: _upsample_nearest_exact1d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest1d_backward - operator_name: upsample_nearest1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact1d_backward - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d - operator_name: upsample_nearest2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d - operator_name: _upsample_nearest_exact2d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest2d_backward - operator_name: upsample_nearest2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact2d_backward - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d - operator_name: upsample_nearest3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d - operator_name: _upsample_nearest_exact3d - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec(Tensor input, SymInt[]? output_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: upsample_nearest3d_backward - operator_name: upsample_nearest3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _upsample_nearest_exact3d_backward - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec - manual_kernel_registration: false - category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - method_of: - - Type - - namespace - mode: native - python_module: nn - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false + has_math_kernel: true - name: upsample_linear1d_out operator_name: upsample_linear1d overload_name: out @@ -128360,7 +130014,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128499,7 +130153,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] output_padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, SymInt[2] output_padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -128624,7 +130278,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv_transpose3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -128763,7 +130417,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] output_padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_transpose3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, SymInt[3] output_padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129541,7 +131195,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conv_depthwise2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129658,7 +131312,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, int[2] padding, int[2] dilation) -> Tensor + schema_string: aten::_conv_depthwise2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias, int[2] stride, SymInt[2] padding, int[2] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129761,7 +131415,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation) -> Tensor + schema_string: aten::conv_depthwise3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -129864,7 +131518,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slow_conv3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -129975,7 +131629,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0) -> Tensor + schema_string: aten::slow_conv3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130072,7 +131726,7 @@ overload_name: output manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, *, Tensor(a!) output) -> Tensor(a!) + schema_string: aten::slow_conv3d_forward.output(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, *, Tensor(a!) output) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -130177,7 +131831,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding) -> Tensor + schema_string: aten::slow_conv3d_forward(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130268,7 +131922,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated2d(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -130379,7 +132033,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1) -> Tensor + schema_string: aten::slow_conv_dilated3d(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -147845,7 +149499,7 @@ overload_name: int manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int(Tensor self, int dim, int index) -> Tensor + schema_string: aten::select_copy.int(Tensor self, int dim, SymInt index) -> Tensor arguments: - annotation: null dynamic_type: at::Tensor @@ -148018,7 +149672,7 @@ overload_name: Tensor manual_kernel_registration: false category_override: '' - schema_string: aten::split_copy.Tensor(Tensor self, int split_size, int dim=0) -> Tensor[] + schema_string: aten::split_copy.Tensor(Tensor self, SymInt split_size, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148075,7 +149729,7 @@ overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::split_with_sizes_copy(Tensor self, int[] split_sizes, int dim=0) -> Tensor[] + schema_string: aten::split_with_sizes_copy(Tensor self, SymInt[] split_sizes, int dim=0) -> Tensor[] arguments: - annotation: null dynamic_type: at::Tensor @@ -148207,6 +149861,51 @@ with_gil: false deprecated: false has_math_kernel: false +- name: squeeze_copy + operator_name: squeeze_copy + overload_name: dims + manual_kernel_registration: false + category_override: '' + schema_string: aten::squeeze_copy.dims(Tensor self, int[] dim) -> Tensor + arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dim + type: at::IntArrayRef + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: t_copy operator_name: t_copy overload_name: '' @@ -148669,221 +150368,32 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy - operator_name: view_copy - overload_name: dtype - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy - operator_name: unfold_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dimension - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: size - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: alias_copy - operator_name: alias_copy - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::alias_copy(Tensor self) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _fw_primal_copy_out - operator_name: _fw_primal_copy - overload_name: out +- name: unbind_copy_out + operator_name: unbind_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -148891,26 +150401,24 @@ name: self type: const at::Tensor & - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -148918,117 +150426,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _make_dual_copy_out - operator_name: _make_dual_copy - overload_name: out +- name: split_copy_out + operator_name: split_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_copy.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: tangent - type: const at::Tensor & + name: split_size + type: int64_t - annotation: null + default: 0 dynamic_type: int64_t is_nullable: false - name: level + name: dim type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) + schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: primal - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: tangent + name: self type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: level + name: split_size type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_as_real_copy_out - operator_name: view_as_real_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149036,146 +150494,67 @@ with_gil: false deprecated: false has_math_kernel: false -- name: view_as_complex_copy_out - operator_name: view_as_complex_copy +- name: split_with_sizes_copy_out + operator_name: split_with_sizes_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::split_with_sizes_copy.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _conj_copy_out - operator_name: _conj_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: out - output: true - type: at::Tensor & + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _neg_view_copy_out - operator_name: _neg_view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::IntArrayRef is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: split_sizes + type: at::IntArrayRef - annotation: null - dynamic_type: at::Tensor + default: 0 + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & + name: dim + type: int64_t - allocate: true annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false name: out output: true - type: at::Tensor & + type: at::TensorList method_of: - Type - namespace mode: native python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & + returns: [] inplace: false is_factory_method: false abstract: true @@ -149183,20 +150562,13 @@ with_gil: false deprecated: false has_math_kernel: false -- name: as_strided_copy_out - operator_name: as_strided_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy(Tensor self, SymInt[] size) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -149207,18 +150579,7 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::IntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149230,24 +150591,6 @@ is_nullable: false name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: storage_offset - type: c10::optional - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149255,8 +150598,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149264,31 +150607,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_broadcast_to_copy_out - operator_name: _sparse_broadcast_to_copy - overload_name: out +- name: view_copy + operator_name: view_copy + overload_name: dtype manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype(Tensor self, ScalarType dtype) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::ScalarType is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: dtype + type: at::ScalarType + schema_order_cpp_signature: at::Tensor (const at::Tensor &, at::ScalarType) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149296,17 +150632,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: at::ScalarType is_nullable: false - name: out - output: true - type: at::Tensor & + name: dtype + type: at::ScalarType method_of: - Type - namespace @@ -149314,8 +150643,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149323,44 +150652,34 @@ with_gil: false deprecated: false has_math_kernel: false -- name: diagonal_copy_out - operator_name: diagonal_copy - overload_name: out +- name: unfold_copy + operator_name: unfold_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy(Tensor self, int dimension, int size, int step) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, int64_t) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149368,30 +150687,20 @@ name: self type: const at::Tensor & - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: offset + name: dimension type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim1 + name: size type: int64_t - annotation: null - default: 1 dynamic_type: int64_t is_nullable: false - name: dim2 + name: step type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149399,8 +150708,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149408,63 +150717,25 @@ with_gil: false deprecated: false has_math_kernel: false -- name: expand_copy_out - operator_name: expand_copy - overload_name: out +- name: alias_copy + operator_name: alias_copy + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy(Tensor self) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) + schema_order_cpp_signature: at::Tensor (const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: implicit - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & method_of: - Type - namespace @@ -149472,8 +150743,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149481,31 +150752,30 @@ with_gil: false deprecated: false has_math_kernel: false -- name: permute_copy_out - operator_name: permute_copy - overload_name: out +- name: to_padded_tensor + operator_name: to_padded_tensor + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor(Tensor self, float padding, SymInt[]? output_size=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: double is_nullable: false - name: dims - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149513,26 +150783,25 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dims - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: out - output: true - type: at::Tensor & + name: padding + type: double + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: output_size + type: at::OptionalIntArrayRef method_of: - Type - - namespace + - Tensor mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149540,36 +150809,24 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _reshape_alias_copy_out - operator_name: _reshape_alias_copy - overload_name: out +- name: _nested_tensor_softmax_with_shape + operator_name: _nested_tensor_softmax_with_shape + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: stride - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: query + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -149577,22 +150834,10 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: query + type: const at::Tensor & method_of: - Type - namespace @@ -149600,8 +150845,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -149609,449 +150854,219 @@ with_gil: false deprecated: false has_math_kernel: false -- name: select_copy_out - operator_name: select_copy - overload_name: int_out +- name: _transformer_encoder_layer_fwd + operator_name: _transformer_encoder_layer_fwd + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::select_copy.int_out(Tensor self, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: index + name: num_heads type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: index - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: detach_copy_out - operator_name: detach_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: qkv_bias + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + - annotation: null + dynamic_type: bool + is_nullable: false + name: use_gelu + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: norm_first + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_1 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: slice_copy_out - operator_name: slice_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_1 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: start - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: end - type: c10::optional + name: ffn_weight_1 + type: const at::Tensor & - annotation: null - default: 1 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_bias_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_weight_2 type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t + name: ffn_bias_2 + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: start - type: c10::optional + name: mask + type: const c10::optional & - annotation: null default: c10::nullopt dynamic_type: int64_t is_nullable: true - name: end + name: mask_type type: c10::optional - - annotation: null - default: 1 - dynamic_type: int64_t - is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_copy_out - operator_name: split_copy - overload_name: Tensor_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_copy.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: src type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: split_size + name: embed_dim type: int64_t - annotation: null - default: 0 dynamic_type: int64_t is_nullable: false - name: dim + name: num_heads type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, int64_t, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: split_size - type: int64_t - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: split_with_sizes_copy_out - operator_name: split_with_sizes_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::split_with_sizes_copy.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: split_sizes - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, at::IntArrayRef, int64_t, at::TensorList) - schema_order_arguments: + name: proj_weight + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: bool is_nullable: false - name: split_sizes - type: at::IntArrayRef + name: use_gelu + type: bool - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList + name: norm_first + type: bool + - annotation: null + dynamic_type: double is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: eps + type: double + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: norm_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_bias_1 type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: norm_weight_2 type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: squeeze_copy_out - operator_name: squeeze_copy - overload_name: dim_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + name: norm_bias_2 + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: ffn_weight_1 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_1 type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: + name: ffn_weight_2 + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: ffn_bias_2 type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150059,8 +151074,8 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150068,412 +151083,153 @@ with_gil: false deprecated: false has_math_kernel: false -- name: t_copy_out - operator_name: t_copy - overload_name: out +- name: _native_multi_head_attention + operator_name: _native_multi_head_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: transpose_copy_out - operator_name: transpose_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: dim0 + name: embed_dim type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: dim1 + name: num_head type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim0 - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim1 - type: int64_t - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unsqueeze_copy_out - operator_name: unsqueeze_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & + name: qkv_bias + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _indices_copy_out - operator_name: _indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: need_weights + type: bool - annotation: null - dynamic_type: at::Tensor + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: _values_copy_out - operator_name: _values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: indices_copy_out - operator_name: indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor + - annotation: null + dynamic_type: int64_t is_nullable: false - name: out - output: true - type: at::Tensor & + name: embed_dim + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: int64_t is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: + name: num_head + type: int64_t - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: values_copy_out - operator_name: values_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: qkv_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_weight type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: crow_indices_copy_out - operator_name: crow_indices_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: proj_bias type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: mask + type: const c10::optional & + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_weights + type: bool + - annotation: null + default: true + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: average_attn_weights + type: bool + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: mask_type + type: c10::optional method_of: - Type - namespace @@ -150481,8 +151237,11 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -150490,409 +151249,287 @@ with_gil: false deprecated: false has_math_kernel: false -- name: col_indices_copy_out - operator_name: col_indices_copy - overload_name: out +- name: scaled_dot_product_attention + operator_name: scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> Tensor arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unbind_copy_out - operator_name: unbind_copy - overload_name: int_out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unbind_copy.int_out(Tensor self, int dim=0, *, Tensor(a!)[] out) -> () - arguments: - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: self - type: const at::Tensor & + name: dropout_p + type: double - annotation: null - default: 0 - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: dim - type: int64_t - schema_order_cpp_signature: void (const at::Tensor &, int64_t, at::TensorList) + name: is_causal + type: bool + schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - name: dim - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::TensorList - is_nullable: false - name: out - output: true - type: at::TensorList - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: [] - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: size - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) - schema_order_arguments: - - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: at::IntArrayRef - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: view_copy_out - operator_name: view_copy - overload_name: dtype_out + has_math_kernel: true +- name: _scaled_dot_product_attention + operator_name: _scaled_dot_product_attention + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - annotation: null - dynamic_type: at::ScalarType - is_nullable: false - name: dtype - type: at::ScalarType - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: unfold_copy_out - operator_name: unfold_copy - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: value + type: const at::Tensor & - annotation: null + default: '{}' dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & + is_nullable: true + name: attn_mask + type: const c10::optional & - annotation: null - dynamic_type: int64_t + default: 0.0 + dynamic_type: double is_nullable: false - name: dimension - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: size - type: int64_t + name: need_attn_weights + type: bool - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: dimension - type: int64_t + name: value + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double is_nullable: false - name: size - type: int64_t + name: dropout_p + type: double - annotation: null - dynamic_type: int64_t + default: false + dynamic_type: bool is_nullable: false - name: step - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor + name: need_attn_weights + type: bool + - annotation: null + default: false + dynamic_type: bool is_nullable: false - name: out - output: true - type: at::Tensor & + name: is_causal + type: bool method_of: - Type - namespace mode: native - python_module: '' + python_module: nn returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: alias_copy_out - operator_name: alias_copy - overload_name: out + has_math_kernel: true +- name: _fused_sdp_choice + operator_name: _fused_sdp_choice + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fused_sdp_choice(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False) -> int arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: key type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false -- name: to_padded_tensor - operator_name: to_padded_tensor - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::to_padded_tensor(Tensor self, float padding, int[]? output_size=None) -> Tensor - arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor (const at::Tensor &, double, at::OptionalIntArrayRef) + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: int64_t (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key type: const at::Tensor & - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: padding + name: dropout_p type: double - annotation: null - default: c10::nullopt - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - - dynamic_type: at::Tensor + - dynamic_type: int64_t name: result - type: at::Tensor + type: int64_t inplace: false is_factory_method: false abstract: true @@ -150900,35 +151537,93 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_softmax_with_shape - operator_name: _nested_tensor_softmax_with_shape +- name: _scaled_dot_product_attention_math + operator_name: _scaled_dot_product_attention_math overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_softmax_with_shape(Tensor self, Tensor query) -> Tensor + schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool is_causal=False, Tensor? dropout_mask=None) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: query + name: key type: const at::Tensor & - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &) - schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: value type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, const c10::optional &) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: query type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value + type: const at::Tensor & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: attn_mask + type: const c10::optional & + - annotation: null + default: 0.0 + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: dropout_mask + type: const c10::optional & method_of: - Type - namespace @@ -150936,72 +151631,134 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 type: at::Tensor inplace: false is_factory_method: false - abstract: true + abstract: false device_guard: true with_gil: false deprecated: false - has_math_kernel: false -- name: _nested_tensor_layer_norm - operator_name: _nested_tensor_layer_norm + has_math_kernel: true +- name: _scaled_dot_product_flash_attention + operator_name: _scaled_dot_product_flash_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_layer_norm(Tensor self, Tensor? weight, Tensor? bias, float eps) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention(Tensor query, Tensor key, Tensor value, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False) -> (Tensor ouput, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, int philox_seed, int philox_offset, Tensor debug_attn_mask) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const c10::optional &, const c10::optional &, double) + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, double, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & + is_nullable: false + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null + default: 0.0 dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool method_of: - Type - - Tensor + - namespace mode: native python_module: '' returns: - dynamic_type: at::Tensor - name: result + field_name: ouput + name: ouput + type: at::Tensor + - dynamic_type: at::Tensor + field_name: logsumexp + name: logsumexp + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_q + name: cum_seq_q + type: at::Tensor + - dynamic_type: at::Tensor + field_name: cum_seq_k + name: cum_seq_k + type: at::Tensor + - dynamic_type: int64_t + field_name: max_q + name: max_q + type: int64_t + - dynamic_type: int64_t + field_name: max_k + name: max_k + type: int64_t + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151010,219 +151767,353 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _transformer_encoder_layer_fwd - operator_name: _transformer_encoder_layer_fwd +- name: _scaled_dot_product_flash_attention_backward + operator_name: _scaled_dot_product_flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_transformer_encoder_layer_fwd(Tensor src, int embed_dim, int num_heads, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, bool use_gelu, bool norm_first, float eps, Tensor norm_weight_1, Tensor norm_bias_1, Tensor norm_weight_2, Tensor norm_bias_2, Tensor ffn_weight_1, Tensor ffn_bias_1, Tensor ffn_weight_2, Tensor ffn_bias_2, Tensor? mask=None, int? mask_type=None) -> Tensor + schema_string: aten::_scaled_dot_product_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor grad_query, Tensor grad_key, Tensor grad_value) arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: src + name: grad_out type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: embed_dim - type: int64_t + name: query + type: const at::Tensor & - annotation: null - dynamic_type: int64_t + dynamic_type: at::Tensor is_nullable: false - name: num_heads - type: int64_t + name: key + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: use_gelu - type: bool + name: cum_seq_k + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: norm_first - type: bool + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null dynamic_type: double is_nullable: false - name: eps + name: dropout_p type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: grad_out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: logsumexp type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: cum_seq_q type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: cum_seq_k type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t - annotation: null - default: c10::nullopt dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: at::Tensor (const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool, double, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, c10::optional) - schema_order_arguments: + is_nullable: false + name: max_k + type: int64_t - annotation: null - dynamic_type: at::Tensor + dynamic_type: double is_nullable: false - name: src - type: const at::Tensor & + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: philox_seed type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_heads + name: philox_offset type: int64_t + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + field_name: grad_query + name: grad_query + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_key + name: grad_key + type: at::Tensor + - dynamic_type: at::Tensor + field_name: grad_value + name: grad_value + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention + operator_name: _scaled_dot_product_efficient_attention + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention(Tensor query, Tensor key, Tensor value, bool compute_log_sumexp, bool is_causal=False) -> (Tensor, Tensor) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: compute_log_sumexp + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: query + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: key + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: value type: const at::Tensor & - annotation: null dynamic_type: bool is_nullable: false - name: use_gelu + name: compute_log_sumexp type: bool - annotation: null + default: false dynamic_type: bool is_nullable: false - name: norm_first + name: is_causal type: bool + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _scaled_dot_product_efficient_attention_backward + operator_name: _scaled_dot_product_efficient_attention_backward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_scaled_dot_product_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) + arguments: - annotation: null - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: eps - type: double + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_1 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_1 + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_weight_2 + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: norm_bias_2 + name: out type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_1 + name: logsumexp type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_1 + name: grad_out_ type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_weight_2 + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: ffn_bias_2 + name: key type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: value + type: const at::Tensor & - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional + dynamic_type: at::Tensor + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: chunk_grad_outputs + type: bool method_of: - Type - namespace @@ -151230,7 +152121,13 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 type: at::Tensor inplace: false is_factory_method: false @@ -151239,12 +152136,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _native_multi_head_attention - operator_name: _native_multi_head_attention +- name: _chunk_grad_outputs_efficient_attention + operator_name: _chunk_grad_outputs_efficient_attention overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_native_multi_head_attention(Tensor query, Tensor key, Tensor value, int embed_dim, int num_head, Tensor qkv_weight, Tensor qkv_bias, Tensor proj_weight, Tensor proj_bias, Tensor? mask=None, bool need_weights=True, bool average_attn_weights=True, int? mask_type=None) -> (Tensor, Tensor) + schema_string: aten::_chunk_grad_outputs_efficient_attention(Tensor query, Tensor key, Tensor value, bool is_causal=False) -> bool arguments: - annotation: null dynamic_type: at::Tensor @@ -151262,61 +152159,57 @@ name: value type: const at::Tensor & - annotation: null - dynamic_type: int64_t - is_nullable: false - name: embed_dim - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: num_head - type: int64_t - - annotation: null - dynamic_type: at::Tensor + default: false + dynamic_type: bool is_nullable: false - name: qkv_weight - type: const at::Tensor & + name: is_causal + type: bool + schema_order_cpp_signature: bool (const at::Tensor &, const at::Tensor &, const at::Tensor &, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: value type: const at::Tensor & - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & - - annotation: null - default: true + default: false dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - - annotation: null - default: true - dynamic_type: bool - is_nullable: false - name: average_attn_weights + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: bool + name: result type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, bool, bool, c10::optional) - schema_order_arguments: + inplace: false + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false +- name: _flash_attention_forward + operator_name: _flash_attention_forward + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_flash_attention_forward(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, bool return_debug_mask) -> (Tensor output, Tensor softmax_logsumexp, int philox_seed, int philox_offset, Tensor debug_attn_mask) + arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151332,60 +152225,93 @@ is_nullable: false name: value type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & - annotation: null dynamic_type: int64_t is_nullable: false - name: embed_dim + name: max_q type: int64_t - annotation: null dynamic_type: int64_t is_nullable: false - name: num_head + name: max_k type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + name: is_causal + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: return_debug_mask + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, bool) + schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_weight + name: query type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: qkv_bias + name: key type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_weight + name: value type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: proj_bias + name: cum_seq_q type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: mask - type: const c10::optional & + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t + - annotation: null + dynamic_type: double + is_nullable: false + name: dropout_p + type: double - annotation: null - default: true dynamic_type: bool is_nullable: false - name: need_weights + name: is_causal type: bool - annotation: null - default: true dynamic_type: bool is_nullable: false - name: average_attn_weights + name: return_debug_mask type: bool - - annotation: null - default: c10::nullopt - dynamic_type: int64_t - is_nullable: true - name: mask_type - type: c10::optional method_of: - Type - namespace @@ -151393,10 +152319,24 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: result0 + field_name: output + name: output type: at::Tensor - dynamic_type: at::Tensor - name: result1 + field_name: softmax_logsumexp + name: softmax_logsumexp + type: at::Tensor + - dynamic_type: int64_t + field_name: philox_seed + name: philox_seed + type: int64_t + - dynamic_type: int64_t + field_name: philox_offset + name: philox_offset + type: int64_t + - dynamic_type: at::Tensor + field_name: debug_attn_mask + name: debug_attn_mask type: at::Tensor inplace: false is_factory_method: false @@ -151405,13 +152345,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention - operator_name: _scaled_dot_product_attention +- name: _flash_attention_backward + operator_name: _flash_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_flash_attention_backward(Tensor grad_out, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal, int philox_seed, int philox_offset) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151428,31 +152373,62 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool, int64_t, int64_t) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151469,34 +152445,60 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: logsumexp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_q + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cum_seq_k + type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_q + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: max_k + type: int64_t - annotation: null - default: 0.0 dynamic_type: double is_nullable: false name: dropout_p type: double - annotation: null - default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null - default: false - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: is_causal - type: bool + name: philox_seed + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: philox_offset + type: int64_t method_of: - Type - namespace mode: native - python_module: nn + python_module: '' returns: - dynamic_type: at::Tensor name: result0 @@ -151504,19 +152506,22 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true -- name: _scaled_dot_product_attention_forward - operator_name: _scaled_dot_product_attention_forward + has_math_kernel: false +- name: _efficient_attention_forward + operator_name: _efficient_attention_forward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_forward(Tensor query, Tensor key, Tensor value, Tensor? cu_seqlens_q, Tensor? cu_seqlens_k, int? max_seqlen_q, bool compute_log_sumexp=False, bool causal=False) -> (Tensor, Tensor) arguments: - annotation: null dynamic_type: at::Tensor @@ -151534,30 +152539,33 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, c10::optional, bool, bool) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -151575,28 +152583,31 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor is_nullable: true - name: attn_mask + name: cu_seqlens_q type: const c10::optional & - annotation: null - default: 0.0 - dynamic_type: double - is_nullable: false - name: dropout_p - type: double + dynamic_type: at::Tensor + is_nullable: true + name: cu_seqlens_k + type: const c10::optional & + - annotation: null + dynamic_type: int64_t + is_nullable: true + name: max_seqlen_q + type: c10::optional - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: compute_log_sumexp type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: causal type: bool method_of: - Type @@ -151617,13 +152628,18 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _scaled_dot_product_attention_math - operator_name: _scaled_dot_product_attention_math +- name: _efficient_attention_backward + operator_name: _efficient_attention_backward overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::_scaled_dot_product_attention_math(Tensor query, Tensor key, Tensor value, Tensor? attn_mask=None, float dropout_p=0.0, bool need_attn_weights=False, bool is_causal=False) -> (Tensor, Tensor) + schema_string: aten::_efficient_attention_backward(Tensor grad_out_, Tensor query, Tensor key, Tensor value, Tensor out, Tensor logsumexp, bool is_causal=False, bool chunk_grad_outputs=False) -> (Tensor, Tensor, Tensor) arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151640,31 +152656,34 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, double, bool, bool) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, bool) schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_out_ + type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -151681,28 +152700,26 @@ name: value type: const at::Tensor & - annotation: null - default: '{}' dynamic_type: at::Tensor - is_nullable: true - name: attn_mask - type: const c10::optional & + is_nullable: false + name: out + type: const at::Tensor & - annotation: null - default: 0.0 - dynamic_type: double + dynamic_type: at::Tensor is_nullable: false - name: dropout_p - type: double + name: logsumexp + type: const at::Tensor & - annotation: null default: false dynamic_type: bool is_nullable: false - name: need_attn_weights + name: is_causal type: bool - annotation: null default: false dynamic_type: bool is_nullable: false - name: is_causal + name: chunk_grad_outputs type: bool method_of: - Type @@ -151716,13 +152733,16 @@ - dynamic_type: at::Tensor name: result1 type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor inplace: false is_factory_method: false - abstract: false + abstract: true device_guard: true with_gil: false deprecated: false - has_math_kernel: true + has_math_kernel: false - name: _triton_scaled_dot_attention operator_name: _triton_scaled_dot_attention overload_name: '' @@ -152001,121 +153021,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _flash_scaled_dot_product_attention - operator_name: _flash_scaled_dot_product_attention - overload_name: '' - manual_kernel_registration: false - category_override: '' - schema_string: aten::_flash_scaled_dot_product_attention(Tensor query, Tensor key, Tensor value, Tensor cum_seq_q, Tensor cum_seq_k, int max_q, int max_k, float dropout_p, bool is_causal) -> Tensor - arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - schema_order_cpp_signature: at::Tensor (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, int64_t, double, bool) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: query - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: key - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: value - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_q - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: cum_seq_k - type: const at::Tensor & - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_q - type: int64_t - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: max_k - type: int64_t - - annotation: null - dynamic_type: double - is_nullable: false - name: dropout_p - type: double - - annotation: null - dynamic_type: bool - is_nullable: false - name: is_causal - type: bool - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: result - type: at::Tensor - inplace: false - is_factory_method: false - abstract: true - device_guard: true - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_decoder_only_layer_fwd operator_name: _transformer_decoder_only_layer_fwd overload_name: '' @@ -157482,6 +158387,200 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_ + operator_name: _fused_adamw_ + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw_(Tensor(a!)[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> () + arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: true + is_factory_method: false + abstract: true + device_guard: true + with_gil: false + deprecated: false + has_math_kernel: false - name: _new_zeros_with_same_feature_meta_out operator_name: _new_zeros_with_same_feature_meta overload_name: out @@ -159780,7 +160879,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::constant_pad_nd.out(Tensor self, int[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::constant_pad_nd.out(Tensor self, SymInt[] pad, Scalar value=0, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159851,7 +160950,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -159980,7 +161079,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::convolution_backward.out(Tensor grad_output, Tensor input, Tensor weight, SymInt[]? bias_sizes, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) arguments: - allocate: true annotation: a! @@ -160465,7 +161564,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, int[] padding, int[] dilation, bool transposed, int[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[] stride, SymInt[] padding, int[] dilation, bool transposed, SymInt[] output_padding, int groups, bool benchmark, bool deterministic, bool cudnn_enabled, bool allow_tf32, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -162568,6 +163667,126 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _ctc_loss_out + operator_name: _ctc_loss + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_ctc_loss.Tensor_out(Tensor log_probs, Tensor targets, Tensor input_lengths, Tensor target_lengths, int blank=0, bool zero_infinity=False, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, int64_t, bool, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: log_probs + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: targets + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input_lengths + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: target_lengths + type: const at::Tensor & + - annotation: null + default: 0 + dynamic_type: int64_t + is_nullable: false + name: blank + type: int64_t + - annotation: null + default: false + dynamic_type: bool + is_nullable: false + name: zero_infinity + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _ctc_loss_backward_out operator_name: _ctc_loss_backward overload_name: out @@ -163008,7 +164227,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding.out(Tensor weight, Tensor indices, int padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding.out(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163103,7 +164322,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, int padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::embedding_dense_backward.out(Tensor grad_output, Tensor indices, SymInt num_weights, SymInt padding_idx, bool scale_grad_by_freq, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -163720,7 +164939,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, int num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_embedding_bag_dense_backward.out(Tensor grad, Tensor indices, Tensor offset2bag, Tensor bag_size, Tensor maximum_indices, SymInt num_weights, bool scale_grad_by_freq, int mode, Tensor? per_sample_weights, int padding_idx=-1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -168009,127 +169228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _mps_max_pool2d_out - operator_name: _mps_max_pool2d +- name: max_pool2d_backward_out + operator_name: max_pool2d_backward overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_mps_max_pool2d.out(Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, bool, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - name: ceil_mode - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mps_max_pool2d_backward_out - operator_name: mps_max_pool2d_backward - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mps_max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::max_pool2d_backward.out(Tensor grad_output, Tensor self, int[2] kernel_size, int[2] stride=[], int[2] padding=0, int[2] dilation=1, bool ceil_mode=False, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169214,107 +170318,825 @@ name: out2 output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - - annotation: null + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_convolution_out + operator_name: mkldnn_convolution + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: groups + type: int64_t + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_out + operator_name: mkldnn_rnn_layer + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer.out(Tensor input, Tensor weight0, Tensor weight1, Tensor weight2, Tensor weight3, Tensor hx_, Tensor cx_, bool reverse, int[] batch_sizes, int mode, int hidden_size, int num_layers, bool has_biases, bool bidirectional, bool batch_first, bool train, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, bool, at::IntArrayRef, int64_t, int64_t, int64_t, bool, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight0 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_ + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out3 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: mkldnn_rnn_layer_backward_out + operator_name: mkldnn_rnn_layer_backward + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::mkldnn_rnn_layer_backward.out(Tensor input, Tensor weight1, Tensor weight2, Tensor weight3, Tensor weight4, Tensor hx_, Tensor cx_tmp, Tensor output, Tensor hy_, Tensor cy_, Tensor? grad_output, Tensor? grad_hy, Tensor? grad_cy, bool reverse, int mode, int hidden_size, int num_layers, bool has_biases, bool train, bool bidirectional, int[] batch_sizes, bool batch_first, Tensor workspace, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5, Tensor(g!) out6) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!), Tensor(g!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! + dynamic_type: at::Tensor + is_nullable: false + name: out3 + output: true + type: at::Tensor & + - allocate: true + annotation: e! + dynamic_type: at::Tensor + is_nullable: false + name: out4 + output: true + type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & + - allocate: true + annotation: g! + dynamic_type: at::Tensor + is_nullable: false + name: out6 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const c10::optional &, const c10::optional &, const c10::optional &, bool, int64_t, int64_t, int64_t, bool, bool, bool, at::IntArrayRef, bool, const at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight1 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight2 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight3 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight4 + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hx_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cx_tmp + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: hy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: cy_ + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_output + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_hy + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: grad_cy + type: const c10::optional & + - annotation: null + dynamic_type: bool + is_nullable: false + name: reverse + type: bool + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: mode + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: hidden_size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: num_layers + type: int64_t + - annotation: null + dynamic_type: bool + is_nullable: false + name: has_biases + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: train + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + name: bidirectional + type: bool + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: batch_sizes + type: at::IntArrayRef + - annotation: null + dynamic_type: bool + is_nullable: false + name: batch_first + type: bool + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: workspace + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - allocate: true + annotation: d! dynamic_type: at::Tensor is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - annotation: null - dynamic_type: ::std::array - is_nullable: false - name: output_mask - type: ::std::array + name: out3 + output: true + type: at::Tensor & - allocate: true - annotation: a! + annotation: e! dynamic_type: at::Tensor is_nullable: false - name: out0 + name: out4 output: true type: at::Tensor & - allocate: true - annotation: b! + annotation: f! dynamic_type: at::Tensor is_nullable: false - name: out1 + name: out5 output: true type: at::Tensor & - allocate: true - annotation: c! + annotation: g! dynamic_type: at::Tensor is_nullable: false - name: out2 + name: out6 output: true type: at::Tensor & method_of: @@ -169332,114 +171154,17 @@ - dynamic_type: at::Tensor name: out2 type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: mkldnn_convolution_out - operator_name: mkldnn_convolution - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::mkldnn_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out3 type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - type: at::IntArrayRef - - annotation: null - dynamic_type: int64_t - is_nullable: false - name: groups - type: int64_t - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true + - dynamic_type: at::Tensor + name: out4 type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - dynamic_type: at::Tensor - name: out + name: out5 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out6 type: at::Tensor & inplace: false is_factory_method: false @@ -169759,7 +171484,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -169888,7 +171613,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_convolution_transpose.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, SymInt[] output_padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170027,7 +171752,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, int[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::miopen_depthwise_convolution.out(Tensor self, Tensor weight, Tensor? bias, SymInt[] padding, int[] stride, int[] dilation, int groups, bool benchmark, bool deterministic, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170745,12 +172470,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _sparse_mask_helper_out - operator_name: _sparse_mask_helper - overload_name: out +- name: mul_out + operator_name: mul + overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_mask_helper.out(Tensor t, Tensor mask_indices, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -170762,25 +172487,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) + name: other + type: const at::Scalar & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: t + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: const at::Scalar & is_nullable: false - name: mask_indices - type: const at::Tensor & + name: other + type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -170804,49 +172529,95 @@ with_gil: false deprecated: false has_math_kernel: false -- name: mul_out - operator_name: mul - overload_name: Scalar_out +- name: _native_batch_norm_legit_functional + operator_name: _native_batch_norm_legit_functional + overload_name: '' manual_kernel_registration: false category_override: '' - schema_string: aten::mul.Scalar_out(Tensor self, Scalar other, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_native_batch_norm_legit_functional(Tensor input, Tensor? weight, Tensor? bias, Tensor running_mean, Tensor running_var, bool training, float momentum, float eps) -> (Tensor, Tensor, Tensor, Tensor running_mean_out, Tensor running_var_out) arguments: - - allocate: true - annotation: a! + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: input + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: running_mean type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Scalar &, at::Tensor &) + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, bool, double, double) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: self + name: input type: const at::Tensor & - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::Tensor + is_nullable: true + name: weight + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::Tensor is_nullable: false - name: other - type: const at::Scalar & - - allocate: true - annotation: a! + name: running_mean + type: const at::Tensor & + - annotation: null dynamic_type: at::Tensor is_nullable: false - name: out - output: true - type: at::Tensor & + name: running_var + type: const at::Tensor & + - annotation: null + dynamic_type: bool + is_nullable: false + name: training + type: bool + - annotation: null + dynamic_type: double + is_nullable: false + name: momentum + type: double + - annotation: null + dynamic_type: double + is_nullable: false + name: eps + type: double method_of: - Type - namespace @@ -170854,8 +172625,22 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out - type: at::Tensor & + name: result0 + type: at::Tensor + - dynamic_type: at::Tensor + name: result1 + type: at::Tensor + - dynamic_type: at::Tensor + name: result2 + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_mean_out + name: running_mean_out + type: at::Tensor + - dynamic_type: at::Tensor + field_name: running_var_out + name: running_var_out + type: at::Tensor inplace: false is_factory_method: false abstract: true @@ -171774,7 +173559,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, int[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nnpack_spatial_convolution.out(Tensor input, Tensor weight, Tensor? bias, SymInt[2] padding, int[2] stride=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172647,7 +174432,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -172708,7 +174493,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::rand.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::rand.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173000,7 +174785,7 @@ overload_name: names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.names_out(int[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.names_out(SymInt[] size, *, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173061,7 +174846,7 @@ overload_name: generator_with_names_out manual_kernel_registration: false category_override: '' - schema_string: aten::randn.generator_with_names_out(int[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::randn.generator_with_names_out(SymInt[] size, *, Generator? generator, Dimname[]? names, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173373,179 +175158,37 @@ with_gil: false deprecated: false has_math_kernel: false -- name: relu_out - operator_name: relu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_out - operator_name: prelu - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::prelu.out(Tensor self, Tensor weight, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false -- name: prelu_backward_out - operator_name: prelu_backward +- name: relu_out + operator_name: relu overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::prelu_backward.out(Tensor grad_output, Tensor self, Tensor weight, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::relu.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 + name: out output: true type: at::Tensor & method_of: @@ -173555,10 +175198,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -173572,7 +175212,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_backward.out(Tensor grad_output, SymInt[] input_sizes, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -173918,7 +175558,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, int index, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_scatter.out(Tensor self, Tensor src, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -174183,7 +175823,7 @@ overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split.Tensor_out(Tensor self, int split_size, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split.Tensor_out(Tensor self, SymInt split_size, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174251,7 +175891,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unsafe_split_with_sizes.out(Tensor self, int[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () + schema_string: aten::unsafe_split_with_sizes.out(Tensor self, SymInt[] split_sizes, int dim=0, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -174382,7 +176022,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::std_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -174404,12 +176044,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -174430,12 +176072,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176060,7 +177704,7 @@ overload_name: correction_out manual_kernel_registration: false category_override: '' - schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim, *, int? correction, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) + schema_string: aten::var_mean.correction_out(Tensor self, int[1]? dim=None, *, int? correction=None, bool keepdim=False, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) arguments: - allocate: true annotation: a! @@ -176082,12 +177726,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -176108,12 +177754,14 @@ name: self type: const at::Tensor & - annotation: null + default: c10::nullopt dynamic_type: at::IntArrayRef is_nullable: true name: dim size: 1 type: at::OptionalIntArrayRef - annotation: null + default: c10::nullopt dynamic_type: int64_t is_nullable: true kwarg_only: true @@ -178691,7 +180339,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, int[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_coo_tensor_with_dims_and_tensors.out(int sparse_dim, int dense_dim, SymInt[] size, Tensor indices, Tensor values, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179528,7 +181176,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse.out(Tensor self, *, Layout? layout=None, int[2]? blocksize=None, int? dense_dim=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179542,13 +181190,57 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::OptionalIntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + kwarg_only: true + name: layout + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + kwarg_only: true + name: blocksize + size: 2 + type: at::OptionalIntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + kwarg_only: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179577,7 +181269,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csr.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csr.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179591,13 +181283,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179626,7 +181330,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_csc.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_csc.out(Tensor self, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179640,13 +181344,25 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179675,7 +181391,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsr.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179695,7 +181411,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179708,6 +181430,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179736,7 +181464,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_sparse_bsc.out(Tensor self, int[2] blocksize, int? dense_dim=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179756,7 +181484,13 @@ name: blocksize size: 2 type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179769,6 +181503,12 @@ name: blocksize size: 2 type: at::IntArrayRef + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: dense_dim + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -179858,7 +181598,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::mkldnn_reorder_conv2d_weight.out(Tensor self, int[2] padding=0, int[2] stride=1, int[2] dilation=1, int groups=1, int[]? input_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -179899,7 +181639,13 @@ is_nullable: false name: groups type: int64_t - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::Tensor &) + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, int64_t, at::OptionalIntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -179933,6 +181679,12 @@ is_nullable: false name: groups type: int64_t + - annotation: null + default: c10::nullopt + dynamic_type: at::IntArrayRef + is_nullable: true + name: input_size + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -181843,7 +183595,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!)) + schema_string: aten::_lstm_mps.out(Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2, Tensor(d!) out3, Tensor(e!) out4, Tensor(f!) out5) -> (Tensor(a!), Tensor(b!), Tensor(c!), Tensor(d!), Tensor(e!), Tensor(f!)) arguments: - allocate: true annotation: a! @@ -181880,6 +183632,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false @@ -181925,7 +183684,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182007,6 +183766,13 @@ name: out4 output: true type: at::Tensor & + - allocate: true + annotation: f! + dynamic_type: at::Tensor + is_nullable: false + name: out5 + output: true + type: at::Tensor & method_of: - Type - namespace @@ -182028,6 +183794,9 @@ - dynamic_type: at::Tensor name: out4 type: at::Tensor & + - dynamic_type: at::Tensor + name: out5 + type: at::Tensor & inplace: false is_factory_method: false abstract: true @@ -182040,7 +183809,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () + schema_string: aten::lstm_mps_backward.out(Tensor grad_y, Tensor? grad_hy, Tensor? grad_cy, Tensor z_state, Tensor cell_state_fwd, Tensor input, Tensor layersOutputs, Tensor[] hx, Tensor[] params, bool has_biases, int num_layers, float dropout, bool train, bool bidirectional, bool batch_first, *, Tensor(a!) out0, Tensor(b!)[] out1, Tensor(c!)[] out2) -> () arguments: - allocate: true annotation: a! @@ -182093,6 +183862,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -182133,7 +183907,7 @@ is_nullable: false name: batch_first type: bool - schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) + schema_order_cpp_signature: void (const at::Tensor &, const c10::optional &, const c10::optional &, const at::Tensor &, const at::Tensor &, const at::Tensor &, const at::Tensor &, at::TensorList, at::TensorList, bool, int64_t, double, bool, bool, bool, at::Tensor &, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -182165,6 +183939,11 @@ is_nullable: false name: input type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: layersOutputs + type: const at::Tensor & - annotation: null dynamic_type: at::TensorList is_nullable: false @@ -185866,92 +187645,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _symeig_helper_out - operator_name: _symeig_helper - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_symeig_helper.out(Tensor self, bool eigenvectors, bool upper, *, Tensor(a!) out0, Tensor(b!) out1) -> (Tensor(a!), Tensor(b!)) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, bool, bool, at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: bool - is_nullable: false - name: eigenvectors - type: bool - - annotation: null - dynamic_type: bool - is_nullable: false - name: upper - type: bool - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _cholesky_solve_helper_out operator_name: _cholesky_solve_helper overload_name: out @@ -186531,7 +188224,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::unfold_backward.out(Tensor grad_in, int[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_backward.out(Tensor grad_in, SymInt[] input_sizes, int dim, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -187072,12 +188765,544 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub - overload_name: Scalar_out +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_min.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_clamp_max.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_maximum_out + operator_name: _foreach_maximum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_maximum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_minimum_out + operator_name: _foreach_minimum + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_minimum.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: const at::Scalar & + is_nullable: false + name: scalar + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: List_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: other + type: at::TensorList + - annotation: null + default: 1 + dynamic_type: const at::Scalar & + is_nullable: false + kwarg_only: true + name: alpha + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187092,11 +189317,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187104,10 +189329,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187128,12 +189353,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul - overload_name: Scalar_out +- name: _foreach_div_out + operator_name: _foreach_div + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187148,11 +189373,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187160,10 +189385,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187184,12 +189409,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div - overload_name: Scalar_out +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min + overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.Scalar_out(Tensor[] self, Scalar scalar, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187204,11 +189429,11 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + name: other + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187216,10 +189441,10 @@ name: self type: at::TensorList - annotation: null - dynamic_type: const at::Scalar & + dynamic_type: at::TensorList is_nullable: false - name: scalar - type: const at::Scalar & + name: other + type: at::TensorList - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187240,12 +189465,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187264,14 +189489,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187283,13 +189501,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187310,12 +189521,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.List_out(Tensor[] self, Tensor[] other, *, Scalar alpha=1, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187334,14 +189545,7 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -187353,13 +189557,6 @@ is_nullable: false name: other type: at::TensorList - - annotation: null - default: 1 - dynamic_type: const at::Scalar & - is_nullable: false - kwarg_only: true - name: alpha - type: const at::Scalar & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187380,12 +189577,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187436,12 +189633,124 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_add_out + operator_name: _foreach_add + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_sub_out + operator_name: _foreach_sub + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_div_out operator_name: _foreach_div - overload_name: List_out + overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187455,23 +189764,79 @@ is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_mul_out + operator_name: _foreach_mul + overload_name: ScalarList_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) - schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef + schema_order_cpp_signature: void (at::TensorList, at::ArrayRef, at::TensorList) + schema_order_arguments: - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: self type: at::TensorList + - annotation: null + dynamic_type: at::ArrayRef + is_nullable: false + name: scalars + type: at::ArrayRef - allocate: true annotation: a! dynamic_type: at::TensorList @@ -187492,12 +189857,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_add_out - operator_name: _foreach_add +- name: _foreach_clamp_min_out + operator_name: _foreach_clamp_min overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_add.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_min.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187548,12 +189913,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_sub_out - operator_name: _foreach_sub +- name: _foreach_clamp_max_out + operator_name: _foreach_clamp_max overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_sub.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_clamp_max.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187604,12 +189969,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_div_out - operator_name: _foreach_div +- name: _foreach_maximum_out + operator_name: _foreach_maximum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_div.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_maximum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -187660,12 +190025,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_mul_out - operator_name: _foreach_mul +- name: _foreach_minimum_out + operator_name: _foreach_minimum overload_name: ScalarList_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_mul.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_minimum.ScalarList_out(Tensor[] self, Scalar[] scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189318,6 +191683,82 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _foreach_addcdiv_out + operator_name: _foreach_addcdiv + overload_name: Tensor_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_addcdiv.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false - name: _foreach_addcmul_out operator_name: _foreach_addcmul overload_name: ScalarList_out @@ -189394,12 +191835,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_maximum_out - operator_name: _foreach_maximum - overload_name: List_out +- name: _foreach_addcmul_out + operator_name: _foreach_addcmul + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_maximum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_addcmul.Tensor_out(Tensor[] self, Tensor[] tensor1, Tensor[] tensor2, Tensor scalars, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189416,9 +191857,19 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 + type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, const at::Tensor &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189428,8 +191879,18 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensor1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: tensor2 type: at::TensorList + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: scalars + type: const at::Tensor & - allocate: true annotation: a! dynamic_type: at::TensorList @@ -189450,12 +191911,70 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_minimum_out - operator_name: _foreach_minimum +- name: _foreach_norm_out + operator_name: _foreach_norm + overload_name: Scalar_out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + default: 2 + dynamic_type: const at::Scalar & + is_nullable: false + name: ord + type: const at::Scalar & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: List_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_minimum.List_out(Tensor[] self, Tensor[] other, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.List_out(Tensor[] self, Tensor[] tensors1, Tensor[] weights, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189472,9 +191991,14 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 type: at::TensorList - schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList) + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights + type: at::TensorList + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189484,7 +192008,12 @@ - annotation: null dynamic_type: at::TensorList is_nullable: false - name: other + name: tensors1 + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: weights type: at::TensorList - allocate: true annotation: a! @@ -189506,12 +192035,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _foreach_norm_out - operator_name: _foreach_norm +- name: _foreach_lerp_out + operator_name: _foreach_lerp overload_name: Scalar_out manual_kernel_registration: false category_override: '' - schema_string: aten::_foreach_norm.Scalar_out(Tensor[] self, Scalar ord=2, *, Tensor(a!)[] out) -> () + schema_string: aten::_foreach_lerp.Scalar_out(Tensor[] self, Tensor[] tensors1, Scalar weight, *, Tensor(a!)[] out) -> () arguments: - allocate: true annotation: a! @@ -189526,12 +192055,16 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - schema_order_cpp_signature: void (at::TensorList, const at::Scalar &, at::TensorList) + schema_order_cpp_signature: void (at::TensorList, at::TensorList, const at::Scalar &, at::TensorList) schema_order_arguments: - annotation: null dynamic_type: at::TensorList @@ -189539,10 +192072,14 @@ name: self type: at::TensorList - annotation: null - default: 2 + dynamic_type: at::TensorList + is_nullable: false + name: tensors1 + type: at::TensorList + - annotation: null dynamic_type: const at::Scalar & is_nullable: false - name: ord + name: weight type: const at::Scalar & - allocate: true annotation: a! @@ -189651,55 +192188,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _torch_cuda_cu_linker_symbol_op_out - operator_name: _torch_cuda_cu_linker_symbol_op - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_torch_cuda_cu_linker_symbol_op.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: searchsorted_out operator_name: searchsorted overload_name: Scalar_out @@ -190345,7 +192833,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, int[3] output_size, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_adaptive_avg_pool3d.out(Tensor self, SymInt[3] output_size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190460,12 +192948,161 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_out - operator_name: upsample_linear1d - overload_name: vec_out +- name: _slow_conv2d_backward_out + operator_name: _slow_conv2d_backward + overload_name: output_mask_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: grad_output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + dynamic_type: ::std::array + is_nullable: false + name: output_mask + type: ::std::array + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out0 + output: true + type: at::Tensor & + - allocate: true + annotation: b! + dynamic_type: at::Tensor + is_nullable: false + name: out1 + output: true + type: at::Tensor & + - allocate: true + annotation: c! + dynamic_type: at::Tensor + is_nullable: false + name: out2 + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out0 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out1 + type: at::Tensor & + - dynamic_type: at::Tensor + name: out2 + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: conv_depthwise3d_out + operator_name: conv_depthwise3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, SymInt[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190477,45 +193114,551 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: bias + type: const c10::optional & - annotation: null - dynamic_type: bool + dynamic_type: at::IntArrayRef is_nullable: false - name: align_corners - type: bool + name: stride + size: 3 + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::Tensor is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: bias + type: const c10::optional & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated2d_out + operator_name: slow_conv_dilated2d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, SymInt[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 2 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 2 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 2 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 2 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: slow_conv_dilated3d_out + operator_name: slow_conv_dilated3d + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, SymInt[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: weight + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: false + name: kernel_size + size: 3 + type: at::IntArrayRef + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + name: bias + type: const c10::optional & + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: stride + size: 3 + type: at::IntArrayRef + - annotation: null + default: 0 + dynamic_type: at::IntArrayRef + is_nullable: false + name: padding + size: 3 + type: at::IntArrayRef + - annotation: null + default: 1 + dynamic_type: at::IntArrayRef + is_nullable: false + name: dilation + size: 3 + type: at::IntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: isinf_out + operator_name: isinf + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: linalg_matrix_exp_out + operator_name: linalg_matrix_exp + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: self + type: const at::Tensor & + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_intlist_out + operator_name: _test_optional_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values + type: const at::Tensor & + - annotation: null + dynamic_type: at::IntArrayRef + is_nullable: true + name: addends + type: at::OptionalIntArrayRef + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::Tensor + name: out + type: at::Tensor & + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _test_optional_filled_intlist_out + operator_name: _test_optional_filled_intlist + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + arguments: + - allocate: true + annotation: a! + dynamic_type: at::Tensor + is_nullable: false + name: out + output: true + type: at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: values type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: true - name: output_size + name: addends + size: 2 type: at::OptionalIntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_arguments: - annotation: null - dynamic_type: bool + dynamic_type: at::Tensor is_nullable: false - name: align_corners - type: bool + name: values + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef + dynamic_type: at::IntArrayRef is_nullable: true - name: scale_factors - type: c10::optional> + name: addends + size: 2 + type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190539,12 +193682,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_linear1d_backward_out - operator_name: upsample_linear1d_backward - overload_name: vec_out +- name: _test_optional_floatlist_out + operator_name: _test_optional_floatlist + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_linear1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190556,54 +193699,24 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: values type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - annotation: null dynamic_type: at::ArrayRef is_nullable: true - name: scale_factors + name: addends type: c10::optional> - allocate: true annotation: a! @@ -190628,12 +193741,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_out - operator_name: upsample_bilinear2d - overload_name: vec_out +- name: _test_warn_in_autograd_out + operator_name: _test_warn_in_autograd + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190645,45 +193758,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190707,12 +193790,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bilinear2d_backward_out - operator_name: upsample_bilinear2d_backward - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_out + operator_name: _test_autograd_multiple_dispatch + overload_name: fullcoverage_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bilinear2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190724,55 +193807,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190796,12 +193839,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_out - operator_name: _upsample_bilinear2d_aa - overload_name: vec_out +- name: _test_autograd_multiple_dispatch_view_copy_out + operator_name: _test_autograd_multiple_dispatch_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190813,45 +193856,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190875,12 +193888,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bilinear2d_aa_backward_out - operator_name: _upsample_bilinear2d_aa_backward - overload_name: vec_out +- name: segment_reduce_out + operator_name: segment_reduce + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bilinear2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190892,55 +193905,109 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: data type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: at::IntArrayRef + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: indices + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + kwarg_only: true + name: axis + type: int64_t - annotation: null + default: false dynamic_type: bool is_nullable: false - name: align_corners + kwarg_only: true + name: unsafe type: bool - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -190964,12 +194031,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_out - operator_name: upsample_trilinear3d - overload_name: vec_out +- name: _segment_reduce_backward_out + operator_name: _segment_reduce_backward + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -190981,45 +194048,101 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + kwarg_only: true + name: initial + type: const c10::optional & + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: grad type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor + is_nullable: false + name: output + type: const at::Tensor & + - annotation: null + dynamic_type: at::Tensor + is_nullable: false + name: data + type: const at::Tensor & + - annotation: null + dynamic_type: c10::string_view + is_nullable: false + name: reduce + type: c10::string_view + - annotation: null + default: '{}' + dynamic_type: at::Tensor is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + kwarg_only: true + name: lengths + type: const c10::optional & - annotation: null - dynamic_type: bool + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: offsets + type: const c10::optional & + - annotation: null + default: 0 + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool + kwarg_only: true + name: axis + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: const at::Scalar & is_nullable: true - name: scale_factors - type: c10::optional> + kwarg_only: true + name: initial + type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191043,12 +194166,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_trilinear3d_backward_out - operator_name: upsample_trilinear3d_backward - overload_name: vec_out +- name: _nested_tensor_from_tensor_list_out + operator_name: _nested_tensor_from_tensor_list + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_trilinear3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191058,57 +194181,65 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: pin_memory + type: c10::optional + schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::Tensor + dynamic_type: at::TensorList is_nullable: false - name: grad_output - type: const at::Tensor & + name: list + type: at::TensorList - annotation: null - dynamic_type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::ScalarType is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: dtype + type: c10::optional - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef + default: c10::nullopt + dynamic_type: at::Layout + is_nullable: true + name: layout + type: c10::optional - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool + default: c10::nullopt + dynamic_type: at::Device + is_nullable: true + name: device + type: c10::optional - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: bool is_nullable: true - name: scale_factors - type: c10::optional> + name: pin_memory + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191132,12 +194263,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_out - operator_name: upsample_bicubic2d - overload_name: vec_out +- name: _fw_primal_copy_out + operator_name: _fw_primal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_fw_primal_copy.out(Tensor self, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191149,45 +194280,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191211,12 +194322,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_bicubic2d_backward_out - operator_name: upsample_bicubic2d_backward - overload_name: vec_out +- name: _make_dual_copy_out + operator_name: _make_dual_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_bicubic2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_make_dual_copy.out(Tensor primal, Tensor tangent, int level, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191228,55 +194339,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + name: level + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: primal type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + dynamic_type: at::Tensor is_nullable: false - name: input_size - type: at::IntArrayRef + name: tangent + type: const at::Tensor & - annotation: null - dynamic_type: bool + dynamic_type: int64_t is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + name: level + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191300,12 +194391,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_out - operator_name: _upsample_bicubic2d_aa - overload_name: vec_out +- name: view_as_real_copy_out + operator_name: view_as_real_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa.vec_out(Tensor input, SymInt[]? output_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_real_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191317,45 +194408,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191379,12 +194440,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_bicubic2d_aa_backward_out - operator_name: _upsample_bicubic2d_aa_backward - overload_name: vec_out +- name: view_as_complex_copy_out + operator_name: view_as_complex_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_bicubic2d_aa_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, bool align_corners, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_as_complex_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191396,55 +194457,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, bool, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: bool - is_nullable: false - name: align_corners - type: bool - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191468,12 +194489,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_out - operator_name: upsample_nearest1d - overload_name: vec_out +- name: _conj_copy_out + operator_name: _conj_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_conj_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191485,35 +194506,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191537,12 +194538,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_out - operator_name: _upsample_nearest_exact1d - overload_name: vec_out +- name: _neg_view_copy_out + operator_name: _neg_view_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_neg_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191554,35 +194555,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191606,12 +194587,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest1d_backward_out - operator_name: upsample_nearest1d_backward - overload_name: vec_out +- name: as_strided_copy_out + operator_name: as_strided_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::as_strided_copy.out(Tensor self, SymInt[] size, SymInt[] stride, SymInt? storage_offset=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191623,45 +194604,47 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: storage_offset + type: c10::optional + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, c10::optional, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: storage_offset + type: c10::optional - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191685,12 +194668,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact1d_backward_out - operator_name: _upsample_nearest_exact1d_backward - overload_name: vec_out +- name: _sparse_broadcast_to_copy_out + operator_name: _sparse_broadcast_to_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact1d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_sparse_broadcast_to_copy.out(Tensor self, int[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191702,45 +194685,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: size type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191764,12 +194727,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_out - operator_name: upsample_nearest2d - overload_name: vec_out +- name: diagonal_copy_out + operator_name: diagonal_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::diagonal_copy.out(Tensor self, int offset=0, int dim1=0, int dim2=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191781,35 +194744,51 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + default: 0 + dynamic_type: int64_t + is_nullable: false + name: offset + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: 0 + dynamic_type: int64_t + is_nullable: false + name: dim1 + type: int64_t + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: dim2 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191833,12 +194812,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_out - operator_name: _upsample_nearest_exact2d - overload_name: vec_out +- name: expand_copy_out + operator_name: expand_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::expand_copy.out(Tensor self, SymInt[] size, *, bool implicit=False, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191850,35 +194829,39 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, bool, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + default: false + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: implicit + type: bool - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191902,12 +194885,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest2d_backward_out - operator_name: upsample_nearest2d_backward - overload_name: vec_out +- name: permute_copy_out + operator_name: permute_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::permute_copy.out(Tensor self, int[] dims, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191919,45 +194902,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: dims type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -191981,12 +194944,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact2d_backward_out - operator_name: _upsample_nearest_exact2d_backward - overload_name: vec_out +- name: _reshape_alias_copy_out + operator_name: _reshape_alias_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact2d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_reshape_alias_copy.out(Tensor self, SymInt[] size, SymInt[] stride, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -191998,45 +194961,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + is_nullable: false + name: size + type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: input_size + name: stride type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192060,12 +195013,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_out - operator_name: upsample_nearest3d - overload_name: vec_out +- name: select_copy_out + operator_name: select_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::select_copy.int_out(Tensor self, int dim, SymInt index, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192077,35 +195030,35 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef + name: self + type: const at::Tensor & - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: index + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192129,12 +195082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_out - operator_name: _upsample_nearest_exact3d - overload_name: vec_out +- name: detach_copy_out + operator_name: detach_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d.vec_out(Tensor input, SymInt[]? output_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::detach_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192146,35 +195099,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: input + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192198,12 +195131,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: upsample_nearest3d_backward_out - operator_name: upsample_nearest3d_backward - overload_name: vec_out +- name: slice_copy_out + operator_name: slice_copy + overload_name: Tensor_out manual_kernel_registration: false category_override: '' - schema_string: aten::upsample_nearest3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::slice_copy.Tensor_out(Tensor self, int dim=0, SymInt? start=None, SymInt? end=None, SymInt step=1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192215,45 +195148,63 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, c10::optional, c10::optional, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef + default: 0 + dynamic_type: int64_t is_nullable: false - name: input_size - type: at::IntArrayRef + name: dim + type: int64_t - annotation: null - dynamic_type: at::ArrayRef + default: c10::nullopt + dynamic_type: int64_t is_nullable: true - name: scale_factors - type: c10::optional> + name: start + type: c10::optional + - annotation: null + default: c10::nullopt + dynamic_type: int64_t + is_nullable: true + name: end + type: c10::optional + - annotation: null + default: 1 + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192277,12 +195228,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _upsample_nearest_exact3d_backward_out - operator_name: _upsample_nearest_exact3d_backward - overload_name: vec_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_upsample_nearest_exact3d_backward.vec_out(Tensor grad_output, SymInt[]? output_size, SymInt[] input_size, float[]? scale_factors, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192294,45 +195245,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::IntArrayRef, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad_output + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: output_size - type: at::OptionalIntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: input_size - type: at::IntArrayRef - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: scale_factors - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192356,131 +195277,47 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _slow_conv2d_backward_out - operator_name: _slow_conv2d_backward - overload_name: output_mask_out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dim_out manual_kernel_registration: false category_override: '' - schema_string: aten::_slow_conv2d_backward.output_mask_out(Tensor grad_output, Tensor self, Tensor weight, int[2] kernel_size, int[2] stride, int[2] padding, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) + schema_string: aten::squeeze_copy.dim_out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array - schema_order_cpp_signature: ::std::tuple (const at::Tensor &, const at::Tensor &, const at::Tensor &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, ::std::array, at::Tensor &, at::Tensor &, at::Tensor &) + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: grad_output - type: const at::Tensor & - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - dynamic_type: ::std::array + dynamic_type: int64_t is_nullable: false - name: output_mask - type: ::std::array + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor is_nullable: false - name: out0 - output: true - type: at::Tensor & - - allocate: true - annotation: b! - dynamic_type: at::Tensor - is_nullable: false - name: out1 - output: true - type: at::Tensor & - - allocate: true - annotation: c! - dynamic_type: at::Tensor - is_nullable: false - name: out2 + name: out output: true type: at::Tensor & method_of: @@ -192490,13 +195327,7 @@ python_module: '' returns: - dynamic_type: at::Tensor - name: out0 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out1 - type: at::Tensor & - - dynamic_type: at::Tensor - name: out2 + name: out type: at::Tensor & inplace: false is_factory_method: false @@ -192505,12 +195336,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: conv_depthwise3d_out - operator_name: conv_depthwise3d - overload_name: out +- name: squeeze_copy_out + operator_name: squeeze_copy + overload_name: dims_out manual_kernel_registration: false category_override: '' - schema_string: aten::conv_depthwise3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias, int[3] stride, int[3] padding, int[3] dilation, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::squeeze_copy.dims_out(Tensor self, int[] dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192524,80 +195355,22 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef - annotation: null dynamic_type: at::IntArrayRef is_nullable: false - name: dilation - size: 3 + name: dim type: at::IntArrayRef - allocate: true annotation: a! @@ -192622,12 +195395,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated2d_out - operator_name: slow_conv_dilated2d +- name: t_copy_out + operator_name: t_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated2d.out(Tensor self, Tensor weight, int[2] kernel_size, Tensor? bias=None, int[2] stride=1, int[2] padding=0, int[2] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::t_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192641,89 +195414,13 @@ is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 2 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 2 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef - is_nullable: false - name: padding - size: 2 - type: at::IntArrayRef - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: dilation - size: 2 - type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192747,12 +195444,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: slow_conv_dilated3d_out - operator_name: slow_conv_dilated3d - overload_name: out +- name: transpose_copy_out + operator_name: transpose_copy + overload_name: int_out manual_kernel_registration: false category_override: '' - schema_string: aten::slow_conv_dilated3d.out(Tensor self, Tensor weight, int[3] kernel_size, Tensor? bias=None, int[3] stride=1, int[3] padding=0, int[3] dilation=1, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::transpose_copy.int_out(Tensor self, int dim0, int dim1, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192767,44 +195464,16 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, at::IntArrayRef, const c10::optional &, at::IntArrayRef, at::IntArrayRef, at::IntArrayRef, at::Tensor &) + name: dim1 + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor @@ -192812,43 +195481,15 @@ name: self type: const at::Tensor & - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: weight - type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: false - name: kernel_size - size: 3 - type: at::IntArrayRef - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - default: 1 - dynamic_type: at::IntArrayRef - is_nullable: false - name: stride - size: 3 - type: at::IntArrayRef - - annotation: null - default: 0 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: padding - size: 3 - type: at::IntArrayRef + name: dim0 + type: int64_t - annotation: null - default: 1 - dynamic_type: at::IntArrayRef + dynamic_type: int64_t is_nullable: false - name: dilation - size: 3 - type: at::IntArrayRef + name: dim1 + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192872,12 +195513,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: isinf_out - operator_name: isinf +- name: unsqueeze_copy_out + operator_name: unsqueeze_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::isinf.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unsqueeze_copy.out(Tensor self, int dim, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192891,13 +195532,23 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dim + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -192921,12 +195572,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: linalg_matrix_exp_out - operator_name: linalg_matrix_exp +- name: _indices_copy_out + operator_name: _indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::linalg_matrix_exp.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192970,12 +195621,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_intlist_out - operator_name: _test_optional_intlist +- name: _values_copy_out + operator_name: _values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_intlist.out(Tensor values, int[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::_values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -192987,25 +195638,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193029,12 +195670,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_filled_intlist_out - operator_name: _test_optional_filled_intlist +- name: indices_copy_out + operator_name: indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_filled_intlist.out(Tensor values, int[2]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193046,27 +195687,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::OptionalIntArrayRef, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::IntArrayRef - is_nullable: true - name: addends - size: 2 - type: at::OptionalIntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193090,12 +195719,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_optional_floatlist_out - operator_name: _test_optional_floatlist +- name: values_copy_out + operator_name: values_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_optional_floatlist.out(Tensor values, float[]? addends, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::values_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193107,25 +195736,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::optional>, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: values + name: self type: const at::Tensor & - - annotation: null - dynamic_type: at::ArrayRef - is_nullable: true - name: addends - type: c10::optional> - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193149,12 +195768,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_warn_in_autograd_out - operator_name: _test_warn_in_autograd +- name: crow_indices_copy_out + operator_name: crow_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_warn_in_autograd.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::crow_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193198,12 +195817,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_out - operator_name: _test_autograd_multiple_dispatch - overload_name: fullcoverage_out +- name: col_indices_copy_out + operator_name: col_indices_copy + overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch.fullcoverage_out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::col_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193247,12 +195866,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _test_autograd_multiple_dispatch_view_copy_out - operator_name: _test_autograd_multiple_dispatch_view_copy +- name: ccol_indices_copy_out + operator_name: ccol_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_test_autograd_multiple_dispatch_view_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193296,12 +195915,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: segment_reduce_out - operator_name: segment_reduce +- name: row_indices_copy_out + operator_name: row_indices_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::segment_reduce.out(Tensor data, str reduce, *, Tensor? lengths=None, Tensor? indices=None, Tensor? offsets=None, int axis=0, bool unsafe=False, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193313,109 +195932,15 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, const c10::optional &, int64_t, bool, const c10::optional &, at::Tensor &) + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: data + name: self type: const at::Tensor & - - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: indices - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t - is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: false - dynamic_type: bool - is_nullable: false - kwarg_only: true - name: unsafe - type: bool - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193439,12 +195964,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _segment_reduce_backward_out - operator_name: _segment_reduce_backward +- name: view_copy_out + operator_name: view_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::_segment_reduce_backward.out(Tensor grad, Tensor output, Tensor data, str reduce, *, Tensor? lengths=None, Tensor? offsets=None, int axis=0, Scalar? initial=None, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.out(Tensor self, SymInt[] size, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193456,101 +195981,25 @@ - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const at::Tensor &, const at::Tensor &, c10::string_view, const c10::optional &, const c10::optional &, int64_t, const c10::optional &, at::Tensor &) + name: size + type: at::IntArrayRef + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::IntArrayRef, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false - name: grad - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: output - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: data + name: self type: const at::Tensor & - annotation: null - dynamic_type: c10::string_view - is_nullable: false - name: reduce - type: c10::string_view - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: lengths - type: const c10::optional & - - annotation: null - default: '{}' - dynamic_type: at::Tensor - is_nullable: true - kwarg_only: true - name: offsets - type: const c10::optional & - - annotation: null - default: 0 - dynamic_type: int64_t + dynamic_type: at::IntArrayRef is_nullable: false - kwarg_only: true - name: axis - type: int64_t - - annotation: null - default: c10::nullopt - dynamic_type: const at::Scalar & - is_nullable: true - kwarg_only: true - name: initial - type: const c10::optional & + name: size + type: at::IntArrayRef - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193574,12 +196023,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_from_tensor_list_out - operator_name: _nested_tensor_from_tensor_list - overload_name: out +- name: view_copy_out + operator_name: view_copy + overload_name: dtype_out manual_kernel_registration: false category_override: '' - schema_string: aten::_nested_tensor_from_tensor_list.out(Tensor[] list, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::view_copy.dtype_out(Tensor self, ScalarType dtype, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193589,65 +196038,27 @@ output: true type: at::Tensor & - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional - schema_order_cpp_signature: at::Tensor & (at::TensorList, c10::optional, c10::optional, c10::optional, c10::optional, at::Tensor &) + type: at::ScalarType + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::ScalarType, at::Tensor &) schema_order_arguments: - annotation: null - dynamic_type: at::TensorList + dynamic_type: at::Tensor is_nullable: false - name: list - type: at::TensorList + name: self + type: const at::Tensor & - annotation: null - default: c10::nullopt dynamic_type: at::ScalarType - is_nullable: true + is_nullable: false name: dtype - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Layout - is_nullable: true - name: layout - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: at::Device - is_nullable: true - name: device - type: c10::optional - - annotation: null - default: c10::nullopt - dynamic_type: bool - is_nullable: true - name: pin_memory - type: c10::optional + type: at::ScalarType - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193671,12 +196082,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: ccol_indices_copy_out - operator_name: ccol_indices_copy +- name: unfold_copy_out + operator_name: unfold_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::ccol_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::unfold_copy.out(Tensor self, int dimension, int size, int step, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193690,13 +196101,43 @@ is_nullable: false name: self type: const at::Tensor & - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, at::Tensor &) + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t + schema_order_cpp_signature: at::Tensor & (const at::Tensor &, int64_t, int64_t, int64_t, at::Tensor &) schema_order_arguments: - annotation: null dynamic_type: at::Tensor is_nullable: false name: self type: const at::Tensor & + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: dimension + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: size + type: int64_t + - annotation: null + dynamic_type: int64_t + is_nullable: false + name: step + type: int64_t - allocate: true annotation: a! dynamic_type: at::Tensor @@ -193720,12 +196161,12 @@ with_gil: false deprecated: false has_math_kernel: false -- name: row_indices_copy_out - operator_name: row_indices_copy +- name: alias_copy_out + operator_name: alias_copy overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::row_indices_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::alias_copy.out(Tensor self, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193774,7 +196215,7 @@ overload_name: out manual_kernel_registration: false category_override: '' - schema_string: aten::to_padded_tensor.out(Tensor self, float padding, int[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) + schema_string: aten::to_padded_tensor.out(Tensor self, float padding, SymInt[]? output_size=None, *, Tensor(a!) out) -> Tensor(a!) arguments: - allocate: true annotation: a! @@ -193840,85 +196281,6 @@ with_gil: false deprecated: false has_math_kernel: false -- name: _nested_tensor_layer_norm_out - operator_name: _nested_tensor_layer_norm - overload_name: out - manual_kernel_registration: false - category_override: '' - schema_string: aten::_nested_tensor_layer_norm.out(Tensor self, Tensor? weight, Tensor? bias, float eps, *, Tensor(a!) out) -> Tensor(a!) - arguments: - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - schema_order_cpp_signature: at::Tensor & (const at::Tensor &, const c10::optional &, const c10::optional &, double, at::Tensor &) - schema_order_arguments: - - annotation: null - dynamic_type: at::Tensor - is_nullable: false - name: self - type: const at::Tensor & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: weight - type: const c10::optional & - - annotation: null - dynamic_type: at::Tensor - is_nullable: true - name: bias - type: const c10::optional & - - annotation: null - dynamic_type: double - is_nullable: false - name: eps - type: double - - allocate: true - annotation: a! - dynamic_type: at::Tensor - is_nullable: false - name: out - output: true - type: at::Tensor & - method_of: - - Type - - namespace - mode: native - python_module: '' - returns: - - dynamic_type: at::Tensor - name: out - type: at::Tensor & - inplace: false - is_factory_method: false - abstract: true - device_guard: false - with_gil: false - deprecated: false - has_math_kernel: false - name: _transformer_encoder_layer_fwd_out operator_name: _transformer_encoder_layer_fwd overload_name: out @@ -195616,3 +197978,425 @@ with_gil: false deprecated: false has_math_kernel: false +- name: _fused_adamw_out + operator_name: _fused_adamw + overload_name: out + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw.out(Tensor[] self, Tensor(b!)[] grads, Tensor(c!)[] exp_avgs, Tensor(d!)[] exp_avg_sqs, Tensor(e!)[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None, Tensor(a!)[] out) -> () + arguments: + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: void (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &, at::TensorList) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: b! + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: c! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: d! + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: e! + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + - allocate: true + annotation: a! + dynamic_type: at::TensorList + is_nullable: false + name: out + output: true + type: at::TensorList + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: [] + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false +- name: _fused_adamw + operator_name: _fused_adamw + overload_name: '' + manual_kernel_registration: false + category_override: '' + schema_string: aten::_fused_adamw(Tensor[] self, Tensor[] grads, Tensor[] exp_avgs, Tensor[] exp_avg_sqs, Tensor[] max_exp_avg_sqs, Tensor[] state_steps, *, float lr, float beta1, float beta2, float weight_decay, float eps, bool amsgrad, bool maximize, Tensor? grad_scale=None, Tensor? found_inf=None) -> (Tensor[] self_out, Tensor[] grads_out, Tensor[] exp_avgs_out, Tensor[] exp_avg_sqs_out, Tensor[] max_exp_avg_sqs_out) + arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + schema_order_cpp_signature: ::std::tuple<::std::vector,::std::vector,::std::vector,::std::vector,::std::vector> (at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, at::TensorList, double, double, double, double, double, bool, bool, const c10::optional &, const c10::optional &) + schema_order_arguments: + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: self + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: grads + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avgs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: max_exp_avg_sqs + type: at::TensorList + - annotation: null + dynamic_type: at::TensorList + is_nullable: false + name: state_steps + type: at::TensorList + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: lr + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta1 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: beta2 + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: weight_decay + type: double + - annotation: null + dynamic_type: double + is_nullable: false + kwarg_only: true + name: eps + type: double + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: amsgrad + type: bool + - annotation: null + dynamic_type: bool + is_nullable: false + kwarg_only: true + name: maximize + type: bool + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: grad_scale + type: const c10::optional & + - annotation: null + default: '{}' + dynamic_type: at::Tensor + is_nullable: true + kwarg_only: true + name: found_inf + type: const c10::optional & + method_of: + - Type + - namespace + mode: native + python_module: '' + returns: + - dynamic_type: at::TensorList + field_name: self_out + name: self_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: grads_out + name: grads_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avgs_out + name: exp_avgs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: exp_avg_sqs_out + name: exp_avg_sqs_out + type: ::std::vector + - dynamic_type: at::TensorList + field_name: max_exp_avg_sqs_out + name: max_exp_avg_sqs_out + type: ::std::vector + inplace: false + is_factory_method: false + abstract: true + device_guard: false + with_gil: false + deprecated: false + has_math_kernel: false diff --git a/vignettes/serialization.Rmd b/vignettes/serialization.Rmd index 18dcf5c5da..51ea2acd14 100644 --- a/vignettes/serialization.Rmd +++ b/vignettes/serialization.Rmd @@ -70,6 +70,7 @@ model_ <- torch_load("model.pt") x <- torch_randn(50, 10) torch_allclose(model(x), model_(x)) ``` + ## Loading models saved in python Currently the only way to load models from python is to rewrite the model architecture in R. All the parameter names must be identical. diff --git a/vignettes/tensor/index.Rmd b/vignettes/tensor/index.Rmd index f1ebfe0124..bc914786ce 100644 --- a/vignettes/tensor/index.Rmd +++ b/vignettes/tensor/index.Rmd @@ -3244,12 +3244,6 @@ svd(some=TRUE, compute_uv=TRUE) -> (Tensor, Tensor, Tensor) See `?torch_svd` -## symeig - -symeig(eigenvectors=FALSE, upper=TRUE) -> (Tensor, Tensor) - -See `?torch_symeig` - ## t t() -> Tensor