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LegacyTHFunctionsCUDA.h
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LegacyTHFunctionsCUDA.h
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#pragma once
#include <ATen/Context.h>
#include <c10/core/ScalarType.h>
#include <c10/core/TensorOptions.h>
namespace c10 {
class Scalar;
}
namespace at {
struct Generator;
class Tensor;
struct Type;
} // namespace at
namespace at {
namespace native {
namespace legacy {
namespace cuda {
Tensor & _th_masked_fill_(Tensor & self, const Tensor & mask, Scalar value);
Tensor & _th_masked_fill_bool_(Tensor & self, const Tensor & mask, Scalar value);
Tensor & _th_masked_scatter_(Tensor & self, const Tensor & mask, const Tensor & source);
Tensor & _th_masked_scatter_bool_(Tensor & self, const Tensor & mask, const Tensor & source);
Tensor & _th_index_copy_(Tensor & self, int64_t dim, const Tensor & index, const Tensor & source);
Tensor & _th_take_out(Tensor & result, const Tensor & self, const Tensor & index);
Tensor _th_take(const Tensor & self, const Tensor & index);
Tensor & _th_put_(Tensor & self, const Tensor & index, const Tensor & source, bool accumulate);
Tensor & _th_index_fill_(Tensor & self, int64_t dim, const Tensor & index, Scalar value);
std::tuple<Tensor &,Tensor &> _th_mode_out(Tensor & values, Tensor & indices, const Tensor & self, int64_t dim, bool keepdim);
std::tuple<Tensor,Tensor> _th_mode(const Tensor & self, int64_t dim, bool keepdim);
std::tuple<Tensor &,Tensor &> _th_sort_out(Tensor & values, Tensor & indices, const Tensor & self, int64_t dim, bool descending);
std::tuple<Tensor,Tensor> _th_sort(const Tensor & self, int64_t dim, bool descending);
std::tuple<Tensor &,Tensor &> _th_topk_out(Tensor & values, Tensor & indices, const Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted);
std::tuple<Tensor,Tensor> _th_topk(const Tensor & self, int64_t k, int64_t dim, bool largest, bool sorted);
Tensor & _th_renorm_out(Tensor & result, const Tensor & self, Scalar p, int64_t dim, Scalar maxnorm);
Tensor _th_renorm(const Tensor & self, Scalar p, int64_t dim, Scalar maxnorm);
Tensor & _th_renorm_(Tensor & self, Scalar p, int64_t dim, Scalar maxnorm);
Tensor & _th_cross_kernel_out(Tensor & result, const Tensor & self, const Tensor & other, int64_t dim);
Tensor _th_cross_kernel(const Tensor & self, const Tensor & other, int64_t dim);
std::tuple<Tensor &,Tensor &> _th_gels_out(Tensor & res1, Tensor & res2, const Tensor & self, const Tensor & A);
std::tuple<Tensor,Tensor> _th_gels(const Tensor & self, const Tensor & A);
Tensor & _th_potri_out(Tensor & output, const Tensor & self, bool upper);
Tensor _th_potri(const Tensor & self, bool upper);
std::tuple<Tensor &,Tensor &> _th_geqrf_out(Tensor & res1, Tensor & res2, const Tensor & self);
std::tuple<Tensor,Tensor> _th_geqrf(const Tensor & self);
std::tuple<Tensor &,Tensor &> _th_multinomial_alias_setup_out(Tensor & J, Tensor & q, const Tensor & probs);
std::tuple<Tensor,Tensor> _th_multinomial_alias_setup(const Tensor & probs);
Tensor & _th_multinomial_alias_draw_out(Tensor & result, const Tensor & q, const Tensor & J, int64_t num_samples, c10::optional<Generator> generator);
Tensor _th_multinomial_alias_draw(const Tensor & q, const Tensor & J, int64_t num_samples, c10::optional<Generator> generator);
Tensor & _th_copy_ignoring_overlaps_(Tensor & self, const Tensor & src);
Tensor & _thnn_multi_margin_loss_forward_out(Tensor & output, const Tensor & self, const Tensor & target, Scalar p, Scalar margin, const Tensor & weight, int64_t reduction);
Tensor _thnn_multi_margin_loss_forward(const Tensor & self, const Tensor & target, Scalar p, Scalar margin, const Tensor & weight, int64_t reduction);
Tensor & _thnn_multi_margin_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, Scalar p, Scalar margin, const Tensor & weight, int64_t reduction);
Tensor _thnn_multi_margin_loss_backward(const Tensor & grad_output, const Tensor & self, const Tensor & target, Scalar p, Scalar margin, const Tensor & weight, int64_t reduction);
std::tuple<Tensor &,Tensor &> _thnn_multilabel_margin_loss_forward_out(Tensor & output, Tensor & is_target, const Tensor & self, const Tensor & target, int64_t reduction);
std::tuple<Tensor,Tensor> _thnn_multilabel_margin_loss_forward(const Tensor & self, const Tensor & target, int64_t reduction);
Tensor & _thnn_multilabel_margin_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, int64_t reduction, const Tensor & is_target);
Tensor _thnn_multilabel_margin_loss_backward(const Tensor & grad_output, const Tensor & self, const Tensor & target, int64_t reduction, const Tensor & is_target);
std::tuple<Tensor &,Tensor &> _thnn_nll_loss_forward_out(Tensor & output, Tensor & total_weight, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index);
std::tuple<Tensor,Tensor> _thnn_nll_loss_forward(const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index);
Tensor & _thnn_nll_loss_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index, const Tensor & total_weight);
Tensor _thnn_nll_loss_backward(const Tensor & grad_output, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index, const Tensor & total_weight);
std::tuple<Tensor &,Tensor &> _thnn_nll_loss2d_forward_out(Tensor & output, Tensor & total_weight, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index);
std::tuple<Tensor,Tensor> _thnn_nll_loss2d_forward(const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index);
Tensor & _thnn_nll_loss2d_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index, const Tensor & total_weight);
Tensor _thnn_nll_loss2d_backward(const Tensor & grad_output, const Tensor & self, const Tensor & target, const Tensor & weight, int64_t reduction, int64_t ignore_index, const Tensor & total_weight);
Tensor & _thnn_glu_forward_out(Tensor & output, const Tensor & self, int64_t dim);
Tensor _thnn_glu_forward(const Tensor & self, int64_t dim);
Tensor & _thnn_glu_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, int64_t dim);
Tensor _thnn_glu_backward(const Tensor & grad_output, const Tensor & self, int64_t dim);
std::tuple<Tensor &,Tensor &> _thnn_log_sigmoid_forward_out(Tensor & output, Tensor & buffer, const Tensor & self);
std::tuple<Tensor,Tensor> _thnn_log_sigmoid_forward(const Tensor & self);
Tensor & _thnn_log_sigmoid_backward_out(Tensor & grad_input, const Tensor & grad_output, const Tensor & self, const Tensor & buffer);
Tensor _thnn_log_sigmoid_backward(const Tensor & grad_output, const Tensor & self, const Tensor & buffer);
Tensor & _thnn_rrelu_with_noise_forward_out(Tensor & output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, c10::optional<at::Generator> generator);
Tensor _thnn_rrelu_with_noise_forward(const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, c10::optional<at::Generator> generator);
Tensor _thnn_rrelu_with_noise_backward(const Tensor & grad_output, const Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training);
Tensor & _thnn_rrelu_with_noise_forward_(Tensor & self, const Tensor & noise, Scalar lower, Scalar upper, bool training, c10::optional<at::Generator> generator);
std::tuple<Tensor &,Tensor &,Tensor &> _thnn_conv2d_forward_out(Tensor & output, Tensor & columns, Tensor & ones, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, const Tensor & bias, IntArrayRef stride, IntArrayRef padding);
std::tuple<Tensor,Tensor,Tensor> _thnn_conv2d_forward(const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, const Tensor & bias, IntArrayRef stride, IntArrayRef padding);
std::tuple<Tensor &,Tensor &,Tensor &> _thnn_conv2d_backward_out(Tensor & grad_input, Tensor & grad_weight, Tensor & grad_bias, const Tensor & grad_output, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, const Tensor & columns, const Tensor & ones);
std::tuple<Tensor,Tensor,Tensor> _thnn_conv2d_backward(const Tensor & grad_output, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, const Tensor & columns, const Tensor & ones, std::array<bool,3> output_mask);
Tensor & _thnn_conv_depthwise2d_forward_out(Tensor & output, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, const Tensor & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation);
Tensor _thnn_conv_depthwise2d_forward(const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, const Tensor & bias, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation);
std::tuple<Tensor &,Tensor &> _thnn_conv_depthwise2d_backward_out(Tensor & grad_input, Tensor & grad_weight, const Tensor & grad_output, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation);
std::tuple<Tensor,Tensor> _thnn_conv_depthwise2d_backward(const Tensor & grad_output, const Tensor & self, const Tensor & weight, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, std::array<bool,2> output_mask);
} // namespace th
} // namespace legacy
} // namespace native
} // namespace at