forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
CUDA support in the CSR layout: sparse_to_dense/add_sparse_csr (pytor…
…ch#59011) Summary: Pull Request resolved: pytorch#59011 Test Plan: Imported from OSS Reviewed By: zou3519 Differential Revision: D28719550 Pulled By: bhosmer fbshipit-source-id: 530c7cd1b20ae6d8865fd414afaf6fab27a643e6
- Loading branch information
1 parent
414c600
commit d1f8775
Showing
4 changed files
with
198 additions
and
10 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
160 changes: 160 additions & 0 deletions
160
aten/src/ATen/native/sparse/cuda/SparseCsrTensorMath.cu
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,160 @@ | ||
| #include <ATen/ATen.h> | ||
| #include <ATen/ExpandUtils.h> | ||
| #include <ATen/InitialTensorOptions.h> | ||
| #include <ATen/NativeFunctions.h> | ||
| #include <ATen/SparseCsrTensorImpl.h> | ||
| #include <ATen/SparseCsrTensorUtils.h> | ||
| #include <ATen/SparseTensorUtils.h> | ||
| #include <ATen/WrapDimUtilsMulti.h> | ||
| #include <ATen/native/BinaryOps.h> | ||
| #include <ATen/native/Resize.h> | ||
| #include <algorithm> | ||
|
|
||
| #include <cuda_runtime.h> | ||
| #include <type_traits> | ||
|
|
||
| #include <THC/THCTensorMathPointwise.cuh> | ||
| #include <THC/THCThrustAllocator.cuh> | ||
|
|
||
| #include <ATen/cuda/CUDAContext.h> | ||
| #include <ATen/cuda/CUDAUtils.h> | ||
| #include <c10/cuda/CUDACachingAllocator.h> | ||
| #include <ATen/native/sparse/cuda/SparseCUDABlas.cuh> | ||
|
|
||
| #include <thrust/device_ptr.h> | ||
| #include <thrust/execution_policy.h> | ||
| #include <thrust/for_each.h> | ||
| #include <thrust/sequence.h> | ||
|
|
||
| namespace at { | ||
| namespace native { | ||
|
|
||
| using namespace at::sparse_csr; | ||
| // certain utiliy functions are usable from sparse COO. | ||
| using namespace at::sparse; | ||
|
|
||
| Tensor& add_out_dense_sparse_csr_cuda( | ||
| Tensor& output, | ||
| const Tensor& dense, | ||
| const SparseCsrTensor& src, | ||
| const Scalar& alpha) { | ||
| TORCH_INTERNAL_ASSERT(dense.layout() == kStrided); | ||
| TORCH_INTERNAL_ASSERT(src.is_sparse_csr()); | ||
| TORCH_INTERNAL_ASSERT(dense.is_cuda()); | ||
|
|
||
| TORCH_CHECK( | ||
| output.is_contiguous(), | ||
| "out argument must be contiguous, but got: ", | ||
| output.suggest_memory_format()); | ||
| TORCH_CHECK( | ||
| output.is_cuda(), | ||
| "add: expected 'out' to be CUDA tensor, but got tensor on device: ", | ||
| output.device()); | ||
|
|
||
| TORCH_CHECK( | ||
| src.is_cuda(), | ||
| "add: expected 'other' to be a CUDA tensor, but got tensor on device: ", | ||
| src.device()); | ||
|
|
||
| TORCH_CHECK( | ||
| dense.sizes().equals(src.sizes()), | ||
| "add: expected 'self' and 'other' to have same size, but self has size ", | ||
| dense.sizes(), | ||
| " while other has size ", | ||
| src.sizes(), | ||
| " (FYI: op2-sparse addition does not currently support broadcasting)"); | ||
|
|
||
| auto commonDtype = promoteTypes(dense.scalar_type(), src.scalar_type()); | ||
| TORCH_CHECK( | ||
| canCast(commonDtype, output.scalar_type()), | ||
| "Can't convert result type ", | ||
| commonDtype, | ||
| " to output ", | ||
| output.scalar_type(), | ||
| " in add operation"); | ||
|
|
||
| Tensor src_values = src.values(); | ||
| Tensor src_crow_indices = src.crow_indices(); | ||
| Tensor src_col_indices = src.col_indices(); | ||
|
|
||
| resize_output(output, dense.sizes()); | ||
|
|
||
| Tensor resultBuffer = output; | ||
| Tensor valuesBuffer = src_values.to(commonDtype); | ||
| if (output.scalar_type() != commonDtype) { | ||
| resultBuffer = dense.to(commonDtype); | ||
| } else if (!is_same_tensor(output, dense)) { | ||
| resultBuffer.copy_(dense); | ||
| } | ||
| AT_DISPATCH_ALL_TYPES( | ||
| commonDtype, | ||
| "add_out_op2_sparse_csr", | ||
| [&valuesBuffer, &resultBuffer, &alpha, &src_crow_indices, &src_col_indices]() { | ||
| AT_DISPATCH_INDEX_TYPES( | ||
| src_crow_indices.scalar_type(), | ||
| "csr_add_out_crow_indices", | ||
| [&valuesBuffer, &resultBuffer, &alpha, &src_crow_indices, &src_col_indices]() { | ||
| scalar_t* values_accessor = valuesBuffer.data_ptr<scalar_t>(); | ||
| scalar_t* out_ptr = resultBuffer.data_ptr<scalar_t>(); | ||
| scalar_t cast_value = alpha.to<scalar_t>(); | ||
|
|
||
| index_t* crow_indices_accessor = src_crow_indices.data_ptr<index_t>(); | ||
| index_t* col_indices_accessor = src_col_indices.data_ptr<index_t>(); | ||
| int64_t out_storage_offset = resultBuffer.storage_offset(); | ||
|
|
||
| auto out_strides = resultBuffer.strides(); | ||
| int64_t out_strides0 = out_strides[0]; | ||
| int64_t out_strides1 = out_strides[1]; | ||
|
|
||
| cudaStream_t stream = at::cuda::getCurrentCUDAStream(); | ||
| auto allocator = THCThrustAllocator(globalContext().lazyInitCUDA()); | ||
| auto policy = thrust::cuda::par(allocator).on(stream); | ||
|
|
||
| // Note that this could be wildly imbalanced if the sparsity pattern varies a lot between rows. | ||
| thrust::for_each( | ||
| policy, | ||
| thrust::make_counting_iterator(int64_t(0)), | ||
| thrust::make_counting_iterator(int64_t(src_crow_indices.size(0) - 1)), | ||
| [values_accessor, | ||
| crow_indices_accessor, | ||
| col_indices_accessor, | ||
| out_ptr, | ||
| out_storage_offset, | ||
| out_strides0, | ||
| cast_value, | ||
| out_strides1 | ||
| ]__device__(int64_t irow) { | ||
| index_t start_index = crow_indices_accessor[irow]; | ||
| index_t end_index = crow_indices_accessor[irow + 1]; | ||
|
|
||
| for (index_t i = start_index; i < end_index; ++i) { | ||
| auto icol = col_indices_accessor[i]; | ||
| auto index = out_storage_offset + irow * out_strides0 + icol * out_strides1; | ||
| out_ptr[index] += cast_value * values_accessor[i]; | ||
| } | ||
| }); | ||
| }); | ||
| }); | ||
| if (output.scalar_type() != commonDtype) { | ||
| output.copy_(resultBuffer); | ||
| } | ||
| return output; | ||
| } | ||
|
|
||
| Tensor& add_out_sparse_csr_cuda( | ||
| const Tensor& self, | ||
| const SparseCsrTensor& other, | ||
| const Scalar& alpha, | ||
| SparseCsrTensor& out) { | ||
| if (self.layout() == kStrided) { | ||
| return add_out_dense_sparse_csr_cuda(out, self, other, alpha); | ||
| } else { | ||
| TORCH_CHECK( | ||
| false, | ||
| "NotImplementedError: Addition of sparse CSR tensors is not yet implemented.") | ||
| } | ||
| return out; | ||
| } | ||
|
|
||
| } // namespace native | ||
| } // namespace at |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters