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Add macros to avoid frequent ROCm ifdefs. Clean up the ifdefs in core/kernels/sparse.

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PiperOrigin-RevId: 310004168
Change-Id: I1e48a64d6f7895c7f031397f1e231e231c4568cd
This commit is contained in:
Penporn Koanantakool 2020-05-05 12:58:01 -07:00 committed by TensorFlower Gardener
parent 1f02731775
commit 50840b9587
4 changed files with 20 additions and 49 deletions
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6
tensorflow/core/kernels/cuda_sparse.h
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@ -35,6 +35,9 @@ using gpusparseAction_t = cusparseAction_t;
using gpusparseHandle_t = cusparseHandle_t;
using gpuStream_t = cudaStream_t;
#define GPUSPARSE(postfix) CUSPARSE_##postfix
#define gpusparse(postfix) cusparse##postfix
#elif TENSORFLOW_USE_ROCM
#include "rocm/include/hipsparse/hipsparse.h"
@ -46,6 +49,9 @@ using gpusparseAction_t = hipsparseAction_t;
using gpusparseHandle_t = hipsparseHandle_t;
using gpuStream_t = hipStream_t;
#define GPUSPARSE(postfix) HIPSPARSE_##postfix
#define gpusparse(postfix) hipsparse##postfix
#endif
#include "tensorflow/core/framework/op_kernel.h"

39
tensorflow/core/kernels/sparse/mat_mul_op.cc
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@ -748,34 +748,19 @@ class CSRSparseMatrixMatMul<GPUDevice, T> {
// transA must be non-transpose if transB is transpose (cusparse
// limitation).
#if GOOGLE_CUDA
const gpusparseOperation_t transA = CUSPARSE_OPERATION_NON_TRANSPOSE;
#elif TENSORFLOW_USE_ROCM
const gpusparseOperation_t transA = HIPSPARSE_OPERATION_NON_TRANSPOSE;
#endif
const gpusparseOperation_t transA = GPUSPARSE(OPERATION_NON_TRANSPOSE);
// transB: b is row-major, and cusparse requires col-major b (or
// equivalently transB == transpose). this version is actually more
// efficient.
#if GOOGLE_CUDA
const gpusparseOperation_t transB = CUSPARSE_OPERATION_TRANSPOSE;
const gpusparseOperation_t transB = GPUSPARSE(OPERATION_TRANSPOSE);
gpusparseMatDescr_t descrA;
TF_RETURN_IF_GPUSPARSE_ERROR(cusparseCreateMatDescr(&descrA));
TF_RETURN_IF_GPUSPARSE_ERROR(gpusparse(CreateMatDescr)(&descrA));
TF_RETURN_IF_GPUSPARSE_ERROR(
cusparseSetMatType(descrA, CUSPARSE_MATRIX_TYPE_GENERAL));
gpusparse(SetMatType)(descrA, GPUSPARSE(MATRIX_TYPE_GENERAL)));
TF_RETURN_IF_GPUSPARSE_ERROR(
cusparseSetMatIndexBase(descrA, CUSPARSE_INDEX_BASE_ZERO));
#elif TENSORFLOW_USE_ROCM
const gpusparseOperation_t transB = HIPSPARSE_OPERATION_TRANSPOSE;
gpusparseMatDescr_t descrA;
TF_RETURN_IF_GPUSPARSE_ERROR(hipsparseCreateMatDescr(&descrA));
TF_RETURN_IF_GPUSPARSE_ERROR(
hipsparseSetMatType(descrA, HIPSPARSE_MATRIX_TYPE_GENERAL));
TF_RETURN_IF_GPUSPARSE_ERROR(
hipsparseSetMatIndexBase(descrA, HIPSPARSE_INDEX_BASE_ZERO));
#endif
gpusparse(SetMatIndexBase)(descrA, GPUSPARSE(INDEX_BASE_ZERO)));
// A is (m, k), Bt is (ldb, k) and Ct is (ldc, n)
const int k = b.dimension(0);
@ -838,19 +823,11 @@ class CSRSparseMatrixMatVec<GPUDevice, T> {
const T beta = 0;
gpusparseMatDescr_t descrA;
#if GOOGLE_CUDA
TF_RETURN_IF_GPUSPARSE_ERROR(cusparseCreateMatDescr(&descrA));
TF_RETURN_IF_GPUSPARSE_ERROR(gpusparse(CreateMatDescr)(&descrA));
TF_RETURN_IF_GPUSPARSE_ERROR(
cusparseSetMatType(descrA, CUSPARSE_MATRIX_TYPE_GENERAL));
gpusparse(SetMatType)(descrA, GPUSPARSE(MATRIX_TYPE_GENERAL)));
TF_RETURN_IF_GPUSPARSE_ERROR(
cusparseSetMatIndexBase(descrA, CUSPARSE_INDEX_BASE_ZERO));
#elif TENSORFLOW_USE_ROCM
TF_RETURN_IF_GPUSPARSE_ERROR(hipsparseCreateMatDescr(&descrA));
TF_RETURN_IF_GPUSPARSE_ERROR(
hipsparseSetMatType(descrA, HIPSPARSE_MATRIX_TYPE_GENERAL));
TF_RETURN_IF_GPUSPARSE_ERROR(
hipsparseSetMatIndexBase(descrA, HIPSPARSE_INDEX_BASE_ZERO));
#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
gpusparse(SetMatIndexBase)(descrA, GPUSPARSE(INDEX_BASE_ZERO)));
const int m = a.dense_shape_host(0);
const int n = a.dense_shape_host(1);

18
tensorflow/core/kernels/sparse/sparse_mat_mul_op.cc
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@ -529,20 +529,12 @@ struct CSRSparseSparseMatrixMatMul<GPUDevice, T>
adjoint_a_(adjoint_a),
transpose_b_(transpose_b) {
// TODO(ebrevdo): Figure out why transposed implementations crash cuSparse.
#if GOOGLE_CUDA
transA_ = transpose_a ? (adjoint_a ? CUSPARSE_OPERATION_TRANSPOSE
: CUSPARSE_OPERATION_CONJUGATE_TRANSPOSE)
: CUSPARSE_OPERATION_NON_TRANSPOSE;
transB_ = transpose_b ? CUSPARSE_OPERATION_TRANSPOSE
: CUSPARSE_OPERATION_NON_TRANSPOSE;
#elif TENSORFLOW_USE_ROCM
transA_ = transpose_a
? (adjoint_a ? HIPSPARSE_OPERATION_TRANSPOSE
: HIPSPARSE_OPERATION_CONJUGATE_TRANSPOSE)
: HIPSPARSE_OPERATION_NON_TRANSPOSE;
transB_ = transpose_b ? HIPSPARSE_OPERATION_TRANSPOSE
: HIPSPARSE_OPERATION_NON_TRANSPOSE;
#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
? (adjoint_a ? GPUSPARSE(OPERATION_TRANSPOSE)
: GPUSPARSE(OPERATION_CONJUGATE_TRANSPOSE))
: GPUSPARSE(OPERATION_NON_TRANSPOSE);
transB_ = transpose_b ? GPUSPARSE(OPERATION_TRANSPOSE)
: GPUSPARSE(OPERATION_NON_TRANSPOSE);
}
Status Initialize() {

6
tensorflow/core/kernels/sparse/transpose_op.cc
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@ -262,11 +262,7 @@ struct CSRSparseMatrixTransposeComponent<GPUDevice, T> {
TF_RETURN_IF_ERROR(ValidateTransposeInputs(x, *y));
GpuSparse cuda_sparse(ctx);
TF_RETURN_IF_ERROR(cuda_sparse.Initialize());
#if GOOGLE_CUDA
const gpusparseAction_t copyValues = CUSPARSE_ACTION_NUMERIC;
#elif TENSORFLOW_USE_ROCM
const gpusparseAction_t copyValues = HIPSPARSE_ACTION_NUMERIC;
#endif // GOOGLE_CUDA || TENSORFLOW_USE_ROCM
const gpusparseAction_t copyValues = GPUSPARSE(ACTION_NUMERIC);
const int rank = x.dense_shape_host.size();
const int m = x.row_ptr.size() - 1;
const int n = x.dense_shape_host(rank - 1);