ai-content-maker/.venv/Lib/site-packages/torch/include/ATen/cuda/CUDABlas.h

376 lines
13 KiB
C++

#pragma once
/*
Provides a subset of CUDA BLAS functions as templates:
gemm<Dtype>(transa, transb, m, n, k, alpha, a, lda, b, ldb, beta, c,
ldc)
gemv<Dtype>(transa, m, n, alpha, a, lda, x, incx, beta, y, incy)
dot<Dtype>(n, x, incx, y, incy, result)
where Dtype is double, float, at::Half or at::BFloat16 (ROCm, NOT for dot).
The functions are available in at::cuda::blas namespace.
*/
#include <ATen/cuda/CUDAContext.h>
#include <ATen/OpMathType.h>
namespace at::cuda::blas {
// RAII guard that sets the CuBLAS pointer mode and restores it to
// its previous value when the guard is destroyed
class PointerModeGuard {
public:
PointerModeGuard(cublasHandle_t handle, cublasPointerMode_t mode) :
handle(handle) {
TORCH_CUDABLAS_CHECK(cublasGetPointerMode(handle, &previous_mode));
TORCH_CUDABLAS_CHECK(cublasSetPointerMode(handle, mode));
}
~PointerModeGuard() {
cublasSetPointerMode(handle, previous_mode);
}
private:
cublasHandle_t handle;
cublasPointerMode_t previous_mode;
};
/* LEVEL 3 BLAS FUNCTIONS */
#define CUDABLAS_GEMM_ARGTYPES(Dtype) \
char transa, char transb, int64_t m, int64_t n, int64_t k, at::opmath_type<Dtype> alpha, \
const Dtype *a, int64_t lda, const Dtype *b, int64_t ldb, at::opmath_type<Dtype> beta,\
Dtype *c, int64_t ldc
#define CUDABLAS_GEMM_ARGS(Dtype) transa, transb, m, n, k, alpha, a, lda, b, ldb, beta, c, ldc
template <typename Dtype>
inline void gemm(CUDABLAS_GEMM_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::gemm: not implemented for ", typeid(Dtype).name());
}
template <>
void gemm<double>(CUDABLAS_GEMM_ARGTYPES(double));
template <>
void gemm<float>(CUDABLAS_GEMM_ARGTYPES(float));
template <>
void gemm<c10::complex<double>>(CUDABLAS_GEMM_ARGTYPES(c10::complex<double>));
template <>
void gemm<c10::complex<float>>(CUDABLAS_GEMM_ARGTYPES(c10::complex<float>));
template <>
void gemm<at::Half>(CUDABLAS_GEMM_ARGTYPES(at::Half));
template <>
void gemm<at::BFloat16>(CUDABLAS_GEMM_ARGTYPES(at::BFloat16));
template <typename Dtype>
inline void gemm_internal(CUDABLAS_GEMM_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::gemm_internal: not implemented for ", typeid(Dtype).name());
}
template <>
void gemm_internal<double>(CUDABLAS_GEMM_ARGTYPES(double));
template <>
void gemm_internal<float>(CUDABLAS_GEMM_ARGTYPES(float));
template <>
void gemm_internal<c10::complex<double>>(CUDABLAS_GEMM_ARGTYPES(c10::complex<double>));
template <>
void gemm_internal<c10::complex<float>>(CUDABLAS_GEMM_ARGTYPES(c10::complex<float>));
template <>
void gemm_internal<at::Half>(CUDABLAS_GEMM_ARGTYPES(at::Half));
template <>
void gemm_internal<at::BFloat16>(CUDABLAS_GEMM_ARGTYPES(at::BFloat16));
#if (!defined(USE_ROCM) && !defined(_MSC_VER)) || (defined(USE_ROCM) && ROCM_VERSION >= 50700)
enum GEMMAndBiasActivationEpilogue {
None,
RELU,
GELU,
};
// NOTE: GELU activation is not supported prior to CUDA 11.4 and will
// do nothing if passed in that case.
template <typename Dtype>
void gemm_and_bias(
bool transpose_mat1,
bool transpose_mat2,
int64_t m,
int64_t n,
int64_t k,
at::opmath_type<Dtype> alpha_val,
const Dtype* mat1_ptr,
int64_t mat1_ld,
const Dtype* mat2_ptr,
int64_t mat2_ld,
const Dtype* bias,
Dtype* result_ptr,
int64_t result_ld,
GEMMAndBiasActivationEpilogue activation = GEMMAndBiasActivationEpilogue::None);
void int8_gemm(
bool transpose_mat1,
bool transpose_mat2,
int64_t m,
int64_t n,
int64_t k,
const int8_t* mat1_ptr,
int64_t mat1_ld,
const int8_t* mat2_ptr,
int64_t mat2_ld,
int32_t* result_ptr,
int64_t result_ld);
void scaled_gemm(
char transa,
char transb,
int64_t m,
int64_t n,
int64_t k,
const void* mat1_ptr,
const void* mat1_scale_ptr,
int64_t mat1_ld,
ScalarType mat1_dtype,
const void* mat2_ptr,
const void* mat2_scale_ptr,
int64_t mat2_ld,
ScalarType mat2_dtype,
const void* bias_ptr,
ScalarType bias_dtype,
void* result_ptr,
const void* result_scale_ptr,
int64_t result_ld,
ScalarType result_dtype,
void* amax_ptr,
bool use_fast_accum);
#endif
#define CUDABLAS_BGEMM_ARGTYPES(Dtype) \
char transa, char transb, int64_t m, int64_t n, int64_t k, at::opmath_type<Dtype> alpha, \
const Dtype *a, int64_t lda, int64_t stridea, \
const Dtype *b, int64_t ldb, int64_t strideb, \
at::opmath_type<Dtype> beta, Dtype *c, int64_t ldc, int64_t stridec, int64_t num_batches
#define CUDABLAS_BGEMM_ARGS(Dtype) \
transa, transb, m, n, k, alpha, a, lda, stridea, b, ldb, strideb, beta, c, ldc, stridec, num_batches
template <typename Dtype>
inline void bgemm(CUDABLAS_BGEMM_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::bgemm: not implemented for ", typeid(Dtype).name());
}
template <>
void bgemm<double>(CUDABLAS_BGEMM_ARGTYPES(double));
template <>
void bgemm<float>(CUDABLAS_BGEMM_ARGTYPES(float));
template <>
void bgemm<c10::complex<double>>(CUDABLAS_BGEMM_ARGTYPES(c10::complex<double>));
template <>
void bgemm<c10::complex<float>>(CUDABLAS_BGEMM_ARGTYPES(c10::complex<float>));
template <>
void bgemm<at::Half>(CUDABLAS_BGEMM_ARGTYPES(at::Half));
template <>
void bgemm<at::BFloat16>(CUDABLAS_BGEMM_ARGTYPES(at::BFloat16));
template <typename Dtype>
inline void bgemm_internal(CUDABLAS_BGEMM_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::bgemm_internal: not implemented for ", typeid(Dtype).name());
}
template <>
void bgemm_internal<double>(CUDABLAS_BGEMM_ARGTYPES(double));
template <>
void bgemm_internal<float>(CUDABLAS_BGEMM_ARGTYPES(float));
template <>
void bgemm_internal<c10::complex<double>>(CUDABLAS_BGEMM_ARGTYPES(c10::complex<double>));
template <>
void bgemm_internal<c10::complex<float>>(CUDABLAS_BGEMM_ARGTYPES(c10::complex<float>));
template <>
void bgemm_internal<at::Half>(CUDABLAS_BGEMM_ARGTYPES(at::Half));
template <>
void bgemm_internal<at::BFloat16>(CUDABLAS_BGEMM_ARGTYPES(at::BFloat16));
#if defined(USE_ROCM) && ROCM_VERSION <= 50500
// ROCm 5.6 hipblas matches the const Dtype *A API, but prior hipblas does not.
#define CUDABLAS_TRSM_ARGTYPES(Dtype) \
hipblasHandle_t handle, hipblasSideMode_t side, hipblasFillMode_t uplo, \
hipblasOperation_t trans, hipblasDiagType_t diag, int m, int n, \
const Dtype *alpha, Dtype *A, int lda, Dtype *B, int ldb
#else
#define CUDABLAS_TRSM_ARGTYPES(Dtype) \
cublasHandle_t handle, cublasSideMode_t side, cublasFillMode_t uplo, \
cublasOperation_t trans, cublasDiagType_t diag, int m, int n, \
const Dtype *alpha, const Dtype *A, int lda, Dtype *B, int ldb
#endif
template <typename Dtype>
inline void trsm(CUDABLAS_TRSM_ARGTYPES(Dtype)) {
TORCH_INTERNAL_ASSERT(false, "at::cuda::blas::trsm: not implemented for ", typeid(Dtype).name());
}
template <>
TORCH_CUDA_CU_API void trsm<float>(CUDABLAS_TRSM_ARGTYPES(float));
template <>
TORCH_CUDA_CU_API void trsm<double>(CUDABLAS_TRSM_ARGTYPES(double));
template <>
TORCH_CUDA_CU_API void trsm<c10::complex<float>>(CUDABLAS_TRSM_ARGTYPES(c10::complex<float>));
template <>
TORCH_CUDA_CU_API void trsm<c10::complex<double>>(CUDABLAS_TRSM_ARGTYPES(c10::complex<double>));
#define CUDABLAS_TRSM_BATCHED_ARGTYPES(Dtype) \
cublasHandle_t handle, cublasSideMode_t side, cublasFillMode_t uplo, \
cublasOperation_t trans, cublasDiagType_t diag, int m, int n, \
const Dtype *alpha, Dtype *A[], int lda, Dtype *B[], int ldb, \
int batchCount
template <typename Dtype>
inline void trsmBatched(CUDABLAS_TRSM_BATCHED_ARGTYPES(Dtype)) {
TORCH_INTERNAL_ASSERT(
false,
"at::cuda::blas::trsmBatched: not implemented for ",
typeid(Dtype).name());
}
template <>
TORCH_CUDA_CU_API void trsmBatched<float>(CUDABLAS_TRSM_BATCHED_ARGTYPES(float));
template <>
TORCH_CUDA_CU_API void trsmBatched<double>(CUDABLAS_TRSM_BATCHED_ARGTYPES(double));
template <>
TORCH_CUDA_CU_API void trsmBatched<c10::complex<float>>(CUDABLAS_TRSM_BATCHED_ARGTYPES(c10::complex<float>));
template <>
TORCH_CUDA_CU_API void trsmBatched<c10::complex<double>>(CUDABLAS_TRSM_BATCHED_ARGTYPES(c10::complex<double>));
/* LEVEL 2 BLAS FUNCTIONS */
#define CUDABLAS_GEMV_ARGTYPES(Dtype) \
char trans, int64_t m, int64_t n, Dtype alpha, const Dtype *a, int64_t lda, \
const Dtype *x, int64_t incx, Dtype beta, Dtype *y, int64_t incy
template <typename Dtype>
inline void gemv(CUDABLAS_GEMV_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::gemv: not implemented for ", typeid(Dtype).name());
}
template <>
void gemv<double>(CUDABLAS_GEMV_ARGTYPES(double));
template <>
void gemv<float>(CUDABLAS_GEMV_ARGTYPES(float));
template <>
void gemv<c10::complex<double>>(CUDABLAS_GEMV_ARGTYPES(c10::complex<double>));
template <>
void gemv<c10::complex<float>>(CUDABLAS_GEMV_ARGTYPES(c10::complex<float>));
template <>
void gemv<at::Half>(CUDABLAS_GEMV_ARGTYPES(at::Half));
template <>
void gemv<at::BFloat16>(CUDABLAS_GEMV_ARGTYPES(at::BFloat16));
/* LEVEL 1 BLAS FUNCTIONS */
#define CUDABLAS_DOT_ARGTYPES(Dtype) \
cublasHandle_t handle, int n, const Dtype *x, int incx, const Dtype *y, \
int incy, Dtype *result
template <typename Dtype>
inline void dot(CUDABLAS_DOT_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::dot: not implemented for ", typeid(Dtype).name());
}
template <>
void dot<double>(CUDABLAS_DOT_ARGTYPES(double));
template <>
void dot<float>(CUDABLAS_DOT_ARGTYPES(float));
template <>
void dot<at::Half>(CUDABLAS_DOT_ARGTYPES(at::Half));
template <>
void dot<at::BFloat16>(CUDABLAS_DOT_ARGTYPES(at::BFloat16));
template <>
void dot<c10::complex<double>>(CUDABLAS_DOT_ARGTYPES(c10::complex<double>));
template <>
void dot<c10::complex<float>>(CUDABLAS_DOT_ARGTYPES(c10::complex<float>));
template <typename Dtype>
inline void vdot(CUDABLAS_DOT_ARGTYPES(Dtype)) {
AT_ERROR("at::cuda::blas::vdot: not implemented for ", typeid(Dtype).name());
}
template <>
void vdot<c10::complex<float>>(CUDABLAS_DOT_ARGTYPES(c10::complex<float>));
template <>
void vdot<c10::complex<double>>(CUDABLAS_DOT_ARGTYPES(c10::complex<double>));
#define CUDABLAS_GETRS_ARGTYPES(Dtype) \
cublasHandle_t handle, cublasOperation_t trans, \
int n, int nrhs, Dtype** dA_array, int lda, int* ipiv_array, \
Dtype** dB_array, int ldb, int* info_array, int batchsize
template<class Dtype>
void getrsBatched(CUDABLAS_GETRS_ARGTYPES(Dtype)) {
TORCH_INTERNAL_ASSERT(false, "at::cuda::blas::getrsBatched: not implemented for ",
typeid(Dtype).name());
}
template<>
TORCH_CUDA_CU_API void getrsBatched<float>(CUDABLAS_GETRS_ARGTYPES(float));
template<>
TORCH_CUDA_CU_API void getrsBatched<double>(CUDABLAS_GETRS_ARGTYPES(double));
template<>
TORCH_CUDA_CU_API void getrsBatched<c10::complex<float>>(CUDABLAS_GETRS_ARGTYPES(c10::complex<float>));
template<>
TORCH_CUDA_CU_API void getrsBatched<c10::complex<double>>(CUDABLAS_GETRS_ARGTYPES(c10::complex<double>));
#define CUDABLAS_GEQRF_BATCHED_ARGTYPES(Dtype) \
cublasHandle_t handle, int m, int n, Dtype **A_array, int lda, \
Dtype **tau_array, int *info, int batchsize
template <class Dtype>
void geqrfBatched(CUDABLAS_GEQRF_BATCHED_ARGTYPES(Dtype)) {
TORCH_INTERNAL_ASSERT(
false,
"at::cuda::blas::geqrfBatched: not implemented for ",
typeid(Dtype).name());
}
template <>
TORCH_CUDA_CU_API void geqrfBatched<float>(CUDABLAS_GEQRF_BATCHED_ARGTYPES(float));
template <>
TORCH_CUDA_CU_API void geqrfBatched<double>(CUDABLAS_GEQRF_BATCHED_ARGTYPES(double));
template <>
TORCH_CUDA_CU_API void geqrfBatched<c10::complex<double>>(
CUDABLAS_GEQRF_BATCHED_ARGTYPES(c10::complex<double>));
template <>
TORCH_CUDA_CU_API void geqrfBatched<c10::complex<float>>(
CUDABLAS_GEQRF_BATCHED_ARGTYPES(c10::complex<float>));
#define CUDABLAS_GETRF_ARGTYPES(Dtype) \
int n, Dtype** dA_array, int ldda, int* ipiv_array, int* info_array, int batchsize
template<class Dtype>
void getrfBatched(CUDABLAS_GETRF_ARGTYPES(Dtype)) {
TORCH_CHECK(false, "at::cuda::blas::getrfBatched: not implemented for ", typeid(Dtype).name());
}
template<>
TORCH_CUDA_CU_API void getrfBatched<float>(CUDABLAS_GETRF_ARGTYPES(float));
template<>
TORCH_CUDA_CU_API void getrfBatched<double>(CUDABLAS_GETRF_ARGTYPES(double));
template<>
TORCH_CUDA_CU_API void getrfBatched<c10::complex<double>>(CUDABLAS_GETRF_ARGTYPES(c10::complex<double>));
template<>
TORCH_CUDA_CU_API void getrfBatched<c10::complex<float>>(CUDABLAS_GETRF_ARGTYPES(c10::complex<float>));
#define CUDABLAS_GELS_BATCHED_ARGTYPES(Dtype) \
cublasHandle_t handle, cublasOperation_t trans, int m, int n, int nrhs, Dtype** dA_array, int ldda, Dtype** dC_array, int lddc, int* info, int *devInfoArray, int batchSize
template <class Dtype>
void gelsBatched(CUDABLAS_GELS_BATCHED_ARGTYPES(Dtype)) {
TORCH_INTERNAL_ASSERT(false, "at::cuda::blas::gelsBatched: not implemented for ", typeid(Dtype).name());
}
template<>
TORCH_CUDA_CU_API void gelsBatched<double>(CUDABLAS_GELS_BATCHED_ARGTYPES(double));
template<>
TORCH_CUDA_CU_API void gelsBatched<float>(CUDABLAS_GELS_BATCHED_ARGTYPES(float));
template<>
TORCH_CUDA_CU_API void gelsBatched<c10::complex<double>>(CUDABLAS_GELS_BATCHED_ARGTYPES(c10::complex<double>));
template<>
TORCH_CUDA_CU_API void gelsBatched<c10::complex<float>>(CUDABLAS_GELS_BATCHED_ARGTYPES(c10::complex<float>));
} // namespace at::cuda::blas