#pragma once /* Provides a subset of CUDA BLAS functions as templates: gemm(transa, transb, m, n, k, alpha, a, lda, b, ldb, beta, c, ldc) gemv(transa, m, n, alpha, a, lda, x, incx, beta, y, incy) dot(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 #include namespace at { namespace cuda { namespace 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 alpha, \ const Dtype *a, int64_t lda, const Dtype *b, int64_t ldb, at::opmath_type beta,\ Dtype *c, int64_t ldc template inline void gemm(CUDABLAS_GEMM_ARGTYPES(Dtype)) { AT_ERROR("at::cuda::blas::gemm: not implemented for ", typeid(Dtype).name()); } template <> void gemm(CUDABLAS_GEMM_ARGTYPES(double)); template <> void gemm(CUDABLAS_GEMM_ARGTYPES(float)); #if !defined(USE_ROCM) || (defined(USE_ROCM) && ROCM_VERSION >= 21000) template <> void gemm>(CUDABLAS_GEMM_ARGTYPES(c10::complex)); #endif #if !defined(USE_ROCM) || (defined(USE_ROCM) && ROCM_VERSION >= 21000) template <> void gemm>(CUDABLAS_GEMM_ARGTYPES(c10::complex)); #endif template <> void gemm(CUDABLAS_GEMM_ARGTYPES(at::Half)); template <> void gemm(CUDABLAS_GEMM_ARGTYPES(at::BFloat16)); #if !defined(USE_ROCM) && !defined(_MSC_VER) 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 void gemm_and_bias( bool transpose_mat1, bool transpose_mat2, int64_t m, int64_t n, int64_t k, at::opmath_type 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); #endif #define CUDABLAS_BGEMM_ARGTYPES(Dtype) \ char transa, char transb, int64_t m, int64_t n, int64_t k, at::opmath_type alpha, \ const Dtype *a, int64_t lda, int64_t stridea, \ const Dtype *b, int64_t ldb, int64_t strideb, \ at::opmath_type beta, Dtype *c, int64_t ldc, int64_t stridec, int64_t num_batches template inline void bgemm(CUDABLAS_BGEMM_ARGTYPES(Dtype)) { AT_ERROR("at::cuda::blas::bgemm: not implemented for ", typeid(Dtype).name()); } template <> void bgemm(CUDABLAS_BGEMM_ARGTYPES(double)); template <> void bgemm(CUDABLAS_BGEMM_ARGTYPES(float)); template <> void bgemm>(CUDABLAS_BGEMM_ARGTYPES(c10::complex)); template <> void bgemm>(CUDABLAS_BGEMM_ARGTYPES(c10::complex)); template <> void bgemm(CUDABLAS_BGEMM_ARGTYPES(at::Half)); template <> void bgemm(CUDABLAS_BGEMM_ARGTYPES(at::BFloat16)); #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 template 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(CUDABLAS_TRSM_ARGTYPES(float)); template <> TORCH_CUDA_CU_API void trsm(CUDABLAS_TRSM_ARGTYPES(double)); template <> TORCH_CUDA_CU_API void trsm>(CUDABLAS_TRSM_ARGTYPES(c10::complex)); template <> TORCH_CUDA_CU_API void trsm>(CUDABLAS_TRSM_ARGTYPES(c10::complex)); #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 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(CUDABLAS_TRSM_BATCHED_ARGTYPES(float)); template <> TORCH_CUDA_CU_API void trsmBatched(CUDABLAS_TRSM_BATCHED_ARGTYPES(double)); template <> TORCH_CUDA_CU_API void trsmBatched>(CUDABLAS_TRSM_BATCHED_ARGTYPES(c10::complex)); template <> TORCH_CUDA_CU_API void trsmBatched>(CUDABLAS_TRSM_BATCHED_ARGTYPES(c10::complex)); /* 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 inline void gemv(CUDABLAS_GEMV_ARGTYPES(Dtype)) { AT_ERROR("at::cuda::blas::gemv: not implemented for ", typeid(Dtype).name()); } template <> void gemv(CUDABLAS_GEMV_ARGTYPES(double)); template <> void gemv(CUDABLAS_GEMV_ARGTYPES(float)); #if !defined(USE_ROCM) || (defined(USE_ROCM) && ROCM_VERSION >= 21000) template <> void gemv>(CUDABLAS_GEMV_ARGTYPES(c10::complex)); template <> void gemv>(CUDABLAS_GEMV_ARGTYPES(c10::complex)); #endif template <> void gemv(CUDABLAS_GEMV_ARGTYPES(at::Half)); template <> void gemv(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 inline void dot(CUDABLAS_DOT_ARGTYPES(Dtype)) { AT_ERROR("at::cuda::blas::dot: not implemented for ", typeid(Dtype).name()); } template <> void dot(CUDABLAS_DOT_ARGTYPES(double)); template <> void dot(CUDABLAS_DOT_ARGTYPES(float)); template <> void dot(CUDABLAS_DOT_ARGTYPES(at::Half)); template <> void dot(CUDABLAS_DOT_ARGTYPES(at::BFloat16)); template <> void dot>(CUDABLAS_DOT_ARGTYPES(c10::complex)); template <> void dot>(CUDABLAS_DOT_ARGTYPES(c10::complex)); template inline void vdot(CUDABLAS_DOT_ARGTYPES(Dtype)) { AT_ERROR("at::cuda::blas::vdot: not implemented for ", typeid(Dtype).name()); } template <> void vdot>(CUDABLAS_DOT_ARGTYPES(c10::complex)); template <> void vdot>(CUDABLAS_DOT_ARGTYPES(c10::complex)); // This guards blocks use of getrsBatched, geqrfBatched, getrfBatched on platforms other than cuda #ifdef CUDART_VERSION #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 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(CUDABLAS_GETRS_ARGTYPES(float)); template<> TORCH_CUDA_CU_API void getrsBatched(CUDABLAS_GETRS_ARGTYPES(double)); template<> TORCH_CUDA_CU_API void getrsBatched>(CUDABLAS_GETRS_ARGTYPES(c10::complex)); template<> TORCH_CUDA_CU_API void getrsBatched>(CUDABLAS_GETRS_ARGTYPES(c10::complex)); #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 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(CUDABLAS_GEQRF_BATCHED_ARGTYPES(float)); template <> TORCH_CUDA_CU_API void geqrfBatched(CUDABLAS_GEQRF_BATCHED_ARGTYPES(double)); template <> TORCH_CUDA_CU_API void geqrfBatched>( CUDABLAS_GEQRF_BATCHED_ARGTYPES(c10::complex)); template <> TORCH_CUDA_CU_API void geqrfBatched>( CUDABLAS_GEQRF_BATCHED_ARGTYPES(c10::complex)); #define CUDABLAS_GETRF_ARGTYPES(Dtype) \ int n, Dtype** dA_array, int ldda, int* ipiv_array, int* info_array, int batchsize template 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(CUDABLAS_GETRF_ARGTYPES(float)); template<> TORCH_CUDA_CU_API void getrfBatched(CUDABLAS_GETRF_ARGTYPES(double)); template<> TORCH_CUDA_CU_API void getrfBatched>(CUDABLAS_GETRF_ARGTYPES(c10::complex)); template<> TORCH_CUDA_CU_API void getrfBatched>(CUDABLAS_GETRF_ARGTYPES(c10::complex)); #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 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(CUDABLAS_GELS_BATCHED_ARGTYPES(double)); template<> TORCH_CUDA_CU_API void gelsBatched(CUDABLAS_GELS_BATCHED_ARGTYPES(float)); template<> TORCH_CUDA_CU_API void gelsBatched>(CUDABLAS_GELS_BATCHED_ARGTYPES(c10::complex)); template<> TORCH_CUDA_CU_API void gelsBatched>(CUDABLAS_GELS_BATCHED_ARGTYPES(c10::complex)); #endif // CUDART_VERSION } // namespace blas } // namespace cuda } // namespace at