/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #pragma once #ifdef PADDLE_USE_MKLML #include #include #include #endif #ifdef PADDLE_USE_MKL #include #include #endif #ifdef PADDLE_USE_ATLAS extern "C" { #include #include } #endif #ifdef PADDLE_USE_OPENBLAS #include #include #endif #ifndef LAPACK_FOUND extern "C" { #include int LAPACKE_sgetrf(int matrix_layout, int m, int n, float* a, int lda, int* ipiv); int LAPACKE_dgetrf(int matrix_layout, int m, int n, double* a, int lda, int* ipiv); int LAPACKE_sgetri(int matrix_layout, int n, float* a, int lda, const int* ipiv); int LAPACKE_dgetri(int matrix_layout, int n, double* a, int lda, const int* ipiv); } #endif #include #include "paddle/framework/eigen.h" #include "paddle/framework/tensor.h" #include "paddle/platform/device_context.h" #include "paddle/platform/enforce.h" namespace paddle { namespace operators { namespace math { // Support continuous memory now // If transA = N, and transB = N // Then matrixA: M * K, matrixB: K * N, matrixC : M * N // For more detailed info, please refer to // http://www.netlib.org/lapack/explore-html/d4/de2/sgemm_8f.html template void gemm(const platform::DeviceContext& context, const CBLAS_TRANSPOSE transA, const CBLAS_TRANSPOSE transB, const int M, const int N, const int K, const T alpha, const T* A, const T* B, const T beta, T* C); // gemm wrapper with stride args for matrix uncontinuous in memory template void gemm(const platform::DeviceContext& context, const bool transA, const bool transB, const int M, const int N, const int K, const T alpha, const T* A, const int lda, const T* B, const int ldb, const T beta, T* C, const int ldc); // matrix multiply with continuous memory template void matmul(const platform::DeviceContext& context, const framework::Tensor& matrix_a, bool trans_a, const framework::Tensor& matrix_b, bool trans_b, T alpha, framework::Tensor* matrix_out, T beta); // Batched gemm template void batched_gemm(const platform::DeviceContext& context, const CBLAS_TRANSPOSE transA, const CBLAS_TRANSPOSE transB, const int M, const int N, const int K, const T alpha, const T* A, const T* B, const T beta, T* C, const int batchCount, const int strideA, const int strideB); template void gemv(const platform::DeviceContext& context, const bool trans_a, const int M, const int N, const T alpha, const T* A, const T* B, const T beta, T* C); template struct SetConstant { void operator()(const platform::DeviceContext& context, framework::Tensor* tensor, T num) { auto t = framework::EigenVector::Flatten(*tensor); t.device(*context.GetEigenDevice()) = t.constant(static_cast(num)); } }; template void set_constant_with_place(const platform::DeviceContext& context, framework::Tensor* tensor, float value); void set_constant(const platform::DeviceContext& context, framework::Tensor* tensor, float value); } // namespace math } // namespace operators } // namespace paddle