Merge pull request #10371 from reyoung/refine_code
Polish MatMul, clean copy & paste codesimplify_fluid_api_recognize_digit
Yu Yang
7 years ago
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GitHub
commit
0285a2b95d
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/operators/math/blas.h"
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namespace paddle {
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namespace operators {
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namespace math {
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// Do nothing. Blas is a header only library.
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} // namespace math
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} // namespace operators
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} // namespace paddle
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/tensor.h"
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#ifdef PADDLE_WITH_MKLML
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#include <mkl_cblas.h>
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#include <mkl_lapacke.h>
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#include <mkl_vml_functions.h>
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#endif
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#ifdef PADDLE_USE_OPENBLAS
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#include <cblas.h>
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#include <lapacke.h>
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#endif
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#ifndef LAPACK_FOUND
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extern "C" {
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#include <cblas.h> // NOLINT
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int LAPACKE_sgetrf(int matrix_layout, int m, int n, float* a, int lda,
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int* ipiv);
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int LAPACKE_dgetrf(int matrix_layout, int m, int n, double* a, int lda,
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int* ipiv);
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int LAPACKE_sgetri(int matrix_layout, int n, float* a, int lda,
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const int* ipiv);
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int LAPACKE_dgetri(int matrix_layout, int n, double* a, int lda,
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const int* ipiv);
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}
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#endif
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namespace paddle {
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namespace operators {
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namespace math {
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template <typename DeviceContext>
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class Blas {
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public:
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explicit Blas(const DeviceContext& context) : context_(context) {}
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template <typename T>
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void GEMM(CBLAS_TRANSPOSE transA, CBLAS_TRANSPOSE transB, int M, int N, int K,
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T alpha, const T* A, const T* B, T beta, T* C) const;
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template <typename T>
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void GEMM(bool transA, bool transB, int M, int N, int K, T alpha, const T* A,
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int lda, const T* B, int ldb, T beta, T* C, int ldc) const;
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template <typename T>
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void MatMul(const framework::Tensor& mat_a, bool trans_a,
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const framework::Tensor& mat_b, bool trans_b, T alpha,
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framework::Tensor* mat_out, T beta) const;
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template <typename T>
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void MatMul(const framework::Tensor& mat_a, bool trans_a,
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const framework::Tensor& mat_b, bool trans_b,
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framework::Tensor* mat_out) const {
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MatMul(mat_a, trans_a, mat_b, trans_b, static_cast<T>(1.0), mat_out,
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static_cast<T>(0.0));
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}
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template <typename T>
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void MatMul(const framework::Tensor& mat_a, const framework::Tensor& mat_b,
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framework::Tensor* mat_out) const {
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this->template MatMul<T>(mat_a, false, mat_b, false, mat_out);
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}
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template <typename T>
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void AXPY(int n, T alpha, const T* x, T* y) const;
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template <typename T>
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void GEMV(bool trans_a, int M, int N, T alpha, const T* A, const T* B, T beta,
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T* C) const;
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template <typename T>
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void BatchedGEMM(CBLAS_TRANSPOSE transA, CBLAS_TRANSPOSE transB, int M, int N,
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int K, T alpha, const T* A, const T* B, T beta, T* C,
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int batchCount, int64_t strideA, int64_t strideB) const;
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private:
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const DeviceContext& context_;
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};
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template <typename DeviceContext, typename T>
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class BlasT : private Blas<DeviceContext> {
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public:
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using Blas<DeviceContext>::Blas;
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template <typename... ARGS>
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void GEMM(ARGS... args) const {
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Base()->template GEMM<T>(args...);
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}
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template <typename... ARGS>
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void MatMul(ARGS... args) const {
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Base()->template MatMul<T>(args...);
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}
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template <typename... ARGS>
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void AXPY(ARGS... args) const {
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Base()->template AXPY<T>(args...);
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}
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template <typename... ARGS>
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void GEMV(ARGS... args) const {
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Base()->template GEMV<T>(args...);
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}
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template <typename... ARGS>
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void BatchedGEMM(ARGS... args) const {
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Base()->template BatchedGEMM<T>(args...);
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}
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private:
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const Blas<DeviceContext>* Base() const {
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return static_cast<const Blas<DeviceContext>*>(this);
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}
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};
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template <typename DeviceContext, typename T>
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inline BlasT<DeviceContext, T> GetBlas(
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const framework::ExecutionContext& exe_ctx) {
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return BlasT<DeviceContext, T>(
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exe_ctx.template device_context<DeviceContext>());
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}
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template <typename DeviceContext, typename T>
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inline BlasT<DeviceContext, T> GetBlas(const DeviceContext& dev_ctx) {
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return BlasT<DeviceContext, T>(dev_ctx);
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}
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} // namespace math
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} // namespace operators
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} // namespace paddle
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#include "paddle/fluid/operators/math/blas_impl.h"
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#ifdef PADDLE_WITH_CUDA
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#include "paddle/fluid/operators/math/blas_impl.cu.h"
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#endif
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