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Merge pull request #3549 from hedaoyuan/convolution
Use EigenBlasGemm improve convolution computing performance in ARMv7 environment.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,91 @@ | ||
| /* 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. */ | ||
|
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| #include <glog/logging.h> | ||
| #include "unsupported/Eigen/CXX11/Tensor" | ||
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| namespace paddle { | ||
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| template <class T> | ||
| struct EigenBlasGemm { | ||
| typedef Eigen::TensorMap<Eigen::Tensor<T, 2, Eigen::RowMajor, int>, | ||
| Eigen::Aligned> | ||
| Matrix; | ||
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| static void compute(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) { | ||
| Eigen::array<int, 2> sizeA; | ||
| if (transA) { | ||
| sizeA[0] = K; | ||
| sizeA[1] = M; | ||
| CHECK_EQ(M, lda); | ||
| } else { | ||
| sizeA[0] = M; | ||
| sizeA[1] = K; | ||
| CHECK_EQ(K, lda); | ||
| } | ||
| Eigen::array<int, 2> sizeB; | ||
| if (transB) { | ||
| sizeB[0] = N; | ||
| sizeB[1] = K; | ||
| CHECK_EQ(K, ldb); | ||
| } else { | ||
| sizeB[0] = K; | ||
| sizeB[1] = N; | ||
| CHECK_EQ(N, ldb); | ||
| } | ||
| Eigen::array<int, 2> sizeC; | ||
| sizeC[0] = M; | ||
| sizeC[1] = N; | ||
| CHECK_EQ(N, ldc); | ||
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| const Matrix a(const_cast<T*>(A), sizeA); | ||
| const Matrix b(const_cast<T*>(B), sizeB); | ||
| Matrix c(C, sizeC); | ||
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| typedef typename Eigen::Tensor<T, 2>::DimensionPair DimPair; | ||
| Eigen::array<DimPair, 1> dims; | ||
| dims[0] = DimPair(1, 0); | ||
| dims[0].first = transA ? 0 : 1; | ||
| dims[0].second = transB ? 1 : 0; | ||
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| Eigen::DefaultDevice device; | ||
| if (alpha == T(1) && beta == T(0)) { | ||
| c.device(device) = a.contract(b, dims); | ||
| } else if (alpha == T(1) && beta == T(1)) { | ||
| c.device(device) += a.contract(b, dims); | ||
| } else { | ||
| c.device(device) = alpha * a.contract(b, dims) + beta * c; | ||
| } | ||
| } | ||
| }; | ||
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| #ifdef PADDLE_TYPE_DOUBLE | ||
| template class EigenBlasGemm<double>; | ||
| #else | ||
| template class EigenBlasGemm<float>; | ||
| #endif | ||
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| } // namespace paddle |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,90 @@ | ||
| /* 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. */ | ||
|
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| #include "GemmFunctor.h" | ||
| #include "paddle/math/MathFunctions.h" | ||
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| namespace paddle { | ||
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| template <class T> | ||
| struct BlasGemm<DEVICE_TYPE_CPU, T> { | ||
| static void compute(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) { | ||
| #ifdef PADDLE_USE_EIGEN_FOR_BLAS | ||
| EigenBlasGemm<T>::compute( | ||
| transA, transB, M, N, K, alpha, A, lda, B, ldb, beta, C, ldc); | ||
| #else | ||
| gemm<T>(transA == false ? CblasNoTrans : CblasTrans, | ||
| transB == false ? CblasNoTrans : CblasTrans, | ||
| M, | ||
| N, | ||
| K, | ||
| alpha, | ||
| A, | ||
| lda, | ||
| B, | ||
| ldb, | ||
| beta, | ||
| C, | ||
| ldc); | ||
| #endif | ||
| } | ||
| }; | ||
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| template <class T> | ||
| struct BlasGemm<DEVICE_TYPE_GPU, T> { | ||
| static void compute(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) { | ||
| hl_matrix_mul((T*)A, | ||
| transA == false ? HPPL_OP_N : HPPL_OP_T, | ||
| (T*)B, | ||
| transB == false ? HPPL_OP_N : HPPL_OP_T, | ||
| C, | ||
| M, | ||
| N, | ||
| K, | ||
| alpha, | ||
| beta, | ||
| lda, | ||
| ldb, | ||
| ldc); | ||
| } | ||
| }; | ||
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| template class BlasGemm<DEVICE_TYPE_CPU, real>; | ||
| template class BlasGemm<DEVICE_TYPE_GPU, real>; | ||
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| } // namespace paddle |
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