58 lines
1.8 KiB
58 lines
1.8 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/operators/math/blas.h"
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#include "paddle/fluid/operators/math/jit_kernel.h"
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DECLARE_int32(paddle_num_threads);
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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, typename T>
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inline void FCCompute(const BlasT<DeviceContext, T>& blas, const int M,
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const int N, const int K, const T* X, const T* W, T* Y,
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const T* B = NULL, bool relu = false) {
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blas.MatMul(M, N, K, X, W, Y);
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if (B == NULL) {
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return;
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}
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if (relu) {
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const auto& vaddrelu = jitkernel::KernelPool::Instance()
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.template Get<jitkernel::VAddReluKernel<T>>(N);
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for (int i = 0; i < M; i++) {
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T* dst = Y + i * N;
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vaddrelu->Compute(B, dst, dst, N);
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}
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} else {
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const auto& vadd = jitkernel::KernelPool::Instance()
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.template Get<jitkernel::VAddKernel<T>>(N);
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#ifdef PADDLE_WITH_MKLML
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#pragma omp parallel for if (FLAGS_paddle_num_threads > 1)
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#endif
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for (int i = 0; i < M; i++) {
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T* dst = Y + i * N;
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vadd->Compute(B, dst, dst, N);
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}
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}
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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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