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131 lines
4.1 KiB
131 lines
4.1 KiB
/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve.
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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 "MKLDNNLayer.h"
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#include "mkldnn.hpp"
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namespace paddle {
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/**
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* @brief A subclass of MKLDNNLayer Addto layer.
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*
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* The config file api is mkldnn_addto
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*/
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class MKLDNNAddtoLayer : public MKLDNNLayer {
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protected:
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std::vector<MKLDNNMatrixPtr> inVals_;
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std::vector<MKLDNNMatrixPtr> inGrads_;
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// layer size == ic * ih * iw == oc * oh *ow, and can not be changed
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size_t layerSize_;
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std::unique_ptr<Weight> biases_;
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// buffers for adding bias
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std::vector<MKLDNNMatrixPtr> vals_;
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std::vector<MKLDNNMatrixPtr> grads_;
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// primitives for adding bias
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std::vector<std::shared_ptr<mkldnn::primitive>> fwdBias_;
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std::shared_ptr<mkldnn::primitive> bwdBias_;
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public:
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explicit MKLDNNAddtoLayer(const LayerConfig& config) : MKLDNNLayer(config) {}
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~MKLDNNAddtoLayer() {}
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bool init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) override;
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void reshape(
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int& bs, int& ic, int& ih, int& iw, int oc, int& oh, int& ow) override;
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void resetFwd(std::vector<mkldnn::primitive>& pipeline,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& wgt,
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MKLDNNMatrixPtr& bias,
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MKLDNNMatrixPtr& out) override;
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void resetBwd(std::vector<mkldnn::primitive>& pipeline,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& wgt,
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MKLDNNMatrixPtr& bias,
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MKLDNNMatrixPtr& out) override;
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void updateWeights(const UpdateCallback& callback) override;
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void printValueFormat() override {
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for (size_t i = 0; i < inVals_.size(); ++i) {
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VLOG(MKLDNN_FMTS) << i << " input: " << inVals_[i]->getFormat() << " >>>";
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}
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if (outVal_) {
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VLOG(MKLDNN_FMTS) << outVal_->getFormat() << " >>> ";
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}
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if (extOutVal_) {
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VLOG(MKLDNN_FMTS) << extOutVal_->getFormat();
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}
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}
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void printGradFormat() override {
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if (extOutGrad_) {
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VLOG(MKLDNN_FMTS) << extOutGrad_->getFormat();
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}
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if (outGrad_) {
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VLOG(MKLDNN_FMTS) << outGrad_->getFormat() << " <<< ";
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}
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for (size_t i = 0; i < inGrads_.size(); ++i) {
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VLOG(MKLDNN_FMTS) << i << " input: " << inGrads_[i]->getFormat() << "<<<";
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}
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}
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protected:
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/**
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* Forward functions: reset buffers(inputs, output, bias),
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* reset primitive descriptor,
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* reset pipeline.
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*/
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void resetFwdBuffers(std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& bias,
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MKLDNNMatrixPtr& out);
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void resetFwdPD(std::shared_ptr<mkldnn::sum::primitive_desc>& pd,
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std::shared_ptr<mkldnn::sum::primitive_desc>& biasPD,
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std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr bias,
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MKLDNNMatrixPtr out);
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void resetFwdPipeline(std::vector<mkldnn::primitive>& pipeline,
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std::shared_ptr<mkldnn::sum::primitive_desc>& pd,
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std::shared_ptr<mkldnn::sum::primitive_desc>& biasPD,
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std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& bias,
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MKLDNNMatrixPtr& out);
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/**
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* Backward functions: reset buffers(inputs, output, bias)
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*/
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void resetBwdBuffers(std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& bias,
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MKLDNNMatrixPtr& out);
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/**
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* prepare for bias
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*/
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void prepareBias(MKLDNNMatrixPtr& bias,
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const MatrixPtr& biasMat,
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const MKLDNNMatrixPtr& out,
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std::vector<MKLDNNMatrixPtr>& outs);
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};
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} // namespace paddle
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