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add MKLDNNLRNLayer
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‎paddle/gserver/layers/MKLDNNLRNLayer.cpp

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/* 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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#include "MKLDNNLRNLayer.h"
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#include "paddle/utils/Logging.h"
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using namespace mkldnn; // NOLINT
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typedef memory::format format;
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namespace paddle {
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REGISTER_LAYER(mkldnn_lrn, MKLDNNLRNLayer);
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bool MKLDNNLRNLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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if (!MKLDNNLayer::init(layerMap, parameterMap)) {
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return false;
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}
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/* the size of inputs for norm-layer is 1 */
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CHECK_EQ(config_.inputs_size(), 1UL);
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const NormConfig& conf = config_.inputs(0).norm_conf();
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localSize_ = conf.size();
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alpha_ = conf.scale();
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beta_ = conf.pow();
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ic_ = conf.channels();
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oc_ = ic_;
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iw_ = conf.img_size();
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ow_ = conf.output_x();
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ih_ = conf.has_img_size_y() ? conf.img_size_y() : conf.img_size();
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oh_ = conf.has_output_y() ? conf.output_y() : conf.output_x();
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CHECK_EQ(iw_, ow_);
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CHECK_EQ(ih_, oh_);
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return true;
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}
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void MKLDNNLRNLayer::reshape(
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int& bs, int& ic, int& ih, int& iw, int& oc, int& oh, int& ow) {
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CHECK_EQ(inputLayers_.size(), 1UL);
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reshapeInput(bs, ih, iw);
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// ic_ and oc can not be changed
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CHECK_EQ((size_t)ic,
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inputLayers_[0]->getOutputValue()->getElementCnt() / bs / ih / iw)
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<< "Input channel can not be changed";
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oh = ih;
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ow = iw;
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reshapeOutput(oh, ow);
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resizeOutput(bs, oc * oh * ow);
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}
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void MKLDNNLRNLayer::resetFwd(std::vector<primitive>& pipeline,
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std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& out) {
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resetFwdBuffers(inputs[0], out);
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resetFwdPD(fwdPD_, inputs[0], out);
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resetFwdPipeline(pipeline, fwdPD_, inputs[0], out);
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}
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void MKLDNNLRNLayer::resetBwd(std::vector<primitive>& pipeline,
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std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& out) {
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std::shared_ptr<lrn_bwd::primitive_desc> pd;
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resetBwdBuffers(inputs[0], out);
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resetBwdPD(pd, inputs[0], out);
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resetBwdPipeline(pipeline, pd, inputs[0], out);
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}
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void MKLDNNLRNLayer::resetFwdBuffers(MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out) {
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resetInValue(in);
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CHECK(in);
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resetOutValue(out, in->getPrimitiveDesc());
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}
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void MKLDNNLRNLayer::resetFwdPD(std::shared_ptr<lrn_fwd::primitive_desc>& pd,
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MKLDNNMatrixPtr in,
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MKLDNNMatrixPtr out) {
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prop_kind pk = passType_ == PASS_TEST ? prop_kind::forward_scoring
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: prop_kind::forward_training;
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auto fwdDesc = lrn_fwd::desc(pk,
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algorithm::lrn_across_channels,
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in->getMemoryDesc(),
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localSize_,
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alpha_,
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beta_,
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1.0f);
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pd.reset(new lrn_fwd::primitive_desc(fwdDesc, engine_));
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// prepare workspace if necessary
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workspace_ =
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passType_ != PASS_TEST
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? std::make_shared<memory>(memory(pd->workspace_primitive_desc()))
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: nullptr;
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}
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void MKLDNNLRNLayer::resetFwdPipeline(
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std::vector<primitive>& pipeline,
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std::shared_ptr<lrn_fwd::primitive_desc>& pd,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out) {
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fwd_ = workspace_
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? std::make_shared<lrn_fwd>(lrn_fwd(*pd, *in, *workspace_, *out))
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: std::make_shared<lrn_fwd>(lrn_fwd(*pd, *in, *out));
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pipeline.push_back(*fwd_);
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}
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void MKLDNNLRNLayer::resetBwdBuffers(MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out) {
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CHECK(inVals_[0] && outVal_);
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resetOutGrad(out, outVal_->getPrimitiveDesc());
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resetInGrad(in, inVals_[0]->getPrimitiveDesc());
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}
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void MKLDNNLRNLayer::resetBwdPD(std::shared_ptr<lrn_bwd::primitive_desc>& pd,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out) {
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pd = nullptr;
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if (in == nullptr) {
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return;
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}
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CHECK(out);
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auto bwdDesc = lrn_bwd::desc(algorithm::lrn_across_channels,
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in->getMemoryDesc(),
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out->getMemoryDesc(),
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localSize_,
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alpha_,
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beta_,
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1.0f);
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pd.reset(new lrn_bwd::primitive_desc(bwdDesc, engine_, *fwdPD_));
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}
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void MKLDNNLRNLayer::resetBwdPipeline(
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std::vector<primitive>& pipeline,
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std::shared_ptr<lrn_bwd::primitive_desc>& pd,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out) {
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if (pd == nullptr) {
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return;
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}
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CHECK(inVals_[0]);
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CHECK(workspace_);
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bwdData_ = std::make_shared<lrn_bwd>(
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lrn_bwd(*pd, *inVals_[0], *out, *workspace_, *in));
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pipeline.push_back(*bwdData_);
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}
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} // namespace paddle

‎paddle/gserver/layers/MKLDNNLRNLayer.h

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/* 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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typedef mkldnn::lrn_forward lrn_fwd;
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typedef mkldnn::lrn_backward lrn_bwd;
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/**
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* @brief A subclass of MKLDNNLayer LRN(Local Response Norm) layer.
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*
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* The config file api is mkldnn_lrn
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*/
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class MKLDNNLRNLayer : public MKLDNNLayer {
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protected:
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// save forward primitive_desc, which can be used in backward
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std::shared_ptr<lrn_fwd::primitive_desc> fwdPD_;
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// according to https://github.com/01org/mkl-dnn/blob/master/tests/gtests/
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// test_lrn_backward.cpp, lrn need workspace for backward
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std::shared_ptr<mkldnn::memory> workspace_;
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int localSize_;
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float alpha_, beta_; // scale and pow in paddle
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public:
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explicit MKLDNNLRNLayer(const LayerConfig& config) : MKLDNNLayer(config) {}
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~MKLDNNLRNLayer() {}
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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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std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& out) override;
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void resetBwd(std::vector<mkldnn::primitive>& pipeline,
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std::vector<MKLDNNMatrixPtr>& inputs,
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MKLDNNMatrixPtr& out) override;
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protected:
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void resetFwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& out);
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void resetFwdPD(std::shared_ptr<lrn_fwd::primitive_desc>& pd,
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MKLDNNMatrixPtr in,
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MKLDNNMatrixPtr out);
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void resetFwdPipeline(std::vector<mkldnn::primitive>& pipeline,
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std::shared_ptr<lrn_fwd::primitive_desc>& pd,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out);
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void resetBwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& out);
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void resetBwdPD(std::shared_ptr<lrn_bwd::primitive_desc>& pd,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out);
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void resetBwdPipeline(std::vector<mkldnn::primitive>& pipeline,
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std::shared_ptr<lrn_bwd::primitive_desc>& pd,
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MKLDNNMatrixPtr& in,
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MKLDNNMatrixPtr& out);
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};
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} // namespace paddle

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