提交 54205c99 编写于 作者: T tensor-tang

add MKLDNNLRNLayer

上级 4786ad14
/* Copyright (c) 2017 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. */
#include "MKLDNNLRNLayer.h"
#include "paddle/utils/Logging.h"
using namespace mkldnn; // NOLINT
typedef memory::format format;
namespace paddle {
REGISTER_LAYER(mkldnn_lrn, MKLDNNLRNLayer);
bool MKLDNNLRNLayer::init(const LayerMap& layerMap,
const ParameterMap& parameterMap) {
if (!MKLDNNLayer::init(layerMap, parameterMap)) {
return false;
}
/* the size of inputs for norm-layer is 1 */
CHECK_EQ(config_.inputs_size(), 1UL);
const NormConfig& conf = config_.inputs(0).norm_conf();
localSize_ = conf.size();
alpha_ = conf.scale();
beta_ = conf.pow();
ic_ = conf.channels();
oc_ = ic_;
iw_ = conf.img_size();
ow_ = conf.output_x();
ih_ = conf.has_img_size_y() ? conf.img_size_y() : conf.img_size();
oh_ = conf.has_output_y() ? conf.output_y() : conf.output_x();
CHECK_EQ(iw_, ow_);
CHECK_EQ(ih_, oh_);
return true;
}
void MKLDNNLRNLayer::reshape(
int& bs, int& ic, int& ih, int& iw, int& oc, int& oh, int& ow) {
CHECK_EQ(inputLayers_.size(), 1UL);
reshapeInput(bs, ih, iw);
// ic_ and oc can not be changed
CHECK_EQ((size_t)ic,
inputLayers_[0]->getOutputValue()->getElementCnt() / bs / ih / iw)
<< "Input channel can not be changed";
oh = ih;
ow = iw;
reshapeOutput(oh, ow);
resizeOutput(bs, oc * oh * ow);
}
void MKLDNNLRNLayer::resetFwd(std::vector<primitive>& pipeline,
std::vector<MKLDNNMatrixPtr>& inputs,
MKLDNNMatrixPtr& out) {
resetFwdBuffers(inputs[0], out);
resetFwdPD(fwdPD_, inputs[0], out);
resetFwdPipeline(pipeline, fwdPD_, inputs[0], out);
}
void MKLDNNLRNLayer::resetBwd(std::vector<primitive>& pipeline,
std::vector<MKLDNNMatrixPtr>& inputs,
MKLDNNMatrixPtr& out) {
std::shared_ptr<lrn_bwd::primitive_desc> pd;
resetBwdBuffers(inputs[0], out);
resetBwdPD(pd, inputs[0], out);
resetBwdPipeline(pipeline, pd, inputs[0], out);
}
void MKLDNNLRNLayer::resetFwdBuffers(MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out) {
resetInValue(in);
CHECK(in);
resetOutValue(out, in->getPrimitiveDesc());
}
void MKLDNNLRNLayer::resetFwdPD(std::shared_ptr<lrn_fwd::primitive_desc>& pd,
MKLDNNMatrixPtr in,
MKLDNNMatrixPtr out) {
prop_kind pk = passType_ == PASS_TEST ? prop_kind::forward_scoring
: prop_kind::forward_training;
auto fwdDesc = lrn_fwd::desc(pk,
algorithm::lrn_across_channels,
in->getMemoryDesc(),
localSize_,
alpha_,
beta_,
1.0f);
pd.reset(new lrn_fwd::primitive_desc(fwdDesc, engine_));
// prepare workspace if necessary
workspace_ =
passType_ != PASS_TEST
? std::make_shared<memory>(memory(pd->workspace_primitive_desc()))
: nullptr;
}
void MKLDNNLRNLayer::resetFwdPipeline(
std::vector<primitive>& pipeline,
std::shared_ptr<lrn_fwd::primitive_desc>& pd,
MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out) {
fwd_ = workspace_
? std::make_shared<lrn_fwd>(lrn_fwd(*pd, *in, *workspace_, *out))
: std::make_shared<lrn_fwd>(lrn_fwd(*pd, *in, *out));
pipeline.push_back(*fwd_);
}
void MKLDNNLRNLayer::resetBwdBuffers(MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out) {
CHECK(inVals_[0] && outVal_);
resetOutGrad(out, outVal_->getPrimitiveDesc());
resetInGrad(in, inVals_[0]->getPrimitiveDesc());
}
void MKLDNNLRNLayer::resetBwdPD(std::shared_ptr<lrn_bwd::primitive_desc>& pd,
MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out) {
pd = nullptr;
if (in == nullptr) {
return;
}
CHECK(out);
auto bwdDesc = lrn_bwd::desc(algorithm::lrn_across_channels,
in->getMemoryDesc(),
out->getMemoryDesc(),
localSize_,
alpha_,
beta_,
1.0f);
pd.reset(new lrn_bwd::primitive_desc(bwdDesc, engine_, *fwdPD_));
}
void MKLDNNLRNLayer::resetBwdPipeline(
std::vector<primitive>& pipeline,
std::shared_ptr<lrn_bwd::primitive_desc>& pd,
MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out) {
if (pd == nullptr) {
return;
}
CHECK(inVals_[0]);
CHECK(workspace_);
bwdData_ = std::make_shared<lrn_bwd>(
lrn_bwd(*pd, *inVals_[0], *out, *workspace_, *in));
pipeline.push_back(*bwdData_);
}
} // namespace paddle
/* Copyright (c) 2017 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. */
#pragma once
#include "MKLDNNLayer.h"
#include "mkldnn.hpp"
namespace paddle {
typedef mkldnn::lrn_forward lrn_fwd;
typedef mkldnn::lrn_backward lrn_bwd;
/**
* @brief A subclass of MKLDNNLayer LRN(Local Response Norm) layer.
*
* The config file api is mkldnn_lrn
*/
class MKLDNNLRNLayer : public MKLDNNLayer {
protected:
// save forward primitive_desc, which can be used in backward
std::shared_ptr<lrn_fwd::primitive_desc> fwdPD_;
// according to https://github.com/01org/mkl-dnn/blob/master/tests/gtests/
// test_lrn_backward.cpp, lrn need workspace for backward
std::shared_ptr<mkldnn::memory> workspace_;
int localSize_;
float alpha_, beta_; // scale and pow in paddle
public:
explicit MKLDNNLRNLayer(const LayerConfig& config) : MKLDNNLayer(config) {}
~MKLDNNLRNLayer() {}
bool init(const LayerMap& layerMap,
const ParameterMap& parameterMap) override;
void reshape(
int& bs, int& ic, int& ih, int& iw, int& oc, int& oh, int& ow) override;
void resetFwd(std::vector<mkldnn::primitive>& pipeline,
std::vector<MKLDNNMatrixPtr>& inputs,
MKLDNNMatrixPtr& out) override;
void resetBwd(std::vector<mkldnn::primitive>& pipeline,
std::vector<MKLDNNMatrixPtr>& inputs,
MKLDNNMatrixPtr& out) override;
protected:
void resetFwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& out);
void resetFwdPD(std::shared_ptr<lrn_fwd::primitive_desc>& pd,
MKLDNNMatrixPtr in,
MKLDNNMatrixPtr out);
void resetFwdPipeline(std::vector<mkldnn::primitive>& pipeline,
std::shared_ptr<lrn_fwd::primitive_desc>& pd,
MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out);
void resetBwdBuffers(MKLDNNMatrixPtr& in, MKLDNNMatrixPtr& out);
void resetBwdPD(std::shared_ptr<lrn_bwd::primitive_desc>& pd,
MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out);
void resetBwdPipeline(std::vector<mkldnn::primitive>& pipeline,
std::shared_ptr<lrn_bwd::primitive_desc>& pd,
MKLDNNMatrixPtr& in,
MKLDNNMatrixPtr& out);
};
} // namespace paddle
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