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89 lines
2.7 KiB
89 lines
2.7 KiB
/* Copyright (c) 2016 Baidu, Inc. 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 "paddle/utils/Logging.h"
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#include "paddle/utils/Stat.h"
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#include "NormProjectionLayer.h"
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namespace paddle {
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size_t CMRProjectionNormLayer::getSize() {
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CHECK_EQ(inputLayers_.size(), 1UL);
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size_t layerSize = 0;
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imgSizeH_ = inputLayers_[0]->getOutput().getFrameHeight();
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imgSizeW_ = inputLayers_[0]->getOutput().getFrameWidth();
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if (imgSizeH_ == 0) {
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imgSizeH_ = imgSize_;
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}
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if (imgSizeW_ == 0) {
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imgSizeW_ = imgSize_;
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}
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outputH_ = imgSizeH_;
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outputW_ = imgSizeW_;
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layerSize = outputH_ * outputW_ * channels_;
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getOutput().setFrameHeight(outputH_);
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getOutput().setFrameWidth(outputW_);
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return layerSize;
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}
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bool CMRProjectionNormLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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/* Initialize the basic parent class */
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ResponseNormLayer::init(layerMap, parameterMap);
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/* the size of inputs for norm-layer is 1 */
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CHECK_EQ(config_.inputs_size(), 1);
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return true;
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}
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void CMRProjectionNormLayer::forward(PassType passType) {
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Layer::forward(passType);
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/* malloc memory for the output_ if necessary */
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/* note: one sample correspond to one row */
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MatrixPtr input = inputLayers_[0]->getOutputValue();
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int batchSize = input->getHeight();
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int size = getSize();
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resetOutput(batchSize, size);
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MatrixPtr outV = getOutputValue();
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Matrix::resizeOrCreate(denoms_, batchSize, size, /* trans */ false, useGpu_);
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denoms_->zeroMem();
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outV->crossMapNormalFwd(*input, imgSizeH_, imgSizeW_, *denoms_, channels_,
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size_, scale_, pow_);
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}
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void CMRProjectionNormLayer::backward(const UpdateCallback& callback) {
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(void)callback;
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if (NULL == inputLayers_[0]->getOutputGrad()) {
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return;
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}
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/* Do derivation */
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MatrixPtr preOutGrad = inputLayers_[0]->getOutputGrad();
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MatrixPtr localGrad = getOutputGrad();
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MatrixPtr localOutV = getOutputValue();
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MatrixPtr preOutV = inputLayers_[0]->getOutputValue();
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preOutGrad->crossMapNormalBwd(*localGrad, *denoms_, *preOutV, *localOutV,
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channels_, imgSizeH_, imgSizeW_, size_, scale_,
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pow_);
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}
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} // namespace paddle
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