hedaoyuan
9 years ago
parent
95a7bc018f
commit
e039410eb7
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/* Copyright (c) 2016 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 "ExpandConvTransLayer.h"
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#include "paddle/utils/Logging.h"
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#include "paddle/utils/Stat.h"
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/* The implementation of the convTransLayer is basically a swap of forward and
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* backward of the original convLayer.
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* The variable naming follows the convention of the convLayer.
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* */
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namespace paddle {
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// REGISTER_LAYER(exconvt, ExpandConvTransLayer);
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bool ExpandConvTransLayer::init(const LayerMap &layerMap,
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const ParameterMap ¶meterMap) {
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/* Initialize the basic convolutional parent class */
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ExpandConvBaseLayer::init(layerMap, parameterMap);
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return true;
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}
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void ExpandConvTransLayer::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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int batchSize = inputLayers_[0]->getOutputValue()->getHeight();
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resetOutput(batchSize, getOutputSize());
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MatrixPtr output = nullptr;
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for (size_t i = 0; i < inputLayers_.size(); ++i) {
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LayerPtr prevLayer = getPrev(i);
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output = prevLayer->getOutputValue();
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REGISTER_TIMER_INFO("shrinkFwd", getName().c_str());
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bpropActs(output, getOutputValue(), i);
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}
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/* add the bias-vector */
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if (biases_.get()) {
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if (sharedBiases_) {
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addSharedBias();
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} else {
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addUnsharedBias();
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}
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}
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/* activation */
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forwardActivation();
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}
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void ExpandConvTransLayer::backward(const UpdateCallback &callback) {
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backwardActivation();
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MatrixPtr imageGrad = getOutputGrad();
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if (biases_ && biases_->getWGrad()) {
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bpropBiases(imageGrad);
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/* Increasing the number of gradient */
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biases_->getParameterPtr()->incUpdate(callback);
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}
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for (size_t i = 0; i < inputLayers_.size(); ++i) {
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/* First, calculate the input layers error */
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for (size_t off = 0; off < imageGrad->getHeight(); off++) {
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if (getPrev(i)->getOutputGrad()) {
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expandFwdOnce(imageGrad, getPrev(i)->getOutputGrad(), i, off);
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}
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}
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if (weights_[i]->getWGrad()) {
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/* Then, calculate the W-gradient for the current layer */
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bpropWeights(imageGrad, getPrev(i)->getOutputValue(), i);
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/* Increasing the number of gradient */
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weights_[i]->getParameterPtr()->incUpdate(callback);
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}
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}
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}
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} // namespace paddle
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@ -1,44 +0,0 @@
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/* Copyright (c) 2016 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 <vector>
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#include "ExpandConvBaseLayer.h"
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#include "paddle/math/Matrix.h"
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namespace paddle {
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/**
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* @brief A subclass of convolution layer.
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* This layer expands input and use matrix multiplication to
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* calculate convolution transpose (deconv) operation.
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*
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* The config file api is img_conv_layer with flag trans=True.
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*/
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class ExpandConvTransLayer : public ExpandConvBaseLayer {
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public:
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explicit ExpandConvTransLayer(const LayerConfig& config)
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: ExpandConvBaseLayer(config) {}
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~ExpandConvTransLayer() {}
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bool init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) override;
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void forward(PassType passType) override;
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void backward(const UpdateCallback& callback) override;
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};
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} // namespace paddle
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