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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 "MaxPoolWithMaskLayer.h"
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#include "paddle/utils/Logging.h"
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#include "paddle/utils/Stat.h"
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namespace paddle {
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bool MaxPoolWithMaskLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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PoolLayer::init(layerMap, parameterMap);
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setOutput("mask", &mask_);
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return true;
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}
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size_t MaxPoolWithMaskLayer::getSize() {
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CHECK_EQ(inputLayers_.size(), 1UL);
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size_t layerSize = 0;
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outputY_ = outputSize(imgSizeY_,
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sizeY_,
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confPaddingY_,
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strideY_,
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/* caffeMode */ false);
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outputX_ = outputSize(imgSize_,
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sizeX_,
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confPadding_,
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stride_,
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/* caffeMode */ false);
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layerSize = outputX_ * outputY_ * channels_;
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getOutput().setFrameHeight(outputY_);
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getOutput().setFrameWidth(outputX_);
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return layerSize;
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}
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void MaxPoolWithMaskLayer::forward(PassType passType) {
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size_t size = getSize();
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MatrixPtr inputV = inputLayers_[0]->getOutputValue();
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int batchSize = inputV->getHeight();
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resetOutput(batchSize, size);
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MatrixPtr outV = getOutputValue();
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CHECK_EQ(size, outV->getWidth());
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resetSpecifyOutput(mask_,
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batchSize,
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size,
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/* isValueClean */ false,
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/* isGradClean */ true);
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MatrixPtr maskV = mask_.value;
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outV->maxPoolForward(*inputV,
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imgSizeY_,
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imgSize_,
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channels_,
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sizeX_,
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sizeY_,
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strideY_,
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stride_,
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outputY_,
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outputX_,
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confPaddingY_,
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confPadding_,
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maskV);
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}
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void MaxPoolWithMaskLayer::backward(const UpdateCallback& callback) {
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(void)callback;
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if (NULL == getInputGrad(0)) {
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return;
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}
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MatrixPtr outGrad = getOutputGrad();
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MatrixPtr inputV = inputLayers_[0]->getOutputValue();
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MatrixPtr outV = getOutputValue();
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MatrixPtr inputGrad = inputLayers_[0]->getOutputGrad();
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inputGrad->maxPoolBackward(*inputV,
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imgSizeY_,
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imgSize_,
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*outGrad,
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*outV,
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sizeX_,
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sizeY_,
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strideY_,
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stride_,
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outputY_,
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outputX_,
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1,
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1,
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confPaddingY_,
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confPadding_);
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}
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} // namespace paddle
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@ -0,0 +1,40 @@
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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 "PoolLayer.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 Basic parent layer of different kinds of pooling
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*/
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class MaxPoolWithMaskLayer : public PoolLayer {
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protected:
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Argument mask_;
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public:
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explicit MaxPoolWithMaskLayer(const LayerConfig& config)
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: PoolLayer(config) {}
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size_t getSize();
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void forward(PassType passType) override;
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void backward(const UpdateCallback& callback = nullptr) override;
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bool init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) override;
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};
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} // namespace paddle
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