Haonan
8 years ago
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GitHub
commit
b9dfe8e7c8
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/* 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 "RotateLayer.h"
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namespace paddle {
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REGISTER_LAYER(rotate, RotateLayer);
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bool RotateLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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Layer::init(layerMap, parameterMap);
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CHECK_EQ(inputLayers_.size(), 1UL);
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height_ = config_.height();
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width_ = config_.width();
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CHECK_GT(height_, 0);
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CHECK_GT(width_, 0);
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return true;
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}
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void RotateLayer::forward(PassType passType) {
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Layer::forward(passType);
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MatrixPtr input = getInputValue(0);
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batchSize_ = input->getHeight();
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size_ = input->getWidth();
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CHECK_GE(size_, height_ * width_);
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CHECK_EQ(size_ % (height_ * width_), 0)
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<< "total size_ is not dividable by (height_ * width_), i.e., "
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<< "channel number should be an integer";
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channels_ = size_ / (height_ * width_);
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resizeOutput(batchSize_, size_);
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MatrixPtr outV = getOutputValue();
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for (int b = 0; b < batchSize_; b++) { // for each input feat map
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for (int c = 0; c < channels_; c++) { // for each feat channel
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MatrixPtr inputSample =
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Matrix::create(input->getData() + b * size_ + c * height_ * width_,
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height_,
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width_,
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false,
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useGpu_);
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MatrixPtr outputSample =
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Matrix::create(outV->getData() + b * size_ + c * height_ * width_,
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width_,
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height_,
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false,
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useGpu_);
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inputSample->rotate(outputSample, false, true /* clock-wise */);
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}
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}
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if (getInputGrad(0)) {
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zeroGrad();
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}
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}
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void RotateLayer::backward(const UpdateCallback& callback) {
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(void)callback;
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MatrixPtr outputGrad = getOutputGrad();
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if (outputGrad == NULL) {
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return;
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}
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// the grad should be rotated in the reverse direction
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MatrixPtr preGrad = getInputGrad(0);
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for (int b = 0; b < batchSize_; b++) { // for each input feat map
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for (int c = 0; c < channels_; c++) { // for each feat channel
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MatrixPtr inputSampleGrad =
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Matrix::create(preGrad->getData() + b * size_ + c * height_ * width_,
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height_,
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width_,
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false,
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useGpu_);
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MatrixPtr outputSampleGrad = Matrix::create(
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outputGrad->getData() + b * size_ + c * height_ * width_,
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width_,
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height_,
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false,
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useGpu_);
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MatrixPtr tmpGrad = nullptr;
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outputSampleGrad->rotate(tmpGrad, true, false /* anti clock-wise */);
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inputSampleGrad->add(*tmpGrad);
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}
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}
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}
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} // namespace paddle
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@ -0,0 +1,51 @@
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/* 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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#pragma once
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#include "Layer.h"
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#include "paddle/math/Matrix.h"
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namespace paddle {
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/**
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* A layer for rotating a multi-channel feature map (M x N x C) in the spatial
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* domain
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* The rotation is 90 degrees in clock-wise for each channel
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* \f[
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* y(j,i,:) = x(M-i-1,j,:)
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* \f]
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* where \f$x\f$ is (M x N x C) input, and \f$y\f$ is (N x M x C) output.
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*
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* The config file api is rotate_layer
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*
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*/
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class RotateLayer : public Layer {
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public:
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explicit RotateLayer(const LayerConfig& config) : Layer(config) {}
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bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
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void forward(PassType passType);
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void backward(const UpdateCallback& callback = nullptr);
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private:
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int batchSize_;
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int size_;
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int height_;
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int width_;
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int channels_;
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};
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} // namespace paddle
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