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106 lines
3.6 KiB
106 lines
3.6 KiB
/* 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 "ExpandConvBaseLayer.h"
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#include "paddle/utils/Logging.h"
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namespace paddle {
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bool ExpandConvBaseLayer::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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ConvBaseLayer::init(layerMap, parameterMap);
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for (auto &inputConfig : config_.inputs()) {
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const ConvConfig &conf = inputConfig.conv_conf();
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/* Consistent caffe mode for multiple input */
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caffeMode_ = conf.caffe_mode();
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}
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getOutputSize();
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return true;
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}
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size_t ExpandConvBaseLayer::getOutputSize() {
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CHECK_NE(inputLayers_.size(), 0UL);
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size_t layerSize = ConvBaseLayer::calOutputSize();
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return layerSize;
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}
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void ExpandConvBaseLayer::addSharedBias() {
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size_t mapW = getOutputSize() / numFilters_;
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size_t mapH = getOutputValue()->getElementCnt() / mapW;
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MatrixPtr out =
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Matrix::create(getOutputValue()->getData(), mapH, mapW, false, useGpu_);
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Matrix::resizeOrCreate(transOutValue_, mapW, mapH, false, useGpu_);
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out->transpose(transOutValue_, false); // false means no memory allocation
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transOutValue_->reshape(transOutValue_->getElementCnt() / numFilters_,
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numFilters_);
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MatrixPtr bias = Matrix::create(biases_->getW()->getData(),
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1,
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biases_->getW()->getElementCnt(),
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false,
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useGpu_);
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transOutValue_->addBias(*bias, 1.0f);
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transOutValue_->reshape(mapW, mapH);
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transOutValue_->transpose(out, false); // false means no memory allocation
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out->clear();
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bias->clear();
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}
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void ExpandConvBaseLayer::addUnsharedBias() {
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MatrixPtr outValue = getOutputValue();
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MatrixPtr bias = Matrix::create(biases_->getW()->getData(),
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1,
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biases_->getW()->getElementCnt(),
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false,
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useGpu_);
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outValue->addBias(*bias, 1.0f);
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}
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void ExpandConvBaseLayer::bpropSharedBias(MatrixPtr biases, MatrixPtr v) {
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size_t mapW = getOutputSize() / numFilters_;
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size_t mapH = v->getElementCnt() / mapW;
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MatrixPtr vTmp = Matrix::create(v->getData(), mapH, mapW, false, useGpu_);
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Matrix::resizeOrCreate(transOutValue_, mapW, mapH, false, useGpu_);
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vTmp->transpose(transOutValue_, false); // false means no memory allocation
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transOutValue_->reshape(transOutValue_->getElementCnt() / numFilters_,
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numFilters_);
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biases->collectBias(*transOutValue_, 1.0f);
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}
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void ExpandConvBaseLayer::bpropBiases(MatrixPtr v) {
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MatrixPtr biases = Matrix::create(biases_->getWGrad()->getData(),
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1,
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biases_->getWGrad()->getElementCnt(),
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false,
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useGpu_);
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if (sharedBiases_) {
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bpropSharedBias(biases, v);
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} else {
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biases->collectBias(*v, 1.0f);
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}
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biases->clear();
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}
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} // namespace paddle
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