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79 lines
2.6 KiB
79 lines
2.6 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/Stat.h"
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#include "Layer.h"
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#include "BatchNormBaseLayer.h"
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#include "BatchNormalizationLayer.h"
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#ifndef PADDLE_ONLY_CPU
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#include "CudnnBatchNormLayer.h"
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#endif
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namespace paddle {
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bool BatchNormBaseLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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/* Initialize the basic parent class */
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if (!Layer::init(layerMap, parameterMap)) return false;
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/* initialize the weightList */
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// first is Input in configure
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// other two is created in config_parser.py
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CHECK_EQ(inputLayers_.size(), 3U);
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CHECK_EQ(inputLayers_.size(), parameters_.size());
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CHECK_EQ(inputLayers_.size(), size_t(config_.inputs_size()));
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const ImageConfig& conf = config_.inputs(0).image_conf();
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channels_ = conf.channels();
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calFeatureMapSize();
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if (config_.has_use_global_stats()) {
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useGlobalStats_ = config_.use_global_stats();
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}
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movingAvgFraction_ = config_.moving_average_fraction();
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weight_.reset(new Weight(1, channels_, parameters_[0]));
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movingMean_.reset(new Weight(1, channels_, parameters_[1]));
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movingVar_.reset(new Weight(1, channels_, parameters_[2]));
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if (biasParameter_.get() != NULL) {
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biases_ = std::unique_ptr<Weight>(new Weight(1, channels_, biasParameter_));
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}
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savedMean_ = Matrix::create(1, channels_, false, useGpu_);
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savedInvVar_ = Matrix::create(1, channels_, false, useGpu_);
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savedMean_->zeroMem();
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savedInvVar_->zeroMem();
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return true;
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}
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void BatchNormBaseLayer::calFeatureMapSize() {
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const ImageConfig& conf = config_.inputs(0).image_conf();
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if (inputLayers_[0]->getOutput().getFrameHeight() == 0 &&
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inputLayers_[0]->getOutput().getFrameWidth() == 0) {
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imgSize_ = conf.img_size();
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imageH_ = imgSize_;
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imageW_ = imgSize_;
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} else {
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imageH_ = inputLayers_[0]->getOutput().getFrameHeight();
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imageW_ = inputLayers_[0]->getOutput().getFrameWidth();
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}
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imgPixels_ = imageH_ * imageW_;
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getOutput().setFrameHeight(imageH_);
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getOutput().setFrameWidth(imageW_);
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}
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} // namespace paddle
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