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70 lines
2.3 KiB
70 lines
2.3 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 "NormLayer.h"
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#include "NormProjectionLayer.h"
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#include "paddle/utils/Logging.h"
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namespace paddle {
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REGISTER_LAYER_CREATE_FUNC(norm, &NormLayer::create);
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Layer* NormLayer::create(const LayerConfig& config) {
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CHECK_EQ(config.inputs_size(), 1);
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const std::string& norm = config.inputs(0).norm_conf().norm_type();
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if (norm == "rnorm") {
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return new ResponseNormLayer(config);
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} else if (norm == "cmrnorm-projection") {
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return new CMRProjectionNormLayer(config);
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} else if (norm == "cross-channel-norm") {
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return new CrossChannelNormLayer(config);
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} else {
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LOG(FATAL) << "Unknown norm type: " << norm;
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return nullptr;
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}
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}
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bool ResponseNormLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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/* Initialize the basic parent class */
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NormLayer::init(layerMap, parameterMap);
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/* the size of inputs for norm-layer is 1 */
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CHECK_EQ(config_.inputs_size(), 1);
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const NormConfig& conf = config_.inputs(0).norm_conf();
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channels_ = conf.channels();
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size_ = conf.size();
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scale_ = conf.scale();
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pow_ = conf.pow();
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outputX_ = conf.output_x();
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imgSize_ = conf.img_size();
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denoms_ = NULL;
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outputY_ = conf.has_output_y() ? conf.output_y() : conf.output_x();
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imgSizeY_ = conf.has_img_size_y() ? conf.img_size_y() : conf.img_size();
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return true;
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}
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bool CrossChannelNormLayer::init(const LayerMap& layerMap,
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const ParameterMap& parameterMap) {
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Layer::init(layerMap, parameterMap);
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CHECK(parameters_[0]);
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const NormConfig& conf = config_.inputs(0).norm_conf();
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channels_ = conf.channels();
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scale_.reset(new Weight(channels_, 1, parameters_[0]));
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return true;
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}
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} // namespace paddle
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