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66 lines
1.8 KiB
66 lines
1.8 KiB
9 years ago
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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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#include "paddle/utils/ThreadLocal.h"
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namespace paddle {
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/**
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* @brief ParameterReluLayer active inputs with learnable parameter weight_.
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* forward:
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* \f[
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* y = x > 0 ? x : w .* x
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* \f]
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* backward:
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* \f[
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* dx = x > 0 ? dy : w .* dy \\
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* dw = x > 0 ? 0 : dy.*x
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* \f]
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* Here, x is the input, w is the weight, y is the output.
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* dx, dw, dy is the gradient.
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*/
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class ParameterReluLayer : public Layer {
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protected:
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std::unique_ptr<Weight> weight_;
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/**
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* @brief partialSum_ makes a group of inputs share same weights,
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* - partialSum_ = 1:
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* element wise activation: each element has a weight_,
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* - partialSum_ = number of elements in one channel,
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* channels wise parameter activation, elements in a channel
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* share same weight_,
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* - partialSum_ = number of outputs
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* all elements share same weight_,
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*/
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size_t partialSum_;
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public:
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explicit ParameterReluLayer(const LayerConfig& config) : Layer(config) {}
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~ParameterReluLayer() {}
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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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};
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} // namespace paddle
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