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106 lines
3.1 KiB
106 lines
3.1 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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#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 The SelectiveFullyConnectedLayer class
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*
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* SelectiveFullyConnectedLayer differs from FullyConnectedLayer by that it
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* requires an additional input to indicate several selected columns, and only
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* compute the multiplications between the input matrices and the selected
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* columns of the parameter matrices of this layer. If the selected columns is
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* not specified, SelectiveFullyConnected layer acts exactly like
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* FullyConnectedLayer.
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*
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* The config file api is selective_fc_layer.
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*/
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class SelectiveFullyConnectedLayer : public Layer {
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protected:
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WeightList weights_;
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std::unique_ptr<Weight> biases_;
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private:
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/**
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* Get selected columns each forward.
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*/
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void getSelectiveCols();
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MatrixPtr mmat_;
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/// cpuSelCols_ is a CpuSparseMatrix, used to save selected columns.
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MatrixPtr cpuSelCols_;
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/// CpuSparseMatrix or GpuSparseMatrix. In CPU mode, selCols_ points
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/// to cpuSelCols_.
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MatrixPtr selCols_;
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size_t inputNum_;
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/// interOutput_ shared same memory with output_.value.
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MatrixPtr interOutput_;
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/// if fullOutput_ is false, interOutGrad_ sparse matrix
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MatrixPtr interOutGrad_;
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/// if true, means output_.value is the same as Fc Layer
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bool fullOutput_;
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public:
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explicit SelectiveFullyConnectedLayer(const LayerConfig& config)
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: Layer(config), selCols_(nullptr) {}
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~SelectiveFullyConnectedLayer() {}
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void prefetch();
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bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);
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Weight& getWeight(int idx) { return *weights_[idx]; }
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/**
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* @brief Resize the output matrix size.
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* And reset value to zero
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*/
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void reserveOutput(size_t height, size_t width, size_t nnz);
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/**
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* @brief Fill candidates to select several activations as output.
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* @param candidates specifies several selected columns of the parameter
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* matrices of this layer.
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* Multiplications only between the input matrices and the selected columns
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* are computed.
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* If the candidates is a nullptr, selective fc layer acts exactly like the
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* fully connected layer.
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* @note CURRENTLY, THIS METHOD IS ONLY USED FOR BEAM SEARCH
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*/
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void fillSelectiveData(
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const std::shared_ptr<std::vector<std::pair<int*, size_t>>>& candidates);
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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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/**
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* @brief Make SelectiveFC act as FullyConnectedLayer
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*/
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void fillFullySelectiveData() {
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fullOutput_ = true;
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}
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};
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} // namespace paddle
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