From 0b080a42da85d67d7a900a9b23bdcea6cfcbc01c Mon Sep 17 00:00:00 2001 From: tensor-tang Date: Fri, 22 Dec 2017 13:36:59 +0800 Subject: [PATCH] add recurrent layer header --- paddle/gserver/layers/RecurrentLayer.cpp | 106 +----------------- paddle/gserver/layers/RecurrentLayer.h | 130 +++++++++++++++++++++++ 2 files changed, 131 insertions(+), 105 deletions(-) create mode 100644 paddle/gserver/layers/RecurrentLayer.h diff --git a/paddle/gserver/layers/RecurrentLayer.cpp b/paddle/gserver/layers/RecurrentLayer.cpp index e4c2b483d..285b11b5a 100644 --- a/paddle/gserver/layers/RecurrentLayer.cpp +++ b/paddle/gserver/layers/RecurrentLayer.cpp @@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ +#include "RecurrentLayer.h" #include #include "Layer.h" #include "SequenceToBatch.h" @@ -21,110 +22,6 @@ DEFINE_bool(rnn_use_batch, false, "Using the batch method for calculation."); namespace paddle { -/** - * @brief RecurrentLayer takes 1 input layer. The output size is the same with - * input layer. - * For each sequence [start, end] it performs the following computation: - * \f[ - * out_{i} = act(in_{i}) \ \ \text{for} \ i = start \\ - * out_{i} = act(in_{i} + out_{i-1} * W) \ \ \text{for} \ start < i <= end - * - * \f] - * If reversed is true, the order is reversed: - * \f[ - * out_{i} = act(in_{i}) \ \ \text{for} \ i = end \\ - * out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start <= i < end - * \f] - * There are two methods to calculate rnn. One way is to compute rnn one - * sequence by one sequence. The other way is to reorganize the input - * into batches, then compute rnn one batch by one batch. Users can select - * them by rnn_use_batch flag. - */ - -class RecurrentLayer : public Layer { -public: - explicit RecurrentLayer(const LayerConfig& config) : Layer(config) {} - - bool init(const LayerMap& layerMap, - const ParameterMap& parameterMap) override; - - void forward(PassType passType) override; - - void backward(const UpdateCallback& callback) override; - - void resetState() override; - - void setState(LayerStatePtr state) override; - - LayerStatePtr getState() override; - -protected: - /** - * @brief If user do not set --rnn_use_batch=true, it will - * compute rnn forward one sequence by one sequence in default. - * @param batchSize Total words number of all samples in this batch. - * @param numSequences The sample number. - * @param starts Each start position of each samples. - */ - void forwardSequence(int batchSize, size_t numSequences, const int* starts); - /** - * @brief Compute rnn forward by one sequence. - * @param start The start position of this sequence (or sample). - * @param length The length of this sequence (or sample), namely the words - * number of this sequence. - */ - void forwardOneSequence(int start, int length); - /** - * @brief Compute rnn backward one sequence by onesequence. - * @param batchSize Total words number of all samples in this batch. - * @param numSequences The sample number. - * @param starts Each start position of each samples. - */ - void backwardSequence(int batchSize, size_t numSequences, const int* starts); - /** - * @brief Compute rnn backward by one sequence. - * @param start The start position of this sequence (or sample). - * @param length The length of this sequence (or sample), namely the words - * number of this sequence. - */ - void backwardOneSequence(int start, int length); - - /** - * @brief Reorganize input into batches and compute rnn forward batch - * by batch. It will convert batch shape to sequence after finishing forward. - * The batch info can refer to SequenceToBatch class. - * @param batchSize Total words number of all samples in this batch. - * @param numSequences The sample number. - * @param starts Each start position of each samples. - */ - void forwardBatch(int batchSize, size_t numSequences, const int* starts); - - /** - * @brief Reorganize input into batches and compute rnn forward batch - * by batch. - * @param batchSize Total words number of all samples in this batch. - * @param numSequences The sample number. - * @param starts Each start position of each samples. - */ - void backwardBatch(int batchSize, size_t numSequences, const int* starts); - -protected: - std::unique_ptr weight_; - std::unique_ptr bias_; - - /// frameOutput_[i] is used to hold the i-th sample of output_ - std::vector frameOutput_; - MatrixPtr prevOutput_; - /// Whether compute rnn by reverse. - bool reversed_; - /// If compute batch by batch, batchValue_ will be used to save the - /// reorganized input value. - std::unique_ptr batchValue_; - /// If compute batch by batch, batchGrad_ will be used to save the - /// gradient with respect to reorganized input value. - std::unique_ptr batchGrad_; -}; - REGISTER_LAYER(recurrent, RecurrentLayer); bool RecurrentLayer::init(const LayerMap& layerMap, @@ -260,7 +157,6 @@ void RecurrentLayer::backward(const UpdateCallback& callback) { bias_->getWGrad()->collectBias(*output_.grad, 1); bias_->getParameterPtr()->incUpdate(callback); } - weight_->getParameterPtr()->incUpdate(callback); } diff --git a/paddle/gserver/layers/RecurrentLayer.h b/paddle/gserver/layers/RecurrentLayer.h new file mode 100644 index 000000000..f40dbe150 --- /dev/null +++ b/paddle/gserver/layers/RecurrentLayer.h @@ -0,0 +1,130 @@ +/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. */ +#pragma once +#include +#include "Layer.h" +#include "SequenceToBatch.h" +#include "paddle/utils/Stat.h" + +namespace paddle { + +/** + * @brief RecurrentLayer takes 1 input layer. The output size is the same with + * input layer. + * For each sequence [start, end] it performs the following computation: + * \f[ + * out_{i} = act(in_{i}) \ \ \text{for} \ i = start \\ + * out_{i} = act(in_{i} + out_{i-1} * W) \ \ \text{for} \ start < i <= end + * + * \f] + * If reversed is true, the order is reversed: + * \f[ + * out_{i} = act(in_{i}) \ \ \text{for} \ i = end \\ + * out_{i} = act(in_{i} + out_{i+1} * W) \ \ \text{for} \ start <= i < end + * \f] + * There are two methods to calculate rnn. One way is to compute rnn one + * sequence by one sequence. The other way is to reorganize the input + * into batches, then compute rnn one batch by one batch. Users can select + * them by rnn_use_batch flag. + */ + +class RecurrentLayer : public Layer { +public: + explicit RecurrentLayer(const LayerConfig& config) : Layer(config) {} + + bool init(const LayerMap& layerMap, + const ParameterMap& parameterMap) override; + + void forward(PassType passType) override; + + void backward(const UpdateCallback& callback) override; + + void resetState() override; + + void setState(LayerStatePtr state) override; + + LayerStatePtr getState() override; + +protected: + /** + * @brief If user do not set --rnn_use_batch=true, it will + * compute rnn forward one sequence by one sequence in default. + * @param batchSize Total words number of all samples in this batch. + * @param numSequences The sample number. + * @param starts Each start position of each samples. + */ + void forwardSequence(int batchSize, size_t numSequences, const int* starts); + /** + * @brief Compute rnn forward by one sequence. + * @param start The start position of this sequence (or sample). + * @param length The length of this sequence (or sample), namely the words + * number of this sequence. + */ + void forwardOneSequence(int start, int length); + /** + * @brief Compute rnn backward one sequence by onesequence. + * @param batchSize Total words number of all samples in this batch. + * @param numSequences The sample number. + * @param starts Each start position of each samples. + */ + void backwardSequence(int batchSize, size_t numSequences, const int* starts); + /** + * @brief Compute rnn backward by one sequence. + * @param start The start position of this sequence (or sample). + * @param length The length of this sequence (or sample), namely the words + * number of this sequence. + */ + void backwardOneSequence(int start, int length); + + /** + * @brief Reorganize input into batches and compute rnn forward batch + * by batch. It will convert batch shape to sequence after finishing forward. + * The batch info can refer to SequenceToBatch class. + * @param batchSize Total words number of all samples in this batch. + * @param numSequences The sample number. + * @param starts Each start position of each samples. + */ + virtual void forwardBatch(int batchSize, + size_t numSequences, + const int* starts); + + /** + * @brief Reorganize input into batches and compute rnn forward batch + * by batch. + * @param batchSize Total words number of all samples in this batch. + * @param numSequences The sample number. + * @param starts Each start position of each samples. + */ + virtual void backwardBatch(int batchSize, + size_t numSequences, + const int* starts); + +protected: + std::unique_ptr weight_; + std::unique_ptr bias_; + + /// frameOutput_[i] is used to hold the i-th sample of output_ + std::vector frameOutput_; + MatrixPtr prevOutput_; + /// Whether compute rnn by reverse. + bool reversed_; + /// If compute batch by batch, batchValue_ will be used to save the + /// reorganized input value. + std::unique_ptr batchValue_; + /// If compute batch by batch, batchGrad_ will be used to save the + /// gradient with respect to reorganized input value. + std::unique_ptr batchGrad_; +}; + +} // namespace paddle -- GitLab