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88 lines
3.1 KiB
88 lines
3.1 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 "paddle/utils/Util.h"
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#include "paddle/parameter/AverageOptimizer.h"
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#include "paddle/parameter/FirstOrderOptimizer.h"
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#include "paddle/parameter/OptimizerFunctions.h"
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#include "paddle/parameter/OptimizerWithRegularizer.h"
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#include "paddle/parameter/Parameter.h"
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#include "paddle/parameter/Regularizer.h"
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#include <memory>
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#include <vector>
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namespace paddle {
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/**
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* \brief A parameter updater that uses multiple threads to update parameters.
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This parameter updater handles GPU and CPU updates differently,
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because at the current moment, the merging on CPU is happening on the
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main thread, and the its parameter size can be much larger than the one GPU.
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Thus, for GPU, the parameter updates happens in updateImpl() function, which
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is called by gradient machines as a callback function as a callback function
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supplied to backward() and forwardBackward().
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For CPU, the parameter updates happens in separate threads maintained by this
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class.
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*/
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class SgdThreadUpdater : public ParameterUpdater {
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public:
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explicit SgdThreadUpdater(const OptimizationConfig& optConfig);
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virtual ~SgdThreadUpdater() {}
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// Use the startPass() function of the base optimizer.
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virtual void startPass();
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// Use the finishPass() function of the base optimizer.
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virtual bool finishPass(real cost);
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virtual void init(std::vector<ParameterPtr>& parameters);
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virtual PassType startBatch(int64_t batchSize);
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// Call finishBatch for each optimizer.
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virtual void finishBatch(real cost);
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virtual void catchUpWith();
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virtual void apply();
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virtual void restore();
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protected:
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// This is the function that will be eventualy called by the GradientMachine.
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// used only for GPU update.
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virtual void updateImpl(Parameter* para);
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OptimizationConfig config_;
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int64_t numSamplesProcessed_;
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// One optimizers for each parameter.
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std::vector<std::unique_ptr<ParameterOptimizer>> optimizers_;
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// The update function for CPU sparse parameters.
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void threadUpdateSparse(int tid, size_t numThreads, Parameter* para);
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// The update function for CPU dense parameters.
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void threadUpdateDense(int tid, size_t numThreads, Parameter* para);
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// The update function for after update operations, such as averager.
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void threadTraverse(const ParameterOptimizer::TraverseCallback& callback,
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int tid, size_t numThreads, Parameter* para);
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typedef std::function<const ParameterOptimizer::TraverseCallback&(Parameter*)>
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GetTraverseCallback;
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void traverse(GetTraverseCallback getTraverseCallback);
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};
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} // namespace paddle
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