65 lines
1.9 KiB
65 lines
1.9 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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#pragma once
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#include "GradientMachine.h"
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#include "NeuralNetwork.h"
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#include "paddle/utils/Locks.h"
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namespace paddle {
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class MultiNetwork : public NeuralNetwork {
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public:
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explicit MultiNetwork(std::string subModelName = "")
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: NeuralNetwork(subModelName) {}
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virtual void init(const ModelConfig& config,
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ParamInitCallback callback,
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const std::vector<ParameterType>& parameterTypes,
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bool useGpu);
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virtual void prefetch(const std::vector<Argument>& inArgs);
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virtual void forward(const std::vector<Argument>& inArgs,
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std::vector<Argument>* outArgs,
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PassType passType);
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virtual void backward(const UpdateCallback& callback = nullptr);
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void forwardBackward(const std::vector<Argument>& inArgs,
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std::vector<Argument>* outArgs,
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PassType passType,
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const UpdateCallback& callback);
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virtual void onPassEnd();
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virtual Evaluator* makeEvaluator() const;
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virtual void eval(Evaluator* evaluator) const;
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const std::vector<std::unique_ptr<NeuralNetwork>>& getSubNetworks() const {
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return subNetworks_;
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}
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virtual void start();
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virtual void finish();
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protected:
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std::vector<std::unique_ptr<NeuralNetwork>> subNetworks_;
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};
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} // namespace paddle
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