forked from mindspore-Ecosystem/mindspore
61 lines
1.9 KiB
C++
61 lines
1.9 KiB
C++
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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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*/
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#ifndef MINDSPORE_LITE_INCLUDE_TRAIN_SESSION_H_
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#define MINDSPORE_LITE_INCLUDE_TRAIN_SESSION_H_
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#include <vector>
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#include <string>
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#include <unordered_map>
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// #include "include/lite_session.h"
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#include "src/lite_session.h"
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namespace mindspore {
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namespace lite {
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struct Model;
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}
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namespace session {
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class TrainSession : public lite::LiteSession {
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public:
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TrainSession();
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~TrainSession() = default;
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int RunGraph(const session::KernelCallBack &before = nullptr,
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const session::KernelCallBack &after = nullptr) override;
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int CompileGraph(lite::Model *model) override;
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virtual void ReplaceOps();
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virtual void *ExportToBuf(void *buf, size_t *len) const;
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// todo: output tensors by tensor name
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std::unordered_map<std::string, std::vector<mindspore::tensor::MSTensor *>> GetOutputMap() const;
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std::vector<tensor::MSTensor *> GetOutputsByName(const std::string &node_name) const;
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virtual void train();
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bool is_train() { return train_mode_ == true; }
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virtual void eval();
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bool is_eval() { return train_mode_ == false; }
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protected:
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bool train_mode_ = false;
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lite::Model *model_ = nullptr;
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std::unordered_map<std::string, std::vector<mindspore::tensor::MSTensor *>> ext_output_map_;
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// private:
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};
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} // namespace session
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} // namespace mindspore
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#endif // MINDSPORE_LITE_INCLUDE_TRAIN_SESSION_H_
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