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105 lines
3.4 KiB
105 lines
3.4 KiB
/**
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* Copyright 2019-2020 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 GE_HYBRID_EXECUTOR_MODEL_HYBRID_MODEL_ASYNC_EXECUTOR_H_
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#define GE_HYBRID_EXECUTOR_MODEL_HYBRID_MODEL_ASYNC_EXECUTOR_H_
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#include <atomic>
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#include <mutex>
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#include <future>
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#include "external/ge/ge_api_error_codes.h"
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#include "external/ge/ge_api_types.h"
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#include "common/dump/opdebug_register.h"
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#include "graph/load/model_manager/data_inputer.h"
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#include "graph/load/model_manager/data_dumper.h"
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#include "hybrid/executor/hybrid_model_executor.h"
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#include "hybrid/executor/hybrid_model_pipeline_executor.h"
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#include "runtime/stream.h"
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namespace ge {
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namespace hybrid {
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class HybridModel;
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class HybridModelAsyncExecutor {
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public:
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explicit HybridModelAsyncExecutor(HybridModel *model);
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~HybridModelAsyncExecutor();
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Status Init();
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Status Execute(const std::vector<DataBuffer> &inputs,
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const std::vector<GeTensorDesc> &input_desc,
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std::vector<DataBuffer> &outputs,
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std::vector<GeTensorDesc> &output_desc);
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Status Execute(const vector<GeTensor> &inputs, vector<GeTensor> &outputs);
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Status Start(const std::shared_ptr<ModelListener> &listener);
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void SetDeviceId(uint32_t device_id);
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void SetModelId(uint32_t model_id);
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Status Stop();
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Status EnqueueData(const std::shared_ptr<InputDataWrapper> &data);
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private:
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Status InitInputDesc();
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Status RunInternal();
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Status SyncVarData();
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Status HandleResult(Status exec_ret,
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uint32_t data_id,
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HybridModelExecutor::ExecuteArgs &args,
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OutputData *output_data);
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Status CopyOutputs(HybridModelExecutor::ExecuteArgs &args,
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OutputData *output_data,
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std::vector<ge::OutputTensorInfo> &outputs);
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Status OnComputeDone(uint32_t data_index, uint32_t result_code, std::vector<ge::OutputTensorInfo> &outputs);
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Status PreRun(InputData ¤t_data, HybridModelExecutor::ExecuteArgs &args);
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Status PrepareInputs(const InputData ¤t_data, HybridModelExecutor::ExecuteArgs &args);
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Status DumpOpDebug();
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std::mutex mu_;
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HybridModel *model_;
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uint32_t device_id_ = 0U;
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uint32_t model_id_ = 0U;
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std::atomic_bool run_flag_;
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std::unique_ptr<DataInputer> data_inputer_;
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std::unique_ptr<HybridModelExecutor> executor_;
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std::unique_ptr<HybridModelPipelineExecutor> pipe_executor_;
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std::future<Status> future_;
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uint64_t iterator_count_ = 0;
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rtStream_t stream_ = nullptr;
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std::map<uint32_t, int64_t> input_sizes_;
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std::map<uint32_t, GeTensorDescPtr> input_tensor_desc_;
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std::vector<bool> is_input_dynamic_;
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std::shared_ptr<ModelListener> listener_;
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DataDumper data_dumper_;
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bool is_op_debug_reg_ = false;
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OpdebugRegister op_debug_register_;
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};
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} // namespace hybrid
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} // namespace ge
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#endif // GE_HYBRID_EXECUTOR_MODEL_HYBRID_MODEL_ASYNC_EXECUTOR_H_
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