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/**
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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 GE_GRAPH_EXECUTE_GRAPH_EXECUTE_H_
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#define GE_GRAPH_EXECUTE_GRAPH_EXECUTE_H_
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#include <cstdarg>
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#include <fstream>
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#include <iostream>
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#include <memory>
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#include <vector>
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#include "common/debug/log.h"
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#include "common/debug/memory_dumper.h"
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#include "common/ge_types.h"
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#include "common/properties_manager.h"
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#include "common/string_util.h"
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#include "common/types.h"
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#include "common/util.h"
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#include "ge/ge_api_types.h"
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#include "graph/compute_graph.h"
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#include "graph/manager/graph_context.h"
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#include "graph/manager/graph_manager_utils.h"
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#include "graph/model.h"
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#include "graph/utils/graph_utils.h"
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#include "graph/utils/tensor_utils.h"
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namespace ge {
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class GraphExecutor {
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public:
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GraphExecutor();
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virtual ~GraphExecutor();
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Status ExecuteGraph(GraphId graph_id, const GeRootModelPtr &ge_root_model, const std::vector<GeTensor> &input_tensor,
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std::vector<GeTensor> &output_tensor);
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ge::Status ExecuteGraphAsync(GraphId graph_id, const GeRootModelPtr &ge_root_model,
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const std::vector<InputTensorInfo> &input_tensor);
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Status SetCondition(std::mutex *mutex, std::condition_variable *cond, std::shared_ptr<GraphModelListener> listener);
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Status SetGraphContext(GraphContextPtr graph_context_ptr);
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static Status SetDynamicSize(uint32_t model_id, const std::vector<uint64_t> &batch_num, int32_t dynamic_type);
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void SetTrainFlag(bool is_train_graph);
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const std::vector<InputOutputDescInfo> &GetOutputsDesc() const { return outputs_desc_; }
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Status FreeExecuteMemory();
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static Status DataInput(const InputData &input_data, OutputData &output_data);
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static Status GetInputOutputDescInfo(const uint32_t model_id, vector<InputOutputDescInfo> &input_desc,
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vector<InputOutputDescInfo> &output_desc);
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static Status GetInputOutputDescInfo(const uint32_t model_id, vector<InputOutputDescInfo> &input_desc,
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vector<InputOutputDescInfo> &output_desc, std::vector<uint32_t> &input_formats,
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std::vector<uint32_t> &output_formats, bool new_model_desc = false);
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static Status GetAippInfo(uint32_t model_id, uint32_t index, AippConfigInfo &aipp_info);
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static Status GetAippType(uint32_t model_id, uint32_t index, InputAippType &type, size_t &aipp_index);
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///
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/// @ingroup ge
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/// @brief Get dynamic batch_info
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/// @param [in] model_id
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/// @param [out] batch_info
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/// @param [out] dynamic_type
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/// @return execute result
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///
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static Status GetDynamicBatchInfo(uint32_t model_id, std::vector<std::vector<int64_t>> &batch_info,
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int32_t &dynamic_type);
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///
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/// @ingroup ge
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/// @brief Get combined dynamic dims info
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/// @param [in] model_id
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/// @param [out] batch_info
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/// @return execute result
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///
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static Status GetCombinedDynamicDims(uint32_t model_id, std::vector<std::vector<int64_t>> &batch_info);
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///
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/// @ingroup ge
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/// @brief Get user designate shape order
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/// @param [in] model_id
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/// @param [out] user_input_shape_order
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/// @return execute result
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///
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static Status GetUserDesignateShapeOrder(uint32_t model_id, std::vector<std::string> &user_input_shape_order);
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static Status GetCurShape(const uint32_t model_id, std::vector<int64_t> &batch_info, int32_t &dynamic_type);
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static Status GetModelAttr(uint32_t model_id, std::vector<string> &dynamic_output_shape_info);
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static Status GetOrigInputInfo(uint32_t model_id, uint32_t index, OriginInputInfo &orig_input_info);
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static Status GetAllAippInputOutputDims(uint32_t model_id, uint32_t index, std::vector<InputOutputDims> &input_dims,
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std::vector<InputOutputDims> &output_dims);
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static Status GetOpDescInfo(uint32_t device_id, uint32_t stream_id, uint32_t task_id, OpDescInfo &op_desc_info);
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private:
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Status PrepareInputData(const std::vector<GeTensor> &input_tensor, InputData &graph_input_data,
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OutputData &graph_output_data, std::vector<InputOutputDescInfo> &output_desc);
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Status SyncExecuteModel(uint32_t model_id, const std::vector<GeTensor> &input_tensor,
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std::vector<GeTensor> &output_tensor);
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Status AsyncExecuteModel(uint32_t model_id, const std::vector<InputTensorInfo> &input_tensor);
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void InitModelIdInfo(std::vector<uint32_t> &out_model_id_info, std::vector<SubGraphInfoPtr> &sub_graph_vec,
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uint32_t output_size);
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Status FreeInOutBuffer();
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Status MallocInOutBuffer(const std::vector<uint64_t> &buffer_size, std::vector<void *> &data_addr);
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bool init_flag_;
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bool train_graph_flag_;
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// For run graph synchronous return
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std::mutex *sync_run_mutex_;
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std::condition_variable *condition_;
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// Run graph asynchronous call back listener
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std::shared_ptr<GraphModelListener> graph_run_listener_;
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GraphContextPtr graph_context_;
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std::vector<InputOutputDescInfo> outputs_desc_;
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GraphId last_graph_id_;
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bool malloc_flag_;
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std::vector<void *> buffer_addr_;
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std::vector<uint64_t> buffer_size_;
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};
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} // namespace ge
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#endif // GE_GRAPH_EXECUTE_GRAPH_EXECUTE_H_
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