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inner_session.h 3.1 kB

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  1. /**
  2. * Copyright 2020 Huawei Technologies Co., Ltd
  3. *
  4. * Licensed under the Apache License, Version 2.0 (the "License");
  5. * you may not use this file except in compliance with the License.
  6. * You may obtain a copy of the License at
  7. *
  8. * http://www.apache.org/licenses/LICENSE-2.0
  9. *
  10. * Unless required by applicable law or agreed to in writing, software
  11. * distributed under the License is distributed on an "AS IS" BASIS,
  12. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. * See the License for the specific language governing permissions and
  14. * limitations under the License.
  15. */
  16. #ifndef GE_SESSION_INNER_SESSION_H_
  17. #define GE_SESSION_INNER_SESSION_H_
  18. #include <map>
  19. #include <string>
  20. #include <vector>
  21. #include "framework/common/ge_types.h"
  22. #include "ge/ge_api_types.h"
  23. #include "graph/manager/graph_manager.h"
  24. namespace ge {
  25. class InnerSession {
  26. public:
  27. InnerSession(uint64_t session_id, const std::map<string, string> &options);
  28. ~InnerSession() = default;
  29. Status Initialize();
  30. Status AddGraph(uint32_t graph_id, const Graph &graph);
  31. Status AddGraph(uint32_t graph_id, const Graph &graph, const std::map<std::string, std::string> &options);
  32. Status AddGraphWithCopy(uint32_t graph_id, const Graph &graph, const std::map<std::string, std::string> &options);
  33. Status RunGraph(uint32_t graph_id, const std::vector<Tensor> &inputs, std::vector<Tensor> &outputs);
  34. Status RemoveGraph(uint32_t graph_id);
  35. Status BuildGraph(uint32_t graph_id, const std::vector<InputTensorInfo> &inputs);
  36. Status RunGraphAsync(uint32_t graph_id, const std::vector<InputTensorInfo> &inputs, RunAsyncCallback callback);
  37. Status Finalize();
  38. Status GetAllVariables(std::map<std::string, GeTensorDesc> &all_variables);
  39. Status GenCheckPointGraph(const std::map<std::string, GeTensorDesc> &all_variables, Graph &graph);
  40. Status SaveVariables(const Graph &graph, const std::vector<std::string> &var_names,
  41. const std::vector<Tensor> &outputs, std::vector<Tensor> &var_values);
  42. Status GetVariable(const std::string &name, Tensor &val);
  43. Status RegisterCallBackFunc(
  44. const std::string &key,
  45. const std::function<Status(uint32_t, const std::map<std::string, ge::Tensor> &)> &callback);
  46. Status RegisterCallBackFunc(
  47. const std::string &key,
  48. const std::function<Status(uint32_t, const std::map<AscendString, ge::Tensor> &)> &callback);
  49. const GraphManager &getGraphManagerObj() const;
  50. bool IsGraphNeedRebuild(uint32_t graph_id);
  51. Status AddDumpProperties(const DumpProperties &dump_properties);
  52. Status RemoveDumpProperties();
  53. void SetRtSocVersion();
  54. private:
  55. bool init_flag_;
  56. uint64_t session_id_;
  57. std::map<string, string> options_;
  58. GraphManager graph_manager_;
  59. std::mutex resource_mutex_; // AddGraph, RemoveGraph and Finalize use
  60. void UpdateThreadContext(const std::map<std::string, std::string> &options);
  61. void UpdateThreadContext(uint32_t graph_id);
  62. static bool is_dump_server_inited_;
  63. };
  64. } // namespace ge
  65. #endif // GE_SESSION_INNER_SESSION_H_

图引擎模块(GE)是MindSpore的一个子模块,其代码由C++实现,位于前端模块ME和底层硬件之间,起到承接作用。图引擎模块以ME下发的图作为输入,然后进行一系列的深度图优化操作,最后输出一张可以在底层硬件上高效运行的图。GE针对昇腾AI处理器的硬件结构特点,做了特定的优化工作,以此来充分发挥出昇腾AI处理器的强大算力。在进行模型训练/推理时,GE会被自动调用而用户并不感知。GE主要由GE API和GE Core两部分组成,详细的架构图如下所示