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error_manager.h 3.6 kB

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  1. /**
  2. * Copyright 2019-2020 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 ERROR_MANAGER_H_
  17. #define ERROR_MANAGER_H_
  18. #include <map>
  19. #include <string>
  20. #include <vector>
  21. #include <mutex>
  22. class ErrorManager {
  23. public:
  24. ///
  25. /// @brief Obtain ErrorManager instance
  26. /// @return ErrorManager instance
  27. ///
  28. static ErrorManager &GetInstance();
  29. ///
  30. /// @brief init
  31. /// @param [in] path: current so path
  32. /// @return int 0(success) -1(fail)
  33. ///
  34. int Init(std::string path);
  35. ///
  36. /// @brief Report error message
  37. /// @param [in] error_code: error code
  38. /// @param [in] args_map: parameter map
  39. /// @return int 0(success) -1(fail)
  40. ///
  41. int ReportErrMessage(std::string error_code, const std::map<std::string, std::string> &args_map);
  42. ///
  43. /// @brief output error message
  44. /// @param [in] handle: print handle
  45. /// @return int 0(success) -1(fail)
  46. ///
  47. int OutputErrMessage(int handle);
  48. ///
  49. /// @brief output message
  50. /// @param [in] handle: print handle
  51. /// @return int 0(success) -1(fail)
  52. ///
  53. int OutputMessage(int handle);
  54. ///
  55. /// @brief Report error message
  56. /// @param [in] key: vector parameter key
  57. /// @param [in] value: vector parameter value
  58. ///
  59. void ATCReportErrMessage(std::string error_code, const std::vector<std::string> &key = {},
  60. const std::vector<std::string> &value = {});
  61. ///
  62. /// @brief report graph compile failed message such as error code and op_name in mstune case
  63. /// @param [in] msg: failed message map, key is error code, value is op_name
  64. /// @return int 0(success) -1(fail)
  65. ///
  66. int ReportMstuneCompileFailedMsg(const std::map<std::string, std::string> &msg);
  67. ///
  68. /// @brief save graph compile failed message from thread local map to global map
  69. /// @param [in] graph_name: graph name
  70. ///
  71. void SaveMstuneCompileFailedMsg(const std::string &graph_name);
  72. ///
  73. /// @brief get graph compile failed message in mstune case
  74. /// @param [in] graph_name: graph name
  75. /// @param [out] msg_map: failed message map, key is error code, value is op_name list
  76. /// @return int 0(success) -1(fail)
  77. ///
  78. int GetMstuneCompileFailedMsg(const std::string &graph_name,
  79. std::map<std::string, std::vector<std::string>> &msg_map);
  80. private:
  81. struct ErrorInfo {
  82. std::string error_id;
  83. std::string error_message;
  84. std::vector<std::string> arg_list;
  85. };
  86. ErrorManager() {}
  87. ~ErrorManager() {}
  88. ErrorManager(const ErrorManager &) = delete;
  89. ErrorManager(ErrorManager &&) = delete;
  90. ErrorManager &operator=(const ErrorManager &) = delete;
  91. ErrorManager &operator=(ErrorManager &&) = delete;
  92. int ParseJsonFile(std::string path);
  93. int ReadJsonFile(const std::string &file_path, void *handle);
  94. bool is_init_ = false;
  95. std::mutex mutex_;
  96. std::map<std::string, ErrorInfo> error_map_;
  97. std::vector<std::string> error_messages_;
  98. std::vector<std::string> warning_messages_;
  99. std::map<std::string, std::map<std::string, std::vector<std::string>>> compile_failed_msg_map_;
  100. };
  101. #endif // ERROR_MANAGER_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