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fwk_adpt_struct.h 4.0 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 FWK_ADPT_STRUCT_H__
  17. #define FWK_ADPT_STRUCT_H__
  18. #include <cstdint>
  19. namespace aicpu {
  20. namespace FWKAdapter {
  21. // API RETURN CODE
  22. enum FWKAdptAPIRetCode {
  23. FWK_ADPT_SUCCESS = 0, // success
  24. FWK_ADPT_NOT_INIT = 1, // not init
  25. FWK_ADPT_ALLOC_FAILED = 2, // allocate memory failed
  26. FWK_ADPT_PARAM_INVALID = 3, // invalid input param
  27. FWK_ADPT_PARAM_PARSE_FAILED = 4, // parase input param failed
  28. FWK_ADPT_NATIVE_ERROR = 5, // error code
  29. FWK_ADPT_NOT_SUPPORT_OPTYPE = 6, // unsupport operate type
  30. FWK_ADPT_INTERNAL_ERROR = 7, // adpter internal error
  31. FWK_ADPT_NOT_SUPPORT_DATATYPE = 8, // unsupport input/output data type
  32. FWK_ADPT_KERNEL_ALREADY_RUNING = 9, // kernel already runing, not support parallel run
  33. FWK_ADPT_SESSION_NOT_EXIST = 10, // session id not exist
  34. FWK_ADPT_SESSION_ALREADY_EXIST = 11, // session id alread exist for create session
  35. FWK_ADPT_NATIVE_END_OF_SEQUENCE = 12, // end of sequence
  36. FWK_ADPT_UNKNOWN_ERROR = 99 // unknown error code
  37. };
  38. // FWKAdapter operate type
  39. // Notice: add new operate type need check with OMM, and make sure append to the end line.
  40. enum FWKOperateType {
  41. FWK_ADPT_SESSION_CREATE = 0,
  42. FWK_ADPT_KERNEL_RUN,
  43. FWK_ADPT_KERNEL_DESTROY,
  44. FWK_ADPT_SESSION_DESTROY,
  45. FWK_ADPT_SINGLE_OP_RUN
  46. };
  47. // Extend Info type for task
  48. enum FWKTaskExtInfoType {
  49. FWK_ADPT_EXT_SHAPE_TYPE = 0,
  50. FWK_ADPT_EXT_INPUT_SHAPE,
  51. FWK_ADPT_EXT_OUTPUT_SHAPE,
  52. FWK_ADPT_EXT_INVALID
  53. };
  54. // API Parameter Structure
  55. struct StrFWKKernel {
  56. FWKOperateType opType;
  57. uint64_t sessionID; // unique
  58. uint64_t stepIDAddr; // step id addr
  59. uint64_t kernelID; // run kernel id, unique in session
  60. uint64_t nodeDefLen; // nodeDef protobuf len
  61. uint64_t nodeDefBuf; // NodeDef protobuf offset addr, need convert to void*
  62. uint64_t funDefLibLen; // FunctionDefLibrary protobuf len
  63. uint64_t funDefLibBuf; // FunctionDefLibrary protobuf addr which use in NodeDef, need convert to void*
  64. uint64_t inputOutputLen; // InputOutput shap protobuf len
  65. uint64_t inputOutputBuf; // InputOutput shap protobuf addr, need convert to void*
  66. uint64_t workspaceBaseAddr; // Workspace base addr, need convert to void*
  67. uint64_t inputOutputAddr; // InputOutput addr, need convert to void*
  68. uint64_t extInfoLen; // extend info total length
  69. uint64_t extInfoAddr; // extend info addr, ExtInfo structure
  70. } __attribute__((packed));
  71. typedef StrFWKKernel FWKOperateParam;
  72. // Extent info ShapeAndType
  73. const uint32_t kMaxShapeDims = 8;
  74. struct ShapeAndType {
  75. int32_t type;
  76. int64_t dims[kMaxShapeDims];
  77. } __attribute__((packed));
  78. // Extend info structure for extInfoAddr
  79. const uint32_t kExtInfoHeadSize = 8;
  80. struct ExtInfo {
  81. int32_t infoType; // extend type
  82. uint32_t infoLen; // length for infoMsg
  83. char infoMsg[0]; // extend value
  84. } __attribute__((packed));
  85. struct ResultSummary {
  86. uint64_t shape_data_ptr; // shape data addr, need convert to void*
  87. uint64_t shape_data_size; // num of dims
  88. uint64_t raw_data_ptr; // raw data addr, need convert to void*
  89. uint64_t raw_data_size; // size of raw data
  90. } __attribute__((packed));
  91. } // end namespace FWKAdapter
  92. } // namespace aicpu
  93. #endif // FWK_ADPT_STRUCT_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