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model_desc.h 3.6 kB

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  1. /**
  2. * Copyright (c) Huawei Technologies Co., Ltd. 2022. All rights reserved.
  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 AIR_CXX_INC_FRAMEWORK_RUNTIME_MODEL_DESC_H_
  17. #define AIR_CXX_INC_FRAMEWORK_RUNTIME_MODEL_DESC_H_
  18. #include "common/ge_types.h"
  19. #include "common/ge_visibility.h"
  20. #include "exe_graph/runtime/shape.h"
  21. #include "exe_graph/runtime/continuous_vector.h"
  22. #include "exe_graph/runtime/storage_format.h"
  23. #include "exe_graph/runtime/storage_shape.h"
  24. namespace gert {
  25. class VISIBILITY_EXPORT ShapeRange {
  26. public:
  27. ShapeRange() = default;
  28. ShapeRange(const Shape &min_shape, const Shape &max_shape);
  29. bool operator==(const ShapeRange &other) const;
  30. const Shape &GetMin() const;
  31. const Shape &GetMax() const;
  32. Shape &MutableMin();
  33. Shape &MutableMax();
  34. private:
  35. Shape min_;
  36. Shape max_;
  37. };
  38. class VISIBILITY_EXPORT ModelIoDesc {
  39. public:
  40. const ge::char_t *GetName() const;
  41. int32_t GetDataType() const;
  42. ge::Format GetStorageFormat() const;
  43. ge::Format GetOriginFormat() const;
  44. int64_t GetSize() const;
  45. const Shape &GetStorageShape() const;
  46. const Shape &GetOriginShape() const;
  47. const ShapeRange &GetOriginShapeRange() const;
  48. const ShapeRange &GetStorageShapeRange() const;
  49. std::vector<std::pair<int64_t, int64_t>> GetOriginShapeRangeVector() const;
  50. std::vector<std::pair<int64_t, int64_t>> GetStorageShapeRangeVector() const;
  51. void SetName(const ge::char_t *name);
  52. void SetDataType(int32_t data_type);
  53. void SetStorageFormat(ge::Format format);
  54. void SetOriginFormat(ge::Format format);
  55. Shape &MutableStorageShape();
  56. Shape &MutableOriginShape();
  57. ShapeRange &MutableOriginShapeRange();
  58. ShapeRange &MutableStorageShapeRange();
  59. private:
  60. const ge::char_t *name_;
  61. int32_t data_type_;
  62. StorageFormat format_;
  63. StorageShape shape_;
  64. ShapeRange storage_shape_range_;
  65. ShapeRange origin_shape_range_;
  66. };
  67. class VISIBILITY_EXPORT ModelDesc {
  68. public:
  69. static size_t CalcSize(size_t input_num, size_t output_num);
  70. const ModelIoDesc *GetInputDesc(size_t index) const;
  71. const ModelIoDesc *GetAllInputsDesc(size_t &input_num) const;
  72. const ModelIoDesc *GetOutputDesc(size_t index) const;
  73. const ModelIoDesc *GetAllOutputsDesc(size_t &output_num) const;
  74. size_t GetInputNum() const;
  75. size_t GetOutputNum() const;
  76. ModelIoDesc *MutableInputDesc(size_t index);
  77. ModelIoDesc *MutableOutputDesc(size_t index);
  78. ModelIoDesc *AllMutableIoDesc(size_t &input_num, size_t &output_num);
  79. void SetInputNum(size_t input_num);
  80. void SetOutputNum(size_t output_num);
  81. ge::graphStatus GetDynamicBatchInfo(std::vector<std::vector<int64_t>> &batch_info, int32_t &dynamic_type) const;
  82. ge::graphStatus GetUserDesignateShapeOrder(std::vector<std::string> &user_designate_shape_order) const;
  83. ge::graphStatus GetModelAttrs(std::vector<std::string> &attrs) const;
  84. private:
  85. size_t input_num_;
  86. size_t output_num_;
  87. ContinuousVector model_io_descs_;
  88. };
  89. static_assert(std::is_trivial<ModelDesc>::value, "The class ModelDesc must be a POD");
  90. } // namespace gert
  91. #endif // AIR_CXX_INC_FRAMEWORK_RUNTIME_MODEL_DESC_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