You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

ge_generator.h 3.6 kB

5 years ago
5 years ago
5 years ago
5 years ago
5 years ago
5 years ago
5 years ago
5 years ago
5 years ago
5 years ago
12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394959697
  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 INC_FRAMEWORK_GENERATOR_GE_GENERATOR_H_
  17. #define INC_FRAMEWORK_GENERATOR_GE_GENERATOR_H_
  18. #include <map>
  19. #include <memory>
  20. #include <string>
  21. #include <vector>
  22. #include "ge/ge_ir_build.h"
  23. #include "common/ge_inner_error_codes.h"
  24. #include "common/ge_types.h"
  25. #include "graph/ge_tensor.h"
  26. #include "graph/graph.h"
  27. #include "graph/op_desc.h"
  28. #include "graph/detail/attributes_holder.h"
  29. #include "omg/omg_inner_types.h"
  30. namespace ge {
  31. class GeGenerator {
  32. public:
  33. static GeGenerator &GetInstance() {
  34. static GeGenerator Instance;
  35. return Instance;
  36. }
  37. GeGenerator() = default;
  38. ~GeGenerator() { (void)Finalize(); }
  39. GeGenerator(const GeGenerator &) = delete;
  40. GeGenerator &operator=(const GeGenerator &) = delete;
  41. Status Initialize(const std::map<std::string, std::string> &options);
  42. Status Initialize(const std::map<std::string, std::string> &options, OmgContext &context);
  43. Status Finalize();
  44. Status GenerateOfflineModel(const Graph &graph, const std::string &file_name_prefix,
  45. const std::vector<GeTensor> &inputs = std::vector<GeTensor>());
  46. Status GenerateOnlineModel(const Graph &graph, const vector<GeTensor> &inputs, ge::ModelBufferData &model);
  47. Status GenerateInfershapeGraph(const Graph &graph);
  48. ///
  49. /// @ingroup ge
  50. /// @brief: Build single OP in Model.
  51. /// @param [in] op_desc: the OP description.
  52. /// @param [in] inputs: input tensors.
  53. /// @param [in] outputs: output tensors.
  54. /// @param [in] model_file_name: name of model file.
  55. /// @return SUCCESS or FAILED
  56. ///
  57. Status BuildSingleOpModel(OpDescPtr &op_desc, const std::vector<GeTensor> &inputs,
  58. const std::vector<GeTensor> &outputs, const std::string &model_file_name);
  59. ///
  60. /// @ingroup ge
  61. /// @brief: Build single Op into model buff.
  62. /// @param [in] op_desc: the OP description.
  63. /// @param [in] inputs: input tensors.
  64. /// @param [in] outputs: output tensors.
  65. /// @param [in] engine_type: specific engine.
  66. /// @param [out] model_buff: model buff of single op.
  67. /// @return SUCCESS or FAILED
  68. Status BuildSingleOpModel(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs,
  69. OpEngineType engine_type, ModelBufferData &model_buff);
  70. private:
  71. Status GenerateModel(const Graph &graph, const string &file_name_prefix, const vector<GeTensor> &inputs,
  72. ge::ModelBufferData &model, bool is_offline = true);
  73. Status BuildSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs,
  74. const string &model_file_name, OpEngineType engine_type, ModelBufferData &model_buff,
  75. bool is_offline = true);
  76. Status CheckForSingleOp(OpDescPtr &op_desc, const vector<GeTensor> &inputs, const vector<GeTensor> &outputs);
  77. class Impl;
  78. std::shared_ptr<Impl> impl_;
  79. };
  80. } // namespace ge
  81. #endif // INC_FRAMEWORK_GENERATOR_GE_GENERATOR_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