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op_info.h 1.8 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 INC_FRAMEWORK_GE_RUNTIME_OP_INFO_H_
  17. #define INC_FRAMEWORK_GE_RUNTIME_OP_INFO_H_
  18. #include <memory>
  19. #include <string>
  20. #include <vector>
  21. namespace ge {
  22. namespace model_runner {
  23. struct TensorInfo {
  24. int64_t GetShapeSize() const {
  25. int64_t res = 1;
  26. if (dims.empty()) {
  27. return 0;
  28. }
  29. for (auto dim : dims) {
  30. res *= dim;
  31. }
  32. return res;
  33. }
  34. int64_t GetDim(uint32_t index) {
  35. if (index >= dims.size()) {
  36. return 0;
  37. }
  38. return dims[index];
  39. }
  40. std::vector<int64_t> dims;
  41. uint32_t datatype;
  42. uint32_t format;
  43. uint32_t real_dim_cnt;
  44. uint32_t size;
  45. bool is_output;
  46. };
  47. struct OpInfo {
  48. uint32_t index;
  49. std::string name;
  50. std::string type;
  51. bool var_is_broadcast;
  52. std::vector<uintptr_t> input_addrs;
  53. std::vector<uintptr_t> output_addrs;
  54. std::vector<TensorInfo> input_tensors;
  55. std::vector<TensorInfo> output_tensors;
  56. std::vector<TensorInfo> weight_tensors;
  57. std::vector<std::string> src_name;
  58. std::vector<int64_t> src_index;
  59. std::string weight_data;
  60. };
  61. using TensorInfoPtr = std::shared_ptr<TensorInfo>;
  62. using OpInfoPtr = std::shared_ptr<OpInfo>;
  63. } // namespace model_runner
  64. } // namespace ge
  65. #endif // INC_FRAMEWORK_GE_RUNTIME_OP_INFO_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