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label_manager.h 1.7 kB

3 years ago
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  1. /**
  2. * Copyright 2021 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 GE_GE_RUNTIME_TASK_LABEL_MANAGER_H_
  17. #define GE_GE_RUNTIME_TASK_LABEL_MANAGER_H_
  18. #include <vector>
  19. #include <memory>
  20. #include <mutex>
  21. #include <map>
  22. #include <runtime/base.h>
  23. namespace ge {
  24. namespace model_runner {
  25. class LabelGuard {
  26. public:
  27. explicit LabelGuard(void *label_info) : label_info_(reinterpret_cast<uintptr_t>(label_info)) {}
  28. ~LabelGuard();
  29. void *GetLabelInfo() { return reinterpret_cast<void *>(label_info_); }
  30. private:
  31. uintptr_t label_info_;
  32. };
  33. class LabelManager {
  34. public:
  35. static std::shared_ptr<LabelManager> GetInstance();
  36. std::shared_ptr<LabelGuard> GetLabelInfo(rtModel_t model, const std::vector<uint32_t> &label_ids,
  37. const std::vector<void *> &all_label);
  38. private:
  39. std::mutex model_info_mapping_mutex_;
  40. std::map<rtModel_t, std::map<std::string, std::weak_ptr<LabelGuard>>> model_info_mapping_;
  41. static std::weak_ptr<LabelManager> instance_;
  42. static std::mutex instance_mutex_;
  43. };
  44. } // namespace model_runner
  45. } // namespace ge
  46. #endif // GE_GE_RUNTIME_TASK_LABEL_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