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engine_place.h 1.7 kB

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  1. /**
  2. * Copyright 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 GE_GRAPH_PARTITION_ENGINE_PLACE_H_
  17. #define GE_GRAPH_PARTITION_ENGINE_PLACE_H_
  18. #include <unordered_map>
  19. #include "framework/common/ge_inner_error_codes.h"
  20. #include "graph/compute_graph.h"
  21. namespace ge {
  22. using NodeEngineMap = std::unordered_map<ConstNodePtr, std::string>;
  23. ///
  24. /// @ingroup graph/partition
  25. /// @brief Assigned individual DNNEngine to each node in the origin graph
  26. /// @author
  27. ///
  28. class EnginePlacer {
  29. public:
  30. explicit EnginePlacer(const ComputeGraphPtr &graph) : compute_graph_(graph) {}
  31. EnginePlacer() = default;
  32. ~EnginePlacer() = default;
  33. Status Run(bool direct_node_flag = true);
  34. Status AssignCompoundEngine();
  35. // Get the unique node-engine map
  36. const NodeEngineMap *GetNodeEngineMap(bool compound_engine_flag) const;
  37. void SetComputeGraph(const ComputeGraphPtr &compute_graph) { compute_graph_ = compute_graph; }
  38. private:
  39. Status Check() const;
  40. ComputeGraphPtr compute_graph_;
  41. NodeEngineMap node_atomic_engine_map_;
  42. NodeEngineMap node_compound_engine_map_;
  43. };
  44. } // namespace ge
  45. #endif // GE_GRAPH_PARTITION_ENGINE_PLACE_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