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assign_remove_pass.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_PASSES_ASSIGN_REMOVE_PASS_H_
  17. #define GE_GRAPH_PASSES_ASSIGN_REMOVE_PASS_H_
  18. #include "graph/passes/base_pass.h"
  19. namespace ge {
  20. class AssignRemovePass : public BaseNodePass {
  21. public:
  22. Status Run(NodePtr &node) override;
  23. private:
  24. #ifndef ONLY_COMPILE_OPEN_SRC
  25. ///
  26. /// @brief Optimize for assign_node
  27. /// @param [in] assign_node
  28. /// @return Status
  29. ///
  30. Status OptimizedAssignNode(NodePtr &assign_node);
  31. ///
  32. /// @brief Transform assign_var_name attr
  33. /// @param [in] node
  34. /// @return Status
  35. ///
  36. Status TransformAttr(NodePtr &node);
  37. #endif
  38. ///
  39. /// @brief Check if need optimize for assign_node
  40. /// @param [in] assign_node
  41. /// @param [in] peer_data_anchor for ref_input of assign_node
  42. /// @param [in] peer_data_anchor for value_input of assign_node
  43. /// @return Status
  44. ///
  45. static bool IsCondMatch(const NodePtr &node, const OutDataAnchorPtr &ref_peer_anchor,
  46. const OutDataAnchorPtr &value_peer_anchor);
  47. };
  48. } // namespace ge
  49. #endif // GE_GRAPH_PASSES_ASSIGN_REMOVE_PASS_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