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pass_utils.h 2.8 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_PASS_UTILS_H_
  17. #define GE_GRAPH_PASSES_PASS_UTILS_H_
  18. #include <vector>
  19. #include "framework/common/debug/ge_log.h"
  20. #include "common/ge_inner_error_codes.h"
  21. #include "graph/compute_graph.h"
  22. namespace ge {
  23. class PassUtils {
  24. public:
  25. PassUtils() = delete;
  26. ~PassUtils() = delete;
  27. static NodePtr GetInDataNode(const ConstNodePtr &node, int index);
  28. static bool IsConstant(const ConstNodePtr &node);
  29. static Status SetOutNodeWeight(const OutDataAnchorPtr &out_data_anchor, const NodePtr &src_node);
  30. static Status RemoveBranch(const NodePtr &node, std::vector<NodePtr> &delete_nodes, std::vector<NodePtr> &end_nodes);
  31. static Status RemoveInactiveBranchToMerge(const OutDataAnchorPtr &inactive_output_anchor,
  32. std::vector<NodePtr> &delete_nodes, std::vector<NodePtr> &end_nodes);
  33. ///
  34. /// check is need iter flow ctrl.
  35. /// @param compute_graph graph
  36. /// @return true:need iter flow ctrl.
  37. /// false:no need
  38. ///
  39. static bool IsNeedTrainIteFlowCtrl(const ComputeGraphPtr &compute_graph);
  40. /// Construct a TensorDesc and put the data in it, it's shape is a list.
  41. /// If the data length is 1, it's shape is []
  42. static Status ConstructTensorDescWithData(const GeTensorDesc &out_desc, std::vector<int64_t> &data,
  43. std::vector<GeTensorPtr> &v_output, const bool scalar_output = false);
  44. template <typename T>
  45. static Status ConstructTensorDescWithData(const GeTensorDesc &out_desc, T *buf, uint32_t len,
  46. std::vector<GeTensorPtr> &v_output, const bool scalar_output = false);
  47. ///
  48. /// find in data anchor index with a valid peer out node existed
  49. /// @param node_ptr
  50. /// @return index
  51. ///
  52. static int GetUniqueInDataAnchorIndex(const NodePtr &node_ptr);
  53. ///
  54. /// unlink node's in data anchors[index]'s father node with node itself
  55. /// then link father node's all in control nodes to node
  56. /// if any and not connected yet
  57. /// @param node
  58. /// @param index: in data anchor index
  59. /// @return
  60. ///
  61. static Status UnlinkNodeWithControlCopy(NodePtr &node, int index);
  62. };
  63. } // namespace ge
  64. #endif // GE_GRAPH_PASSES_PASS_UTILS_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