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multi_batch_pass.h 3.2 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_MULTI_BATCH_PASS_H_
  17. #define GE_GRAPH_PASSES_MULTI_BATCH_PASS_H_
  18. #include <string>
  19. #include <vector>
  20. #include "inc/graph_pass.h"
  21. namespace ge {
  22. class MultiBatchPass : public GraphPass {
  23. public:
  24. explicit MultiBatchPass(bool attach_label_only = false) : attach_label_only_(attach_label_only) {}
  25. ~MultiBatchPass() override = default;
  26. Status Run(ComputeGraphPtr graph) override;
  27. Status ClearStatus() override;
  28. private:
  29. Status FindPredValue(const ComputeGraphPtr &graph, OutDataAnchorPtr &pred_value);
  30. Status GetDynamicType();
  31. bool CheckSwitchN(std::vector<std::vector<int64_t>> &batch_shape, std::vector<std::vector<int64_t>> &combined_batch);
  32. bool GetBatchInfo(uint32_t batch_num, std::vector<std::vector<int64_t>> &batch_shape,
  33. std::vector<std::vector<int64_t>> &combined_batch);
  34. Status FindSwitchOutNodes(uint32_t batch_num);
  35. Status ReplaceSwitchN(const ComputeGraphPtr &graph, const OutDataAnchorPtr &pred_value,
  36. const std::vector<std::vector<int64_t>> &batch_shape,
  37. const std::vector<std::vector<int64_t>> &combined_batch);
  38. bool CheckDims(const std::vector<std::vector<int64_t>> &output_shape) const;
  39. NodePtr CreateSwitchCaseNode(const ComputeGraphPtr &graph, const std::string &name,
  40. const OutDataAnchorPtr &pred_value,
  41. const std::vector<std::vector<int64_t>> &batch_shape,
  42. const std::vector<std::vector<int64_t>> &combined_batch);
  43. Status BypassSwitchN(const NodePtr &switch_n_node, const NodePtr &switch_case_node);
  44. Status AttachLabel(const NodePtr &switch_case_node);
  45. Status AttachBatchLabel(uint32_t batch_idx);
  46. Status AttachStreamLabel(uint32_t batch_idx, const std::string &stream_label);
  47. Status MoveCtrlEdges(const NodePtr &old_node, const NodePtr &new_node);
  48. Status AttachLabelOnly(uint32_t batch_num);
  49. Status GetUserDesignateShape();
  50. ///
  51. /// @ingroup ge
  52. /// @brief Set batch label for Case mode.
  53. /// @param [in] const ComputeGraphPtr &graph: Root/Case graph.
  54. /// @param [in] const NodePtr &case_node: Case Node.
  55. /// @return 0: SUCCESS / others: FAILED
  56. ///
  57. Status SetCaseLabel(const ComputeGraphPtr &graph, const NodePtr &case_node);
  58. std::vector<NodePtr> switch_n_nodes_;
  59. std::vector<NodePtr> bypass_nodes_;
  60. std::vector<std::vector<NodePtr>> batch_head_nodes_;
  61. std::vector<std::string> data_name_order_;
  62. int32_t dynamic_type_ = 0;
  63. bool attach_label_only_;
  64. };
  65. } // namespace ge
  66. #endif // GE_GRAPH_PASSES_MULTI_BATCH_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