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node_item.h 5.2 kB

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  1. /**
  2. * Copyright 2019-2020 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_HYBRID_MODEL_NODE_ITEM_H_
  17. #define GE_HYBRID_MODEL_NODE_ITEM_H_
  18. #include <mutex>
  19. #include <vector>
  20. #include "external/ge/ge_api_error_codes.h"
  21. #include "graph/node.h"
  22. #include "graph/op_desc.h"
  23. #include "framework/common/types.h"
  24. #include "hybrid/common/tensor_value.h"
  25. namespace ge {
  26. namespace hybrid {
  27. class NodeTask;
  28. class NodeExecutor;
  29. struct FusedSubgraph {
  30. std::map<int, std::vector<GeTensorDescPtr>> input_mapping;
  31. std::map<int, OpDescPtr> output_mapping;
  32. std::vector<NodePtr> nodes;
  33. ComputeGraphPtr graph;
  34. };
  35. bool IsControlFlowV2Op(const std::string &op_type);
  36. class OptionalMutexGuard {
  37. public:
  38. OptionalMutexGuard(std::mutex *mutex, const std::string &name);
  39. ~OptionalMutexGuard();
  40. private:
  41. std::mutex *mu_{nullptr};
  42. std::string name_;
  43. };
  44. // for caching static information across execution
  45. struct NodeItem {
  46. ~NodeItem() = default;
  47. static Status Create(const NodePtr &node, std::unique_ptr<NodeItem> &node_item);
  48. const std::string &NodeName() const {
  49. return node_name;
  50. }
  51. const std::string &NodeType() const {
  52. return node_type;
  53. }
  54. OpDescPtr GetOpDesc() const {
  55. return node->GetOpDesc();
  56. }
  57. bool IsInputShapeStatic(int index) const;
  58. GeTensorDescPtr MutableOutputDesc(int index) const;
  59. Status UpdateInputDesc(int index, const GeTensorDesc &tensor_desc);
  60. GeTensorDescPtr MutableInputDesc(int index) const;
  61. Status GetInputDesc(int index, GeTensorDesc &tensor_desc) const;
  62. Status GetOutputDesc(int index, GeTensorDesc &tensor_desc) const;
  63. Status GetCanonicalInputIndex(uint32_t index, int &canonical_index) const;
  64. bool IsControlFlowV2Op() const {
  65. return is_ctrl_flow_v2_op_;
  66. }
  67. bool IsControlFlowOp() const {
  68. return is_ctrl_flow_op_;
  69. }
  70. bool IsMergeOp() const {
  71. return is_merge_op_;
  72. }
  73. bool IsHcclOp() const;
  74. void SetToDynamic();
  75. void SetDataSend(NodeItem *node_item, int anchor_index);
  76. void SetCtrlSend(NodeItem *node_item, uint32_t switch_index);
  77. void SetMergeCtrl(NodeItem *node_item, uint32_t merge_index);
  78. size_t GetMergeCtrl(uint32_t merge_index) const;
  79. OptionalMutexGuard MutexGuard(const std::string &name) const {
  80. return OptionalMutexGuard(copy_mu_.get(), name + "_" + node_name);
  81. }
  82. std::string DebugString() const;
  83. NodePtr node;
  84. OpDesc *op_desc;
  85. int node_id = -1;
  86. int group = -1;
  87. int num_inputs = 0;
  88. int num_outputs = 0;
  89. int input_start = -1;
  90. int output_start = -1;
  91. bool is_dynamic = false;
  92. bool has_observer = false;
  93. bool has_optional_inputs = false;
  94. bool is_output_shape_static = true;
  95. bool is_need_force_infershape = false;
  96. UnknowShapeOpType shape_inference_type = DEPEND_IN_SHAPE;
  97. std::string node_name;
  98. std::string node_type;
  99. std::vector<ge::NodePtr> dependents_for_shape_inference;
  100. std::vector<ge::NodePtr> dependents_for_execution;
  101. std::set<int> to_const_output_id_list;
  102. // src_output_id, dst_anchor_id, dst_node
  103. std::vector<std::vector<std::pair<int, NodeItem *>>> outputs;
  104. // for linked drive
  105. bool is_root_node_ = false;
  106. bool is_ctrl_flow_v2_op_ = false;
  107. bool is_ctrl_flow_op_ = false;
  108. bool is_merge_op_ = false;
  109. std::set<const NodeItem *> root_ctrl_; // Recv ctrl from root node
  110. std::set<const NodeItem *> root_data_; // Recv data from root node
  111. std::set<const NodeItem *> data_send_; // Send data notify to
  112. std::map<const NodeItem *, int> data_recv_; // Recv data notify from
  113. std::set<const NodeItem *> ctrl_send_; // Send ctrl notify to
  114. std::set<const NodeItem *> ctrl_recv_; // Recv ctrl notify from
  115. std::vector<std::vector<const NodeItem *>> switch_groups_; // Send ctrl notify to
  116. std::set<int> enter_inside_; // Enter feed loop inside Node, Not cross Merge.
  117. std::shared_ptr<NodeTask> kernel_task;
  118. std::unique_ptr<FusedSubgraph> fused_subgraph;
  119. const NodeExecutor *node_executor = nullptr;
  120. std::map<int, ge::NodePtr> ref_outputs;
  121. std::map<int, int> reuse_inputs;
  122. std::map<int, int> reuse_outputs;
  123. int num_static_input_shapes = 0;
  124. bool is_profiling_report = false;
  125. private:
  126. explicit NodeItem(NodePtr node);
  127. Status Init();
  128. Status InitInputsAndOutputs();
  129. void ResolveOptionalInputs();
  130. Status ResolveDynamicState();
  131. Status ResolveStaticInputsAndOutputs();
  132. void ResolveUnknownShapeType();
  133. GeTensorDescPtr DoGetInputDesc(int index) const;
  134. std::vector<bool> is_input_shape_static_;
  135. std::vector<uint32_t> input_desc_indices_;
  136. std::shared_ptr<std::mutex> copy_mu_;
  137. mutable std::mutex mu_;
  138. };
  139. } // namespace hybrid
  140. } // namespace ge
  141. #endif // GE_HYBRID_MODEL_NODE_ITEM_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