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compute_graph.h 11 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 INC_GRAPH_COMPUTE_GRAPH_H_
  17. #define INC_GRAPH_COMPUTE_GRAPH_H_
  18. #include <map>
  19. #include <memory>
  20. #include <string>
  21. #include <utility>
  22. #include <vector>
  23. #include <deque>
  24. #include "detail/attributes_holder.h"
  25. #include "graph/anchor.h"
  26. #include "graph/node.h"
  27. #include "graph/op_desc.h"
  28. #include "graph/range_vistor.h"
  29. namespace ge {
  30. class Node;
  31. using NodePtr = std::shared_ptr<Node>;
  32. class Edge;
  33. using EdgePtr = std::shared_ptr<Edge>;
  34. class InDataAnchor;
  35. using InDataAnchorPtr = std::shared_ptr<InDataAnchor>;
  36. class OutDataAnchor;
  37. using OutDataAnchorPtr = std::shared_ptr<OutDataAnchor>;
  38. class ControlAnchor;
  39. using ControlAnchorPtr = std::shared_ptr<ControlAnchor>;
  40. class InControlAnchor;
  41. using InControlAnchorPtr = std::shared_ptr<InControlAnchor>;
  42. class OutControlAnchor;
  43. using OutControlAnchorPtr = std::shared_ptr<OutControlAnchor>;
  44. class GeAttrValue;
  45. using AttrValuePtr = std::shared_ptr<GeAttrValue>;
  46. using ConstComputeGraph = const ComputeGraph;
  47. class OperatorImpl;
  48. using OperatorImplPtr = std::shared_ptr<OperatorImpl>;
  49. class ComputeGraph : public std::enable_shared_from_this<ComputeGraph>, public AttrHolder {
  50. friend class GraphUtils;
  51. public:
  52. template <class T>
  53. using Vistor = RangeVistor<T, std::shared_ptr<ConstComputeGraph>>;
  54. explicit ComputeGraph(const std::string &name);
  55. ~ComputeGraph() override;
  56. std::string GetName() const;
  57. void SetName(const std::string &name);
  58. using AttrHolder::DelAttr;
  59. using AttrHolder::GetAttr;
  60. using AttrHolder::HasAttr;
  61. using AttrHolder::SetAttr;
  62. size_t GetAllNodesSize() const;
  63. Vistor<NodePtr> GetAllNodes() const;
  64. size_t GetDirectNodesSize() const;
  65. Vistor<NodePtr> GetDirectNode() const;
  66. Vistor<NodePtr> GetInputNodes() const;
  67. Vistor<NodePtr> GetOutputNodes() const;
  68. NodePtr FindNode(const std::string &name) const;
  69. NodePtr FindFirstNodeMatchType(const std::string &name) const;
  70. // AddNode with NodePtr
  71. NodePtr AddNode(NodePtr node);
  72. NodePtr AddNode(OpDescPtr op);
  73. NodePtr AddNode(OpDescPtr op, int64_t id); // for unserialize.
  74. NodePtr AddNodeFront(NodePtr node);
  75. NodePtr AddNodeFront(const OpDescPtr &op);
  76. NodePtr AddInputNode(NodePtr node);
  77. NodePtr AddOutputNode(NodePtr node);
  78. graphStatus RemoveNode(const NodePtr &node);
  79. graphStatus RemoveInputNode(const NodePtr &node);
  80. graphStatus RemoveOutputNode(const NodePtr &node);
  81. graphStatus RemoveConstInput(const NodePtr &node);
  82. /// Add a subgraph to this graph. The subgraph must has a parent graph and parent node,
  83. /// which means the member functions `SetParentGraph` and `SetParentNode` of the subgraph
  84. /// must be called before add it to the root graph. and subgraph->GetParentNode()->GetOwnerGraph()
  85. /// must equal to subgraph->GetOwnerGraph().
  86. /// The subgraphs can only be added to a *root graph*. A root graph is a graph without any parent graph.
  87. /// The subgraph's name SHOULD(not must) be the same as the parameter `name`
  88. graphStatus AddSubgraph(const std::string &name, const std::shared_ptr<ComputeGraph> &subgraph);
  89. graphStatus AddSubgraph(const std::shared_ptr<ComputeGraph> &subgraph);
  90. void RemoveSubgraph(const std::string &name);
  91. void RemoveSubgraph(const std::shared_ptr<ComputeGraph> &subgraph);
  92. std::shared_ptr<ComputeGraph> GetSubgraph(const std::string &name) const;
  93. std::vector<std::shared_ptr<ComputeGraph>> GetAllSubgraphs() const;
  94. // obsolete
  95. std::shared_ptr<ComputeGraph> AddSubGraph(std::shared_ptr<ComputeGraph> sub_graph);
  96. // obsolete
  97. graphStatus RemoveSubGraph(const std::shared_ptr<ComputeGraph> &sub_graph);
  98. ///
  99. /// @brief Update input-mapping
  100. /// @param [in] input_mapping : index_of_cur_graph_node_input -> index_of_new_graph_node_input
  101. /// @return graphStatus
  102. ///
  103. graphStatus UpdateInputMapping(const std::map<uint32_t, uint32_t> &input_mapping);
  104. ///
  105. /// @brief Update output-mapping
  106. /// @param [in] output_mapping : index_of_cur_graph_node_output -> index_of_new_graph_node_output
  107. /// @return graphStatus
  108. ///
  109. graphStatus UpdateOutputMapping(const std::map<uint32_t, uint32_t> &output_mapping);
  110. graphStatus TopologicalSorting();
  111. bool IsValid() const;
  112. void Dump() const;
  113. graphStatus IsolateNode(const NodePtr &node);
  114. graphStatus Verify();
  115. graphStatus InferShape();
  116. graphStatus InferOriginFormat();
  117. graphStatus InferShapeInNeed();
  118. graphStatus InsertEventNodes();
  119. bool operator==(const ComputeGraph &r_compute_graph) const;
  120. const std::map<std::vector<std::string>, std::vector<std::string>> &GetShareParamLayer() const {
  121. return params_share_map_;
  122. }
  123. void SetShareParamLayer(const std::map<std::vector<std::string>, std::vector<std::string>> params_share_map) {
  124. params_share_map_ = params_share_map;
  125. }
  126. void SetInputsOrder(const std::vector<std::string> &inputs_order) { inputs_order_ = inputs_order; }
  127. void SetGraphOutNodes(std::map<std::string, std::vector<int32_t>> out_nodes_map) { out_nodes_map_ = out_nodes_map; }
  128. void AppendGraphOutNodes(std::map<std::string, std::vector<int32_t>> out_nodes_map) {
  129. for (auto &item : out_nodes_map) {
  130. (void)out_nodes_map_.emplace(item.first, item.second);
  131. }
  132. }
  133. shared_ptr<ComputeGraph> GetParentGraph();
  134. void SetParentGraph(const shared_ptr<ComputeGraph> &parent);
  135. shared_ptr<Node> GetParentNode();
  136. void SetParentNode(const shared_ptr<Node> &parent);
  137. const std::map<std::string, std::vector<int32_t>> &GetGraphOutNodes() const { return out_nodes_map_; }
  138. void SetOrigGraph(ComputeGraphPtr orig_graph) { origGraph_ = orig_graph; }
  139. ComputeGraphPtr GetOrigGraph(void) { return origGraph_; }
  140. void SetOutputSize(uint32_t size) { output_size_ = size; }
  141. uint32_t GetOutputSize() const { return output_size_; }
  142. void SetInputSize(uint32_t size) { input_size_ = size; }
  143. uint32_t GetInputSize() const { return input_size_; }
  144. ///
  145. /// Set is need train iteration.
  146. /// If set true, it means this graph need to be run iteration some
  147. /// times(according variant "npu_runconfig/iterations_per_loop").
  148. /// @param need_iteration is need iteration
  149. ///
  150. void SetNeedIteration(bool need_iteration) { need_iteration_ = need_iteration; }
  151. void SetUserDefOutput(const std::string &output_name);
  152. const std::string GetOutput();
  153. ///
  154. /// Get is need train iteration.
  155. /// @return is need iteration
  156. ///
  157. bool GetNeedIteration() const { return need_iteration_; }
  158. void SetGraphOpName(const std::map<uint32_t, std::string> &op_name_map) { op_name_map_ = op_name_map; }
  159. const std::map<uint32_t, std::string> &GetGraphOpName() const { return op_name_map_; }
  160. const std::map<OperatorImplPtr, NodePtr> &GetAllNodesInfo() const;
  161. void SetAllNodesInfo(const std::map<OperatorImplPtr, NodePtr> &nodes) { all_nodes_infos_ = nodes; }
  162. void SetGraphOutNodesInfo(std::vector<std::pair<NodePtr, int32_t>> &out_nodes_info) {
  163. output_nodes_info_ = out_nodes_info;
  164. }
  165. void AppendGraphOutNodesInfo(std::vector<std::pair<NodePtr, int32_t>> &out_nodes_info) {
  166. output_nodes_info_.insert(output_nodes_info_.end(), out_nodes_info.begin(), out_nodes_info.end());
  167. }
  168. const std::vector<std::pair<NodePtr, int32_t>> &GetGraphOutNodesInfo() const { return output_nodes_info_; }
  169. void SetGraphTargetNodesInfo(const std::vector<NodePtr> &target_nodes_info) {
  170. target_nodes_info_ = target_nodes_info;
  171. }
  172. const std::vector<NodePtr> &GetGraphTargetNodesInfo() const { return target_nodes_info_; }
  173. void SetSessionID(uint64_t session_id) { session_id_ = session_id; }
  174. uint64_t GetSessionID() const { return session_id_; }
  175. void SetGraphID(uint32_t graph_id) { graph_id_ = graph_id; }
  176. uint32_t GetGraphID() const { return graph_id_; }
  177. void SaveDataFormat(ge::Format data_format) { data_format_ = data_format; }
  178. ge::Format GetDataFormat() const { return data_format_; }
  179. bool IsSummaryGraph() const { return is_summary_graph_; }
  180. void SetSummaryFlag(bool is_summary_graph) { is_summary_graph_ = is_summary_graph; }
  181. // Graph Before BFE
  182. ComputeGraphPtr origGraph_;
  183. protected:
  184. ProtoAttrMapHelper MutableAttrMap() override;
  185. ConstProtoAttrMapHelper GetAttrMap() const override;
  186. private:
  187. graphStatus DFSTopologicalSorting(std::vector<NodePtr> &node_vec, std::map<NodePtr, uint32_t> &map_in_edge_num,
  188. std::vector<NodePtr> &stack);
  189. graphStatus BFSTopologicalSorting(std::vector<NodePtr> &node_vec, std::map<NodePtr, uint32_t> &map_in_edge_num,
  190. std::deque<NodePtr> &stack);
  191. graphStatus CollectBreadthOutNode(const NodePtr &node, std::map<NodePtr, uint32_t> &map_in_edge_num,
  192. std::map<string, NodePtr> &breadth_node_map);
  193. graphStatus TopologicalSortingGraph();
  194. graphStatus SortNodes(std::vector<NodePtr> &stack, std::map<NodePtr, uint32_t> &mapInEdgeNum);
  195. Vistor<NodePtr> AllGraphNodes(std::vector<std::shared_ptr<ComputeGraph>> &subgraphs) const;
  196. size_t GetInEdgeSize(const NodePtr &node);
  197. size_t GetOutEdgeSize(const NodePtr &node);
  198. graphStatus RemoveExtraOutEdge(const NodePtr &node);
  199. bool GraphMembersAreEqual(const ComputeGraph &r_graph) const;
  200. bool GraphAttrsAreEqual(const ComputeGraph &r_graph) const;
  201. bool VectorInputNodePtrIsEqual(const std::vector<NodePtr> &r_node_ptr_vector,
  202. const std::vector<NodePtr> &l_node_ptr_vector) const;
  203. friend class ModelSerializeImp;
  204. friend class GraphDebugImp;
  205. friend class OnnxUtils;
  206. std::string name_;
  207. uint32_t graph_id_ = 0;
  208. ProtoAttrMapHelper attrs_;
  209. std::vector<NodePtr> nodes_;
  210. std::map<OperatorImplPtr, NodePtr> all_nodes_infos_;
  211. std::vector<NodePtr> target_nodes_info_;
  212. std::vector<NodePtr> input_nodes_;
  213. std::vector<std::string> inputs_order_;
  214. uint32_t input_size_ = 1;
  215. std::map<std::string, std::vector<int32_t>> out_nodes_map_;
  216. uint32_t output_size_ = 1;
  217. std::vector<std::pair<NodePtr, int32_t>> output_nodes_info_;
  218. std::vector<std::shared_ptr<ComputeGraph>> sub_graph_;
  219. std::map<std::string, std::shared_ptr<ComputeGraph>> names_to_subgraph_;
  220. std::weak_ptr<ComputeGraph> parent_graph_;
  221. std::weak_ptr<Node> parent_node_;
  222. // the members followed should not in the ComputeGraph class
  223. bool is_valid_flag_;
  224. bool is_summary_graph_ = false;
  225. // Indicates whether it is need iteration
  226. bool need_iteration_ = false;
  227. std::map<std::vector<std::string>, std::vector<std::string>> params_share_map_;
  228. // TaskIdx -> op_name Map
  229. std::map<uint32_t, std::string> op_name_map_;
  230. uint64_t session_id_ = 0;
  231. ge::Format data_format_ = ge::FORMAT_ND;
  232. };
  233. } // namespace ge
  234. #endif // INC_GRAPH_COMPUTE_GRAPH_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