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node_item.h 5.5 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 "graph/utils/node_utils.h"
  24. #include "framework/common/types.h"
  25. #include "hybrid/common/tensor_value.h"
  26. namespace ge {
  27. namespace hybrid {
  28. class NodeTask;
  29. class NodeExecutor;
  30. struct FusedSubgraph {
  31. std::map<int, std::vector<GeTensorDescPtr>> input_mapping;
  32. std::map<int, OpDescPtr> output_mapping;
  33. std::vector<NodePtr> nodes;
  34. ComputeGraphPtr graph;
  35. };
  36. bool IsControlFlowV2Op(const std::string &op_type);
  37. class OptionalMutexGuard {
  38. public:
  39. OptionalMutexGuard(std::mutex *mutex, const std::string &name);
  40. ~OptionalMutexGuard();
  41. private:
  42. std::mutex *mu_{nullptr};
  43. std::string name_;
  44. };
  45. // for caching static information across execution
  46. struct NodeItem {
  47. ~NodeItem() = default;
  48. static Status Create(const NodePtr &node, std::unique_ptr<NodeItem> &node_item);
  49. const std::string &NodeName() const {
  50. return node_name;
  51. }
  52. const std::string &NodeType() const {
  53. return node_type;
  54. }
  55. OpDescPtr GetOpDesc() const {
  56. return node->GetOpDesc();
  57. }
  58. bool IsInputShapeStatic(int index) const;
  59. GeTensorDescPtr MutableOutputDesc(int index) const;
  60. Status UpdateInputDesc(int index, const GeTensorDesc &tensor_desc);
  61. GeTensorDescPtr MutableInputDesc(int index) const;
  62. Status GetInputDesc(int index, GeTensorDesc &tensor_desc) const;
  63. Status GetOutputDesc(int index, GeTensorDesc &tensor_desc) const;
  64. Status GetCanonicalInputIndex(uint32_t index, int &canonical_index) const;
  65. bool IsControlFlowV2Op() const {
  66. return is_ctrl_flow_v2_op_;
  67. }
  68. bool IsControlFlowOp() const {
  69. return is_ctrl_flow_op_;
  70. }
  71. bool IsMergeOp() const {
  72. return is_merge_op_;
  73. }
  74. bool IsEnterOp() const {
  75. return kEnterOpTypes.count(node_type) > 0;
  76. }
  77. bool IsExitOp() const {
  78. return kExitOpTypes.count(node_type) > 0;
  79. }
  80. bool IsHcclOp() const;
  81. void SetToDynamic();
  82. void SetDataSend(NodeItem *node_item, int anchor_index);
  83. void SetCtrlSend(NodeItem *node_item, uint32_t switch_index);
  84. void SetMergeCtrl(NodeItem *node_item, uint32_t merge_index);
  85. size_t GetMergeCtrl(uint32_t merge_index) const;
  86. OptionalMutexGuard MutexGuard(const std::string &name) const {
  87. return OptionalMutexGuard(copy_mu_.get(), name + "_" + node_name);
  88. }
  89. std::string DebugString() const;
  90. NodePtr node;
  91. OpDesc *op_desc;
  92. int node_id = -1;
  93. int group = -1;
  94. int num_inputs = 0;
  95. int num_outputs = 0;
  96. int input_start = -1;
  97. int output_start = -1;
  98. bool is_dynamic = false;
  99. bool has_observer = false;
  100. bool has_optional_inputs = false;
  101. bool is_output_shape_static = true;
  102. bool is_need_force_infershape = false;
  103. UnknowShapeOpType shape_inference_type = DEPEND_IN_SHAPE;
  104. std::string node_name;
  105. std::string node_type;
  106. std::vector<ge::NodePtr> dependents_for_shape_inference;
  107. std::vector<ge::NodePtr> dependents_for_execution;
  108. std::set<int> to_const_output_id_list;
  109. // src_output_id, dst_anchor_id, dst_node
  110. std::vector<std::vector<std::pair<int, NodeItem *>>> outputs;
  111. // for linked drive
  112. bool is_root_node_ = false;
  113. bool is_ctrl_flow_v2_op_ = false;
  114. bool is_ctrl_flow_op_ = false;
  115. bool is_merge_op_ = false;
  116. bool is_enter_active_ = false;
  117. int64_t frame_index_ = -1;
  118. int64_t parent_frame_ = -1;
  119. std::set<const NodeItem *> root_ctrl_; // Recv ctrl from root node
  120. std::map<int, const NodeItem *> root_data_; // Recv data from root node
  121. std::set<const NodeItem *> enter_ctrl_; // Recv ctrl from Enter node
  122. std::map<int, const NodeItem *> enter_data_; // Recv data from Enter node
  123. std::set<const NodeItem *> data_send_; // Send data notify to
  124. std::map<const NodeItem *, int> data_recv_; // Recv data notify from
  125. std::set<const NodeItem *> ctrl_send_; // Send ctrl notify to
  126. std::set<const NodeItem *> ctrl_recv_; // Recv ctrl notify from
  127. std::vector<std::vector<const NodeItem *>> switch_groups_; // Send ctrl notify to
  128. std::shared_ptr<NodeTask> kernel_task;
  129. std::unique_ptr<FusedSubgraph> fused_subgraph;
  130. const NodeExecutor *node_executor = nullptr;
  131. std::map<int, ge::NodePtr> ref_outputs;
  132. std::map<int, int> reuse_inputs;
  133. std::map<int, int> reuse_outputs;
  134. int num_static_input_shapes = 0;
  135. bool is_profiling_report = false;
  136. private:
  137. explicit NodeItem(NodePtr node);
  138. Status Init();
  139. Status InitInputsAndOutputs();
  140. void ResolveOptionalInputs();
  141. Status ResolveDynamicState();
  142. Status ResolveStaticInputsAndOutputs();
  143. void ResolveUnknownShapeType();
  144. GeTensorDescPtr DoGetInputDesc(int index) const;
  145. std::vector<bool> is_input_shape_static_;
  146. std::vector<uint32_t> input_desc_indices_;
  147. std::shared_ptr<std::mutex> copy_mu_;
  148. mutable std::mutex mu_;
  149. };
  150. } // namespace hybrid
  151. } // namespace ge
  152. #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