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subgraph_executor.h 5.5 kB

4 years ago
4 years ago
4 years ago
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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_EXECUTOR_EXECUTOR_SUBGRAPH_EXECUTOR_H_
  17. #define GE_HYBRID_EXECUTOR_EXECUTOR_SUBGRAPH_EXECUTOR_H_
  18. #include <vector>
  19. #include "common/blocking_queue.h"
  20. #include "common/thread_pool.h"
  21. #include "hybrid/executor/subgraph_context.h"
  22. #include "hybrid/executor/node_state.h"
  23. #include "hybrid/executor/hybrid_execution_context.h"
  24. #include "hybrid/executor/worker/shape_inference_engine.h"
  25. #include "hybrid/model/graph_item.h"
  26. #include "hybrid/node_executor/task_context.h"
  27. namespace ge {
  28. namespace hybrid {
  29. // Executor for executing a subgraph
  30. class SubgraphExecutor {
  31. public:
  32. SubgraphExecutor(const GraphItem *graph_item, GraphExecutionContext *context, bool force_infer_shape = false,
  33. ThreadPool *pre_run_pool = nullptr);
  34. ~SubgraphExecutor();
  35. Status InitForPartialExecution(const std::vector<TensorValue> &inputs,
  36. const std::vector<ConstGeTensorDescPtr> &input_desc);
  37. Status PartialExecuteAsync(int task_group);
  38. void ReleaseContext() { subgraph_context_.reset(nullptr); }
  39. /**
  40. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  41. * valid after this method returned
  42. * @param inputs input tensors
  43. * @param input_desc input tensor descriptions
  44. * @return SUCCESS on success, error code otherwise
  45. */
  46. Status ExecuteAsync(const std::vector<TensorValue> &inputs,
  47. const std::vector<ConstGeTensorDescPtr> &input_desc);
  48. /**
  49. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  50. * valid after this method returned
  51. * @param inputs input tensors
  52. * @param input_desc input tensor descriptions
  53. * @return SUCCESS on success, error code otherwise
  54. */
  55. Status ExecuteAsync(const std::vector<TensorValue> &inputs,
  56. const std::vector<ConstGeTensorDescPtr> &input_desc,
  57. const std::vector<TensorValue> &outputs);
  58. /**
  59. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  60. * valid after this method returned
  61. * @param task_context instance of TaskContext
  62. * @return SUCCESS on success, error code otherwise
  63. */
  64. Status ExecuteAsync(TaskContext &task_context);
  65. /**
  66. * Synchronize all tasks in the subgraph. output tensor data are valid after this method returned
  67. * @return SUCCESS on success, error code otherwise
  68. */
  69. Status Synchronize();
  70. /**
  71. * Get output tensors
  72. * @param outputs output tensors
  73. * @return SUCCESS on success, error code otherwise
  74. */
  75. Status GetOutputs(std::vector<TensorValue> &outputs);
  76. /**
  77. * Get output tensors and output tensor descriptions
  78. * @param outputs output tensors
  79. * @param output_desc output tensor descriptions
  80. * @return SUCCESS on success, error code otherwise
  81. */
  82. Status GetOutputs(std::vector<TensorValue> &outputs, std::vector<ConstGeTensorDescPtr> &output_desc);
  83. private:
  84. Status PrepareForExecution(GraphExecutionContext *ctx, NodeState &node_state);
  85. Status EnableOutputZeroCopy(const std::vector<TensorValue> &outputs);
  86. Status InferShape(ShapeInferenceEngine *shape_inference_engine, NodeState &node_state) const;
  87. Status Init(const std::vector<TensorValue> &inputs,
  88. const std::vector<ConstGeTensorDescPtr> &input_desc);
  89. Status InitInputsForUnknownShape(const std::vector<TensorValue> &inputs,
  90. const std::vector<ConstGeTensorDescPtr> &input_desc);
  91. Status InitInputsForKnownShape(const std::vector<TensorValue> &inputs);
  92. Status ExecuteAsyncForKnownShape(const std::vector<TensorValue> &inputs);
  93. Status ScheduleTasks(int group = -1);
  94. Status PrepareNodes(int group = -1);
  95. Status LaunchTasks();
  96. Status SetOutputsToParentNode(TaskContext &task_context);
  97. Status InitCallback(NodeState *node_state, std::function<void()> &callback);
  98. Status NodeEnqueue(NodeState *node_state);
  99. Status PrepareNode(const NodeItem &node_item, int group);
  100. BlockingQueue<const NodeItem *> &GetPrepareQueue(int group);
  101. Status ScheduleNodes();
  102. Status NodeScheduled(NodeState *node_state);
  103. Status AfterPrepared(NodeState *node_state);
  104. void AfterExecuted(NodeState *node_state);
  105. void OnNodeDone(NodeState *node_state);
  106. const GraphItem *graph_item_;
  107. GraphExecutionContext *context_;
  108. std::unique_ptr<SubgraphContext> subgraph_context_;
  109. bool force_infer_shape_;
  110. ThreadPool *pre_run_pool_;
  111. bool own_thread_pool_;
  112. BlockingQueue<NodeState *> ready_queue_;
  113. std::unique_ptr<ShapeInferenceEngine> shape_inference_engine_;
  114. std::mutex mu_; // Guard for prepare_queues_.
  115. std::map<int, BlockingQueue<const NodeItem *>> prepare_queues_;
  116. BlockingQueue<NodeState *> schedule_queue_;
  117. };
  118. } // namespace hybrid
  119. } // namespace ge
  120. #endif // GE_HYBRID_EXECUTOR_EXECUTOR_SUBGRAPH_EXECUTOR_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