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subgraph_executor.h 5.4 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. ~SubgraphExecutor();
  34. Status InitForPartialExecution(const std::vector<TensorValue> &inputs,
  35. const std::vector<ConstGeTensorDescPtr> &input_desc);
  36. Status PartialExecuteAsync(int task_group);
  37. void ReleaseContext() { subgraph_context_.reset(nullptr); }
  38. /**
  39. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  40. * valid after this method returned
  41. * @param inputs input tensors
  42. * @param input_desc input tensor descriptions
  43. * @return SUCCESS on success, error code otherwise
  44. */
  45. Status ExecuteAsync(const std::vector<TensorValue> &inputs,
  46. const std::vector<ConstGeTensorDescPtr> &input_desc);
  47. /**
  48. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  49. * valid after this method returned
  50. * @param inputs input tensors
  51. * @param input_desc input tensor descriptions
  52. * @return SUCCESS on success, error code otherwise
  53. */
  54. Status ExecuteAsync(const std::vector<TensorValue> &inputs,
  55. const std::vector<ConstGeTensorDescPtr> &input_desc,
  56. const std::vector<TensorValue> &outputs);
  57. /**
  58. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  59. * valid after this method returned
  60. * @param task_context instance of TaskContext
  61. * @return SUCCESS on success, error code otherwise
  62. */
  63. Status ExecuteAsync(TaskContext &task_context);
  64. /**
  65. * Synchronize all tasks in the subgraph. output tensor data are valid after this method returned
  66. * @return SUCCESS on success, error code otherwise
  67. */
  68. Status Synchronize();
  69. /**
  70. * Get output tensors
  71. * @param outputs output tensors
  72. * @return SUCCESS on success, error code otherwise
  73. */
  74. Status GetOutputs(std::vector<TensorValue> &outputs);
  75. /**
  76. * Get output tensors and output tensor descriptions
  77. * @param outputs output tensors
  78. * @param output_desc output tensor descriptions
  79. * @return SUCCESS on success, error code otherwise
  80. */
  81. Status GetOutputs(std::vector<TensorValue> &outputs, std::vector<ConstGeTensorDescPtr> &output_desc);
  82. private:
  83. Status PrepareForExecution(GraphExecutionContext *ctx, NodeState &node_state);
  84. Status EnableOutputZeroCopy(const std::vector<TensorValue> &outputs);
  85. Status InferShape(ShapeInferenceEngine *shape_inference_engine, NodeState &node_state) const;
  86. Status Init(const std::vector<TensorValue> &inputs,
  87. const std::vector<ConstGeTensorDescPtr> &input_desc);
  88. Status InitInputsForUnknownShape(const std::vector<TensorValue> &inputs,
  89. const std::vector<ConstGeTensorDescPtr> &input_desc);
  90. Status InitInputsForKnownShape(const std::vector<TensorValue> &inputs);
  91. Status ExecuteAsyncForKnownShape(const std::vector<TensorValue> &inputs);
  92. Status ScheduleTasks(int group = -1);
  93. Status PrepareNodes(int group = -1);
  94. Status LaunchTasks();
  95. Status SetOutputsToParentNode(TaskContext &task_context);
  96. Status InitCallback(NodeState *node_state, std::function<void()> &callback);
  97. Status NodeEnqueue(NodeState *node_state);
  98. Status PrepareNode(const NodeItem &node_item, int group);
  99. BlockingQueue<const NodeItem *> &GetPrepareQueue(int group);
  100. Status ScheduleNodes();
  101. Status NodeScheduled(NodeState *node_state);
  102. Status AfterPrepared(NodeState *node_state);
  103. void AfterExecuted(NodeState *node_state);
  104. void OnNodeDone(NodeState *node_state);
  105. const GraphItem *graph_item_;
  106. GraphExecutionContext *context_;
  107. std::unique_ptr<SubgraphContext> subgraph_context_;
  108. bool force_infer_shape_;
  109. ThreadPool pre_run_pool_;
  110. BlockingQueue<NodeState *> ready_queue_;
  111. std::unique_ptr<ShapeInferenceEngine> shape_inference_engine_;
  112. std::mutex mu_; // Guard for prepare_queues_.
  113. std::map<int, BlockingQueue<const NodeItem *>> prepare_queues_;
  114. BlockingQueue<NodeState *> schedule_queue_;
  115. };
  116. } // namespace hybrid
  117. } // namespace ge
  118. #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