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subgraph_executor.h 4.6 kB

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. /**
  35. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  36. * valid after this method returned
  37. * @param inputs input tensors
  38. * @param input_desc input tensor descriptions
  39. * @return SUCCESS on success, error code otherwise
  40. */
  41. Status ExecuteAsync(const std::vector<TensorValue> &inputs,
  42. const std::vector<ConstGeTensorDescPtr> &input_desc);
  43. /**
  44. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  45. * valid after this method returned
  46. * @param inputs input tensors
  47. * @param input_desc input tensor descriptions
  48. * @return SUCCESS on success, error code otherwise
  49. */
  50. Status ExecuteAsync(const std::vector<TensorValue> &inputs,
  51. const std::vector<ConstGeTensorDescPtr> &input_desc,
  52. const std::vector<TensorValue> &outputs);
  53. /**
  54. * Execute subgraph async, output tensor address(not data) and output tensor descriptions are
  55. * valid after this method returned
  56. * @param task_context instance of TaskContext
  57. * @return SUCCESS on success, error code otherwise
  58. */
  59. Status ExecuteAsync(TaskContext &task_context);
  60. /**
  61. * Synchronize all tasks in the subgraph. output tensor data are valid after this method returned
  62. * @return SUCCESS on success, error code otherwise
  63. */
  64. Status Synchronize();
  65. /**
  66. * Get output tensors
  67. * @param outputs output tensors
  68. * @return SUCCESS on success, error code otherwise
  69. */
  70. Status GetOutputs(std::vector<TensorValue> &outputs);
  71. /**
  72. * Get output tensors and output tensor descriptions
  73. * @param outputs output tensors
  74. * @param output_desc output tensor descriptions
  75. * @return SUCCESS on success, error code otherwise
  76. */
  77. Status GetOutputs(std::vector<TensorValue> &outputs, std::vector<ConstGeTensorDescPtr> &output_desc);
  78. private:
  79. Status PrepareForExecution(GraphExecutionContext *ctx, NodeState &node_state);
  80. Status EnableOutputZeroCopy(const std::vector<TensorValue> &outputs);
  81. static Status InferShape(ShapeInferenceEngine *shape_inference_engine, NodeState &node_state);
  82. Status Init(const std::vector<TensorValue> &inputs,
  83. const std::vector<ConstGeTensorDescPtr> &input_desc);
  84. Status InitInputsForUnknownShape(const std::vector<TensorValue> &inputs,
  85. const std::vector<ConstGeTensorDescPtr> &input_desc);
  86. Status InitInputsForKnownShape(const std::vector<TensorValue> &inputs);
  87. Status ExecuteAsyncForKnownShape(const std::vector<TensorValue> &inputs);
  88. Status ScheduleTasks();
  89. Status PrepareNodes();
  90. Status LaunchTasks();
  91. Status SetOutputsToParentNode(TaskContext &task_context);
  92. const GraphItem *graph_item_;
  93. GraphExecutionContext *context_;
  94. std::unique_ptr<SubgraphContext> subgraph_context_;
  95. bool force_infer_shape_;
  96. ThreadPool pre_run_pool_;
  97. BlockingQueue<NodeState *> ready_queue_;
  98. std::unique_ptr<ShapeInferenceEngine> shape_inference_engine_;
  99. std::shared_ptr<TaskContext> known_shape_task_context_;
  100. };
  101. } // namespace hybrid
  102. } // namespace ge
  103. #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