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task_context.h 5.0 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_KERNEL_TASK_CONTEXT_H_
  17. #define GE_HYBRID_KERNEL_TASK_CONTEXT_H_
  18. #include <map>
  19. #include <mutex>
  20. #include <vector>
  21. #include "common/properties_manager.h"
  22. #include "external/ge/ge_api_error_codes.h"
  23. #include "framework/common/ge_types.h"
  24. #include "hybrid/common/tensor_value.h"
  25. #include "hybrid/common/npu_memory_allocator.h"
  26. #include "hybrid/executor/node_state.h"
  27. #include "hybrid/executor/rt_callback_manager.h"
  28. #include "hybrid/model/node_item.h"
  29. namespace ge {
  30. namespace hybrid {
  31. struct GraphExecutionContext;
  32. class SubgraphContext;
  33. class TaskContext {
  34. public:
  35. static std::unique_ptr<TaskContext> Create(NodeState *node_state,
  36. GraphExecutionContext *execution_context,
  37. SubgraphContext *subgraph_context);
  38. ~TaskContext();
  39. int NumInputs() const;
  40. int NumOutputs() const;
  41. size_t NumWorkspaces() const;
  42. const NodeItem &GetNodeItem() const;
  43. NodeState *GetNodeState() const;
  44. const char *GetNodeName() const;
  45. TensorValue *MutableInput(int index);
  46. ConstGeTensorDescPtr GetInputDesc(int index) const;
  47. ConstGeTensorDescPtr GetOutputDesc(int index) const;
  48. GeTensorDescPtr MutableInputDesc(int index) const;
  49. GeTensorDescPtr MutableOutputDesc(int index) const;
  50. void ReleaseInputsAndOutputs();
  51. bool NeedCallback();
  52. void ReleaseInput(int index);
  53. void ReleaseWorkspace();
  54. const TensorValue *GetInput(int index) const;
  55. const TensorValue *GetOutput(int index) const;
  56. TensorValue *MutableOutput(int index);
  57. TensorValue *GetVariable(const std::string &name);
  58. rtStream_t GetStream() const;
  59. int64_t GetSessionId() const;
  60. uint64_t GetIterationNumber() const;
  61. void NodeDone();
  62. void OnError(Status error);
  63. Status SetOutput(int index, const TensorValue &tensor);
  64. Status AllocateOutput(int index,
  65. const GeTensorDesc &tensor_desc,
  66. TensorValue **tensor,
  67. AllocationAttr *attr = nullptr);
  68. Status AllocateOutputs(AllocationAttr *attr = nullptr);
  69. Status AllocateWorkspaces();
  70. Status AllocateWorkspace(size_t size, void **buffer, void *ori_addr = nullptr);
  71. bool IsTraceEnabled() const;
  72. bool IsDumpEnabled() const;
  73. const DumpProperties& GetDumpProperties() const;
  74. const GraphExecutionContext *GetExecutionContext() {
  75. return execution_context_;
  76. }
  77. Status AllocateTensor(size_t size, TensorValue &tensor, AllocationAttr *attr = nullptr);
  78. void *MutableWorkspace(int index);
  79. const void *GetVarBaseAddr();
  80. Status RegisterCallback(const std::function<void()> &callback_fun) const;
  81. Status TryExecuteCallback(const std::function<void()> &callback_fun) const;
  82. Status PropagateOutputs();
  83. Status GetStatus() const;
  84. void SetStatus(Status status);
  85. uint32_t GetTaskId() const;
  86. void SetTaskId(uint32_t task_id);
  87. uint32_t GetStreamId() const;
  88. void SetStreamId(uint32_t stream_id);
  89. void SetOverFlow(bool is_over_flow);
  90. bool IsOverFlow();
  91. Status Synchronize();
  92. bool IsForceInferShape() const;
  93. void SetForceInferShape(bool force_infer_shape);
  94. void *handle_ = nullptr;
  95. const std::vector<TaskDescInfo>& GetProfilingTaskDescInfo() const { return task_desc_info; }
  96. Status SaveProfilingTaskDescInfo(uint32_t task_id, uint32_t stream_id,
  97. const std::string &task_type, uint32_t block_dim);
  98. void ClearProfilingTaskDescInfo() { task_desc_info.clear(); }
  99. private:
  100. TaskContext(GraphExecutionContext *execution_context,
  101. NodeState *node_state,
  102. SubgraphContext *subgraph_context);
  103. static string TensorDesc2String(const GeTensorDesc &desc);
  104. Status AllocateTensor(const GeTensorDesc &tensor_desc, TensorValue &tensor, AllocationAttr *attr);
  105. NodeState *node_state_ = nullptr;
  106. const NodeItem *node_item_ = nullptr;
  107. bool force_infer_shape_ = false;
  108. GraphExecutionContext *execution_context_;
  109. SubgraphContext *subgraph_context_;
  110. TensorValue *inputs_start_ = nullptr;
  111. TensorValue *outputs_start_ = nullptr;
  112. Status status_ = SUCCESS;
  113. std::vector<void *> workspaces_;
  114. uint64_t iteration_ = 0;
  115. uint32_t task_id_ = 0;
  116. uint32_t stream_id_ = 0;
  117. std::vector<TaskDescInfo> task_desc_info;
  118. bool is_over_flow_ = false;
  119. };
  120. } // namespace hybrid
  121. } // namespace ge
  122. #endif // GE_HYBRID_KERNEL_TASK_CONTEXT_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