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task_context.h 3.9 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 "hybrid/common/tensor_value.h"
  24. #include "hybrid/common/npu_memory_allocator.h"
  25. #include "hybrid/executor/rt_callback_manager.h"
  26. #include "hybrid/model/node_item.h"
  27. namespace ge {
  28. namespace hybrid {
  29. class GraphExecutionContext;
  30. class SubgraphContext;
  31. class TaskContext {
  32. public:
  33. static std::unique_ptr<TaskContext> Create(const NodeItem &node_item, GraphExecutionContext *execution_context,
  34. SubgraphContext *subgraph_context);
  35. ~TaskContext();
  36. int NumInputs() const;
  37. int NumOutputs() const;
  38. size_t NumWorkspaces() const;
  39. const NodeItem &GetNodeItem() const;
  40. const char *GetNodeName() const;
  41. TensorValue *MutableInput(int index);
  42. ConstGeTensorDescPtr GetInputDesc(int index);
  43. ConstGeTensorDescPtr GetOutputDesc(int index);
  44. GeTensorDescPtr MutableInputDesc(int index);
  45. GeTensorDescPtr MutableOutputDesc(int index);
  46. void ReleaseInput(int index);
  47. const TensorValue *GetInput(int index) const;
  48. const TensorValue *GetOutput(int index) const;
  49. TensorValue *MutableOutput(int index);
  50. TensorValue *GetVariable(const std::string &name);
  51. rtStream_t GetStream();
  52. int64_t GetSessionId() const;
  53. uint64_t GetIterationNumber() const;
  54. void NodeDone();
  55. void OnError(Status error);
  56. Status SetOutput(int index, const TensorValue &tensor);
  57. Status AllocateOutput(int index, const GeTensorDesc &tensor_desc, TensorValue **tensor,
  58. AllocationAttr *attr = nullptr);
  59. Status AllocateOutputs(AllocationAttr *attr = nullptr);
  60. Status AllocateWorkspaces();
  61. Status AllocateWorkspace(size_t size, void **buffer, void *ori_addr = nullptr);
  62. bool IsTraceEnabled() const;
  63. bool IsDumpEnabled() const;
  64. const DumpProperties &GetDumpProperties() const;
  65. const GraphExecutionContext *GetExecutionContext() { return execution_context_; }
  66. Status AllocateTensor(size_t size, TensorValue &tensor, AllocationAttr *attr = nullptr);
  67. void *MutableWorkspace(int index);
  68. const void *GetVarBaseAddr();
  69. Status RegisterCallback(const std::function<void()> &callback_fun) const;
  70. Status TryExecuteCallback(const std::function<void()> &callback_fun) const;
  71. Status PropagateOutputs();
  72. Status GetStatus() const;
  73. void SetStatus(Status status);
  74. bool IsForceInferShape() const;
  75. void SetForceInferShape(bool force_infer_shape);
  76. void *handle_ = nullptr;
  77. private:
  78. TaskContext(GraphExecutionContext *execution_context, const NodeItem *node_item, SubgraphContext *subgraph_context);
  79. static string TensorDesc2String(const GeTensorDesc &desc);
  80. Status AllocateTensor(const GeTensorDesc &tensor_desc, TensorValue &tensor, AllocationAttr *attr);
  81. const NodeItem *node_item_ = nullptr;
  82. bool force_infer_shape_ = false;
  83. GraphExecutionContext *execution_context_;
  84. SubgraphContext *subgraph_context_;
  85. TensorValue *inputs_start_ = nullptr;
  86. TensorValue *outputs_start_ = nullptr;
  87. Status status_ = SUCCESS;
  88. std::vector<void *> workspaces_;
  89. uint64_t iteration_ = 0;
  90. };
  91. } // namespace hybrid
  92. } // namespace ge
  93. #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