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op_task.h 7.6 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_SINGLE_OP_TASK_OP_TASK_H_
  17. #define GE_SINGLE_OP_TASK_OP_TASK_H_
  18. #include <memory>
  19. #include <string>
  20. #include <external/graph/tensor.h>
  21. #include "common/dump/dump_op.h"
  22. #include "common/dump/dump_properties.h"
  23. #include "common/ge_inner_error_codes.h"
  24. #include "graph/op_kernel_bin.h"
  25. #include "runtime/stream.h"
  26. #include "graph/node.h"
  27. #include "cce/aicpu_engine_struct.h"
  28. #include "hybrid/node_executor/aicpu/aicpu_ext_info.h"
  29. #include "init/gelib.h"
  30. namespace ge {
  31. enum OpTaskType {
  32. OP_TASK_TBE = 0,
  33. OP_TASK_AICPU,
  34. OP_TASK_AICPUCC,
  35. OP_TASK_INVALID,
  36. };
  37. class OpTask {
  38. public:
  39. OpTask() = default;
  40. virtual ~OpTask() = default;
  41. virtual Status LaunchKernel(rtStream_t stream) = 0;
  42. virtual Status UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  43. return UNSUPPORTED;
  44. }
  45. virtual Status LaunchKernel(const std::vector<void *> &inputs, const std::vector<void *> &outputs,
  46. const std::vector<void *> &workspaces, rtStream_t stream) {
  47. return UNSUPPORTED;
  48. }
  49. virtual OpTaskType GetOpTaskType() = 0;
  50. virtual const void *GetIOAddr() const = 0;
  51. const vector<int64_t> &GetWorkspaceSizes() const;
  52. void SetWorkspaceSizes(const vector<int64_t> &workspace_sizes);
  53. const OpDescPtr &GetOpdesc() const { return op_desc_; }
  54. Status OpenDump(const std::vector<uintptr_t> &io_addr, rtStream_t stream);
  55. virtual Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc, const std::vector<DataBuffer> &input_buffers,
  56. std::vector<GeTensorDesc> &output_desc, std::vector<DataBuffer> &output_buffers,
  57. rtStream_t stream) {
  58. return UNSUPPORTED;
  59. }
  60. private:
  61. std::vector<int64_t> workspace_sizes_;
  62. protected:
  63. DumpProperties dump_properties_;
  64. DumpOp dump_op_;
  65. OpDescPtr op_desc_;
  66. };
  67. class TbeOpTask : public OpTask {
  68. public:
  69. ~TbeOpTask() override;
  70. Status LaunchKernel(rtStream_t stream) override;
  71. OpTaskType GetOpTaskType() override { return OP_TASK_TBE; }
  72. const void *GetIOAddr() const override { return nullptr; }
  73. void SetSmDesc(void *sm_desc);
  74. void SetStubFunc(const std::string &name, const void *stub_func);
  75. void SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim, const OpDescPtr &op_desc);
  76. Status UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) override;
  77. Status LaunchKernel(const vector<void *> &inputs, const vector<void *> &outputs, const vector<void *> &workspaces,
  78. rtStream_t stream) override;
  79. const void *GetArgs() const;
  80. size_t GetArgSize() const;
  81. const std::string &GetStubName() const;
  82. void EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, size_t max_tiling_size);
  83. private:
  84. static Status UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor);
  85. Status UpdateNodeByShape(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc);
  86. const void *stub_func_ = nullptr;
  87. std::unique_ptr<uint8_t[]> args_;
  88. size_t arg_size_ = 0;
  89. uint32_t block_dim_ = 1;
  90. void *sm_desc_ = nullptr;
  91. std::string stub_name_;
  92. void *tiling_buffer_ = nullptr;
  93. uint32_t max_tiling_size_ = 0;
  94. std::string tiling_data_;
  95. NodePtr node_;
  96. };
  97. class AiCpuBaseTask : public OpTask {
  98. public:
  99. AiCpuBaseTask() = default;
  100. ~AiCpuBaseTask() override;
  101. const UnknowShapeOpType GetUnknownType() const { return unknown_type_; }
  102. protected:
  103. Status SetExtInfoAndType(const std::string &kernel_ext_info);
  104. Status UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc, std::vector<GeTensorDesc> &output_desc);
  105. Status UpdateOutputShape(vector<GeTensorDesc> &output_desc);
  106. Status UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc);
  107. protected:
  108. size_t num_inputs_ = 0;
  109. size_t num_outputs_ = 0;
  110. UnknowShapeOpType unknown_type_ = DEPEND_IN_SHAPE;
  111. std::unique_ptr<ge::hybrid::AicpuExtInfoHandler> aicpu_ext_handle_;
  112. void *ext_info_addr_dev_ = nullptr;
  113. };
  114. class AiCpuTask : public AiCpuBaseTask {
  115. public:
  116. AiCpuTask() = default;
  117. ~AiCpuTask() override;
  118. Status LaunchKernel(rtStream_t stream) override;
  119. OpTaskType GetOpTaskType() override { return OP_TASK_AICPU; }
  120. const void *GetIOAddr() const override;
  121. Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc, const std::vector<DataBuffer> &input_buffers,
  122. std::vector<GeTensorDesc> &output_desc, std::vector<DataBuffer> &output_buffers,
  123. rtStream_t stream) override;
  124. Status SetMemCopyTask(const domi::KernelExDef &kernel_def);
  125. private:
  126. Status SetIO(const vector<void *> &inputs, vector<void *> &outputs);
  127. // for copy task.
  128. Status InitForSummaryAndCopy();
  129. Status UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc, vector<DataBuffer> &outputs,
  130. rtStream_t stream);
  131. Status ReadResultSummaryAndPrepareMemory();
  132. Status CopyDataToHbm(vector<DataBuffer> &outputs, rtStream_t stream);
  133. Status PrepareCopyInputs(vector<DataBuffer> &outputs);
  134. Status UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc);
  135. friend class AiCpuTaskBuilder;
  136. void *workspace_addr_ = nullptr;
  137. std::string task_info_;
  138. void *args_ = nullptr;
  139. size_t arg_size_ = 0;
  140. std::string op_type_;
  141. void *io_addr_ = nullptr;
  142. bool dynamic_flag_ = false;
  143. // for copy task
  144. void *copy_task_args_buf_;
  145. void *copy_workspace_buf_;
  146. std::vector<void *> output_summary_;
  147. std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;
  148. void *copy_ioaddr_dev_;
  149. void *copy_input_release_flag_dev_;
  150. void *copy_input_data_size_dev_;
  151. void *copy_input_src_dev_;
  152. void *copy_input_dst_dev_;
  153. vector<void *> out_shape_hbm_;
  154. };
  155. class AiCpuCCTask : public AiCpuBaseTask {
  156. public:
  157. AiCpuCCTask() = default;
  158. ~AiCpuCCTask() override;
  159. AiCpuCCTask(const AiCpuCCTask &) = delete;
  160. AiCpuCCTask &operator=(const AiCpuCCTask &) = delete;
  161. Status LaunchKernel(rtStream_t stream) override;
  162. OpTaskType GetOpTaskType() override { return OP_TASK_AICPUCC; }
  163. const void *GetIOAddr() const override;
  164. const void *GetArgs() const;
  165. void SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size);
  166. void SetSoName(const std::string &so_name);
  167. void SetkernelName(const std::string &kernel_Name);
  168. void SetIoAddr(void *io_addr);
  169. size_t GetArgSize() const;
  170. Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc, const std::vector<DataBuffer> &input_buffers,
  171. std::vector<GeTensorDesc> &output_desc, std::vector<DataBuffer> &output_buffers,
  172. rtStream_t stream) override;
  173. private:
  174. friend class AiCpuCCTaskBuilder;
  175. std::string so_name_;
  176. std::string kernel_name_;
  177. std::unique_ptr<uint8_t[]> args_;
  178. size_t arg_size_ = 0;
  179. uint32_t block_dim_ = 1;
  180. void *sm_desc_ = nullptr;
  181. void *io_addr_ = nullptr;
  182. };
  183. } // namespace ge
  184. #endif // GE_SINGLE_OP_TASK_OP_TASK_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