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op_task.h 8.6 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,
  43. const vector<GeTensorDesc> &output_desc) {
  44. return UNSUPPORTED;
  45. }
  46. virtual Status LaunchKernel(const std::vector<void *> &inputs,
  47. const std::vector<void *> &outputs,
  48. const std::vector<void *> &workspaces,
  49. rtStream_t stream) {
  50. return UNSUPPORTED;
  51. }
  52. virtual OpTaskType GetOpTaskType() = 0;
  53. virtual const void *GetIOAddr() const = 0;
  54. const vector<int64_t> &GetWorkspaceSizes() const;
  55. void SetWorkspaceSizes(const vector<int64_t> &workspace_sizes);
  56. void SetModelArgs(std::string model_name, uint32_t model_id);
  57. Status GetProfilingArgs(std::string &model_name, std::string &op_name, uint32_t &model_id, uint32_t &block_dim);
  58. const OpDescPtr &GetOpdesc() const {return op_desc_;}
  59. Status OpenDump(rtStream_t stream);
  60. void SetIoAddrsForDump(const vector<uint64_t> &io_addrs_for_dump) {
  61. io_addrs_for_dump_ = io_addrs_for_dump;
  62. }
  63. virtual Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  64. const std::vector<DataBuffer> &input_buffers,
  65. std::vector<GeTensorDesc> &output_desc,
  66. std::vector<DataBuffer> &output_buffers,
  67. rtStream_t stream) {
  68. return UNSUPPORTED;
  69. }
  70. private:
  71. std::vector<int64_t> workspace_sizes_;
  72. protected:
  73. DumpProperties dump_properties_;
  74. DumpOp dump_op_;
  75. OpDescPtr op_desc_;
  76. std::string model_name_;
  77. uint32_t model_id_ = 0;
  78. uint32_t block_dim_ = 1;
  79. std::vector<uint64_t> io_addrs_for_dump_;
  80. };
  81. class TbeOpTask : public OpTask {
  82. public:
  83. ~TbeOpTask() override;
  84. Status LaunchKernel(rtStream_t stream) override;
  85. OpTaskType GetOpTaskType() override {
  86. return OP_TASK_TBE;
  87. }
  88. const void *GetIOAddr() const override {
  89. return nullptr;
  90. }
  91. void SetSmDesc(void *sm_desc);
  92. void SetStubFunc(const std::string &name, const void *stub_func);
  93. void SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim, const OpDescPtr &op_desc);
  94. Status UpdateRunInfo(const vector<GeTensorDesc> &input_desc,
  95. const vector<GeTensorDesc> &output_desc) override;
  96. Status LaunchKernel(const vector<void *> &inputs,
  97. const vector<void *> &outputs,
  98. const vector<void *> &workspaces,
  99. rtStream_t stream) override;
  100. const void *GetArgs() const;
  101. size_t GetArgSize() const;
  102. const std::string &GetStubName() const;
  103. void EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, size_t max_tiling_size);
  104. private:
  105. static Status UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor);
  106. Status UpdateNodeByShape(const vector<GeTensorDesc> &input_desc,
  107. const vector<GeTensorDesc> &output_desc);
  108. const void *stub_func_ = nullptr;
  109. std::unique_ptr<uint8_t[]> args_;
  110. size_t arg_size_ = 0;
  111. void *sm_desc_ = nullptr;
  112. std::string stub_name_;
  113. void *tiling_buffer_ = nullptr;
  114. uint32_t max_tiling_size_ = 0;
  115. std::string tiling_data_;
  116. NodePtr node_;
  117. };
  118. class AiCpuBaseTask : public OpTask {
  119. public:
  120. AiCpuBaseTask() = default;
  121. ~AiCpuBaseTask() override;
  122. const UnknowShapeOpType GetUnknownType() const { return unknown_type_; }
  123. protected:
  124. Status SetExtInfoAndType(const std::string &kernel_ext_info, uint64_t kernel_id);
  125. Status UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc,
  126. std::vector<GeTensorDesc> &output_desc,
  127. rtStream_t stream);
  128. Status UpdateOutputShape(vector<GeTensorDesc> &output_desc);
  129. Status UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc);
  130. protected:
  131. size_t num_inputs_ = 0;
  132. size_t num_outputs_ = 0;
  133. UnknowShapeOpType unknown_type_ = DEPEND_IN_SHAPE;
  134. std::unique_ptr<ge::hybrid::AicpuExtInfoHandler> aicpu_ext_handle_;
  135. void *ext_info_addr_dev_ = nullptr;
  136. };
  137. class AiCpuTask : public AiCpuBaseTask {
  138. public:
  139. AiCpuTask() = default;
  140. ~AiCpuTask() override;
  141. Status LaunchKernel(rtStream_t stream) override;
  142. OpTaskType GetOpTaskType() override {
  143. return OP_TASK_AICPU;
  144. }
  145. const void *GetIOAddr() const override;
  146. Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  147. const std::vector<DataBuffer> &input_buffers,
  148. std::vector<GeTensorDesc> &output_desc,
  149. std::vector<DataBuffer> &output_buffers,
  150. rtStream_t stream) override;
  151. Status SetMemCopyTask(const domi::KernelExDef &kernel_def);
  152. private:
  153. Status SetIO(const vector<void *> &inputs, vector<void *> &outputs);
  154. // for copy task.
  155. Status InitForSummaryAndCopy();
  156. Status UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
  157. vector<DataBuffer> &outputs,
  158. rtStream_t stream);
  159. Status ReadResultSummaryAndPrepareMemory();
  160. Status CopyDataToHbm(vector<DataBuffer> &outputs, rtStream_t stream);
  161. Status PrepareCopyInputs(vector<DataBuffer> &outputs);
  162. Status UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc);
  163. friend class AiCpuTaskBuilder;
  164. void *workspace_addr_ = nullptr;
  165. std::string task_info_;
  166. // device addr
  167. void *args_ = nullptr;
  168. size_t arg_size_ = 0;
  169. std::string op_type_;
  170. // device addr
  171. void *io_addr_ = nullptr;
  172. bool dynamic_flag_ = false;
  173. // for copy task
  174. void *copy_task_args_buf_;
  175. void *copy_workspace_buf_;
  176. std::vector<void *> output_summary_;
  177. std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;
  178. void *copy_ioaddr_dev_;
  179. void *copy_input_release_flag_dev_;
  180. void *copy_input_data_size_dev_;
  181. void *copy_input_src_dev_;
  182. void *copy_input_dst_dev_;
  183. vector<void *> out_shape_hbm_;
  184. uint64_t kernel_id_ = 0;
  185. };
  186. class AiCpuCCTask : public AiCpuBaseTask {
  187. public:
  188. AiCpuCCTask() = default;
  189. ~AiCpuCCTask() override;
  190. AiCpuCCTask(const AiCpuCCTask &) = delete;
  191. AiCpuCCTask &operator=(const AiCpuCCTask &) = delete;
  192. Status LaunchKernel(rtStream_t stream) override;
  193. OpTaskType GetOpTaskType() override { return OP_TASK_AICPUCC; }
  194. const void *GetIOAddr() const override;
  195. const void *GetArgs() const;
  196. void SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size);
  197. void SetSoName(const std::string &so_name);
  198. void SetkernelName(const std::string &kernel_Name);
  199. void SetIoAddr(void *io_addr);
  200. size_t GetArgSize() const;
  201. Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  202. const std::vector<DataBuffer> &input_buffers,
  203. std::vector<GeTensorDesc> &output_desc,
  204. std::vector<DataBuffer> &output_buffers,
  205. rtStream_t stream) override;
  206. private:
  207. friend class AiCpuCCTaskBuilder;
  208. std::string so_name_;
  209. std::string kernel_name_;
  210. std::unique_ptr<uint8_t[]> args_;
  211. size_t arg_size_ = 0;
  212. void *sm_desc_ = nullptr;
  213. void *io_addr_ = nullptr;
  214. bool is_custom_ = false;
  215. uint32_t dump_flag_ = RT_KERNEL_DEFAULT;
  216. };
  217. } // namespace ge
  218. #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