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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<void *> &inputs,
  56. std::vector<GeTensorDesc> &output_desc, std::vector<void *> &outputs, rtStream_t stream) {
  57. return UNSUPPORTED;
  58. }
  59. private:
  60. std::vector<int64_t> workspace_sizes_;
  61. protected:
  62. DumpProperties dump_properties_;
  63. DumpOp dump_op_;
  64. OpDescPtr op_desc_;
  65. };
  66. class TbeOpTask : public OpTask {
  67. public:
  68. ~TbeOpTask() override;
  69. Status LaunchKernel(rtStream_t stream) override;
  70. OpTaskType GetOpTaskType() override { return OP_TASK_TBE; }
  71. const void *GetIOAddr() const override { return nullptr; }
  72. void SetSmDesc(void *sm_desc);
  73. void SetStubFunc(const std::string &name, const void *stub_func);
  74. void SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim, const OpDescPtr &op_desc);
  75. Status UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) override;
  76. Status LaunchKernel(const vector<void *> &inputs, const vector<void *> &outputs, const vector<void *> &workspaces,
  77. rtStream_t stream) override;
  78. const void *GetArgs() const;
  79. size_t GetArgSize() const;
  80. const std::string &GetStubName() const;
  81. void EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, size_t max_tiling_size);
  82. private:
  83. static Status UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor);
  84. Status UpdateNodeByShape(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc);
  85. const void *stub_func_ = nullptr;
  86. std::unique_ptr<uint8_t[]> args_;
  87. size_t arg_size_ = 0;
  88. uint32_t block_dim_ = 1;
  89. void *sm_desc_ = nullptr;
  90. std::string stub_name_;
  91. void *tiling_buffer_ = nullptr;
  92. uint32_t max_tiling_size_ = 0;
  93. std::string tiling_data_;
  94. NodePtr node_;
  95. };
  96. class AiCpuBaseTask : public OpTask {
  97. public:
  98. AiCpuBaseTask() = default;
  99. ~AiCpuBaseTask() override;
  100. const UnknowShapeOpType GetUnknownType() const { return unknown_type_; }
  101. protected:
  102. Status SetExtInfoAndType(const std::string &kernel_ext_info);
  103. Status UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc, std::vector<GeTensorDesc> &output_desc);
  104. Status UpdateOutputShape(vector<GeTensorDesc> &output_desc);
  105. Status UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc);
  106. protected:
  107. size_t num_inputs_ = 0;
  108. size_t num_outputs_ = 0;
  109. UnknowShapeOpType unknown_type_ = DEPEND_IN_SHAPE;
  110. std::unique_ptr<ge::hybrid::AicpuExtInfoHandler> aicpu_ext_handle_;
  111. void *ext_info_addr_dev_ = nullptr;
  112. };
  113. class AiCpuTask : public AiCpuBaseTask {
  114. public:
  115. AiCpuTask() = default;
  116. ~AiCpuTask() override;
  117. Status LaunchKernel(rtStream_t stream) override;
  118. OpTaskType GetOpTaskType() override { return OP_TASK_AICPU; }
  119. const void *GetIOAddr() const override;
  120. Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc, const std::vector<void *> &inputs,
  121. std::vector<GeTensorDesc> &output_desc, std::vector<void *> &outputs, rtStream_t stream) override;
  122. Status SetMemCopyTask(const domi::KernelExDef &kernel_def);
  123. private:
  124. Status SetIO(const vector<void *> &inputs, vector<void *> &outputs);
  125. // for copy task.
  126. Status InitForSummaryAndCopy();
  127. Status UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc, vector<void *> &outputs,
  128. rtStream_t stream);
  129. Status ReadResultSummaryAndPrepareMemory(std::vector<void *> &out_shape_hbm);
  130. Status CopyDataToHbm(vector<void *> &outputs, const std::vector<void *> &out_shape_hbm, rtStream_t stream);
  131. Status PrepareCopyInputs(vector<void *> &outputs, const std::vector<void *> &out_shape_hbm);
  132. Status UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc, const std::vector<void *> &out_shape_hbm);
  133. friend class AiCpuTaskBuilder;
  134. void *workspace_addr_ = nullptr;
  135. std::string task_info_;
  136. void *args_ = nullptr;
  137. size_t arg_size_ = 0;
  138. std::string op_type_;
  139. void *io_addr_ = nullptr;
  140. bool dynamic_flag_ = false;
  141. // for copy task
  142. void *copy_task_args_buf_;
  143. void *copy_workspace_buf_;
  144. std::vector<void *> output_summary_;
  145. std::vector<aicpu::FWKAdapter::ResultSummary> output_summary_host_;
  146. void *copy_ioaddr_dev_;
  147. void *copy_input_release_flag_dev_;
  148. void *copy_input_data_size_dev_;
  149. void *copy_input_src_dev_;
  150. void *copy_input_dst_dev_;
  151. };
  152. class AiCpuCCTask : public AiCpuBaseTask {
  153. public:
  154. AiCpuCCTask() = default;
  155. ~AiCpuCCTask() override;
  156. AiCpuCCTask(const AiCpuCCTask &) = delete;
  157. AiCpuCCTask &operator=(const AiCpuCCTask &) = delete;
  158. Status LaunchKernel(rtStream_t stream) override;
  159. OpTaskType GetOpTaskType() override { return OP_TASK_AICPUCC; }
  160. const void *GetIOAddr() const override;
  161. const void *GetArgs() const;
  162. void SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size);
  163. void SetSoName(const std::string &so_name);
  164. void SetkernelName(const std::string &kernel_Name);
  165. void SetIoAddr(void *io_addr);
  166. size_t GetArgSize() const;
  167. Status LaunchKernel(const std::vector<GeTensorDesc> &input_desc, const std::vector<void *> &inputs,
  168. std::vector<GeTensorDesc> &output_desc, std::vector<void *> &outputs, rtStream_t stream) override;
  169. private:
  170. friend class AiCpuCCTaskBuilder;
  171. std::string so_name_;
  172. std::string kernel_name_;
  173. std::unique_ptr<uint8_t[]> args_;
  174. size_t arg_size_ = 0;
  175. uint32_t block_dim_ = 1;
  176. void *sm_desc_ = nullptr;
  177. void *io_addr_ = nullptr;
  178. };
  179. } // namespace ge
  180. #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