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output.h 1.7 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_GE_RUNTIME_OUTPUT_H_
  17. #define GE_GE_RUNTIME_OUTPUT_H_
  18. #include <memory>
  19. #include <vector>
  20. #include "framework/ge_runtime/davinci_model.h"
  21. #include "framework/common/ge_types.h"
  22. namespace ge {
  23. namespace model_runner {
  24. class Output {
  25. public:
  26. Output(const OpInfoPtr &op_info, const std::shared_ptr<DavinciModel> &model);
  27. virtual ~Output();
  28. bool Init();
  29. bool CopyRslt(OutputData *rslt, uint32_t data_begin, uint32_t &data_index, bool support_mem_share);
  30. bool SetDataBuf(DataBuffer &data_buf, uint32_t data_begin, uint32_t &data_count, size_t i, bool support_mem_share);
  31. // Copy assignment operator and copy constructor are deleted
  32. Output &operator=(const Output &output) = delete;
  33. Output(const Output &output) = delete;
  34. protected:
  35. std::shared_ptr<DavinciModel> model_;
  36. OpInfoPtr op_info_;
  37. // Input descriptions
  38. size_t input_num_;
  39. vector<void *> v_input_data_addr_; // Init as:buf_base + op_def_->input(i));
  40. vector<uint32_t> v_input_size_;
  41. };
  42. } // namespace model_runner
  43. } // namespace ge
  44. #endif // GE_GE_RUNTIME_OUTPUT_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