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infer_data_slice_registry.h 1.8 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 INC_REGISTER_INFER_DATA_SLICE_REGISTRY_H_
  17. #define INC_REGISTER_INFER_DATA_SLICE_REGISTRY_H_
  18. #include "external/graph/ge_error_codes.h"
  19. #include "external/graph/operator.h"
  20. namespace ge {
  21. using InferDataSliceFunc = std::function<graphStatus(Operator & )>;
  22. class GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY InferDataSliceFuncRegister {
  23. public:
  24. InferDataSliceFuncRegister(const char *operator_type, const InferDataSliceFunc &infer_data_slice_func);
  25. ~InferDataSliceFuncRegister() = default;
  26. };
  27. // infer data slice func register
  28. #define IMPLEMT_INFER_DATA_SLICE(op_name, func_name) \
  29. GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY static graphStatus func_name(op::op_name &op)
  30. #define INFER_DATA_SLICE_FUNC(op_name, x) [&](Operator &v) { return x((op::op_name &)v); }
  31. #define __INFER_DATA_SLICE_FUNC_REG_IMPL__(op_name, x, n) \
  32. static const InferDataSliceFuncRegister PASTE(ids_register, n)(#op_name, x)
  33. #define INFER_DATA_SLICE_FUNC_REG(op_name, x) \
  34. __INFER_DATA_SLICE_FUNC_REG_IMPL__(op_name, INFER_DATA_SLICE_FUNC(op_name, x), __COUNTER__)
  35. } // namespace ge
  36. #endif // INC_REGISTER_INFER_DATA_SLICE_REGISTRY_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