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op_tiling.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_OP_TILING_H_
  17. #define INC_REGISTER_OP_TILING_H_
  18. #include "graph/debug/ge_attr_define.h"
  19. #include "graph/node.h"
  20. #include "register/op_tiling_registry.h"
  21. #include <nlohmann/json.hpp>
  22. namespace optiling {
  23. #define REGISTER_OP_TILING_FUNC(optype, opfunc) REGISTER_OP_TILING_FUNC_UNIQ_HELPER(optype, opfunc, __COUNTER__)
  24. #define REGISTER_OP_TILING_FUNC_UNIQ_HELPER(optype, opfunc, counter) \
  25. REGISTER_OP_TILING_FUNC_UNIQ(optype, opfunc, counter)
  26. #define REGISTER_OP_TILING_FUNC_UNIQ(optype, opfunc, counter) \
  27. static OpTilingInterf g_##optype##TilingInterf##counter(#optype, opfunc)
  28. using OpTilingFuncOld =
  29. std::function<bool(const std::string &, const TeOpParas &, const nlohmann::json &, OpRunInfo &)>;
  30. class FMK_FUNC_HOST_VISIBILITY OpTilingInterf {
  31. public:
  32. OpTilingInterf(std::string op_type, OpTilingFuncOld func);
  33. ~OpTilingInterf() = default;
  34. static std::string OpTilingUuid;
  35. };
  36. extern "C" ge::graphStatus OpParaCalculate(const ge::Node &node, OpRunInfo &run_info);
  37. extern "C" ge::graphStatus OpAtomicCalculate(const ge::Node &node, OpRunInfo &run_info);
  38. } // namespace optiling
  39. #endif // INC_REGISTER_OP_TILING_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