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internal_ops.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 GE_OP_INTERNAL_OPS_H_
  17. #define GE_OP_INTERNAL_OPS_H_
  18. #include "graph/operator_reg.h"
  19. #include "graph/operator.h"
  20. namespace ge {
  21. /**
  22. *@brief aicpu assit help op for auxiliary matrix generation.
  23. *@par Inputs:
  24. *The input is dynamic for attribute func_name \n
  25. *@par Attributes:
  26. *@li func_name:An required param, for example "topkv2". \n
  27. *@par Outputs:
  28. *The output is dynamic for attribute func_name.
  29. */
  30. REG_OP(AssistHelp)
  31. .DYNAMIC_INPUT(x, TensorType({ DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16,
  32. DT_UINT8, DT_INT32, DT_INT64, DT_UINT32, DT_UINT64, DT_BOOL, DT_DOUBLE }))
  33. .DYNAMIC_OUTPUT(y, TensorType({ DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16,
  34. DT_UINT8, DT_INT32, DT_INT64, DT_UINT32, DT_UINT64, DT_BOOL, DT_DOUBLE}))
  35. . REQUIRED_ATTR (func_name, String)
  36. . OP_END_FACTORY_REG(AssistHelp)
  37. /**
  38. *@brief aicpu cache help for lhisi cache flush.
  39. *@par Inputs:
  40. *The input is dynamic for attribute func_name \n
  41. *@par Outputs:
  42. *The output is dynamic for attribute func_name.
  43. */
  44. REG_OP(CacheUpdate)
  45. .INPUT(x, TensorType::BasicType())
  46. .OUTPUT(x, TensorType::BasicType())
  47. .OP_END_FACTORY_REG(CacheUpdate)
  48. } // namespace ge
  49. #endif // GE_OP_INTERNAL_OPS_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