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condtake_ops.h 1.9 kB

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  1. /**
  2. * Copyright 2019 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. /*!
  17. * \file condtake_ops.h
  18. * \brief
  19. */
  20. #ifndef OPS_BUILT_IN_OP_PROTO_INC_CONDTAKE_OPS_H_
  21. #define OPS_BUILT_IN_OP_PROTO_INC_CONDTAKE_OPS_H_
  22. #include "graph/operator_reg.h"
  23. #include "graph/operator.h"
  24. namespace ge {
  25. /**
  26. *@brief Take elements from data if specific condition is satisfied on mask. \n
  27. *@par Inputs:
  28. *@li data: input tensor from which to take elements, High-dimension input would
  29. first be flattened.
  30. *@li mask: condition param; must be the same shape with data. \n
  31. *@par Attributes:
  32. *@li mode:convert by convert in Mode.
  33. *@li val:convert by <class 'float'>
  34. *@li eps:convert by <class 'float'> (default: 1e-06) \n
  35. *@par Outputs:
  36. *@li out_data: the elements taken
  37. *@li out_index: the indices corresponding to those elements
  38. *@li valid_num: elements of out_data and out_index from zeros to valid_num is valid.
  39. */
  40. REG_OP(CondTake)
  41. .INPUT(data, TensorType({DT_FLOAT}))
  42. .INPUT(mask, TensorType({DT_FLOAT}))
  43. .OUTPUT(out_data, TensorType({DT_FLOAT}))
  44. .OUTPUT(out_index, TensorType({DT_INT32}))
  45. .OUTPUT(valid_num, TensorType({DT_INT32}))
  46. .REQUIRED_ATTR(mode, String)
  47. .REQUIRED_ATTR(val, Float)
  48. .ATTR(eps, Float, 1e-06)
  49. .OP_END_FACTORY_REG(CondTake)
  50. } // namespace ge
  51. #endif // OPS_BUILT_IN_OP_PROTO_INC_CONDTAKE_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