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get_data_ops.h 2.9 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 get_data_ops.h
  18. * \brief
  19. */
  20. #ifndef OPS_BUILT_IN_OP_PROTO_INC_GET_DATA_OPS_H_
  21. #define OPS_BUILT_IN_OP_PROTO_INC_GET_DATA_OPS_H_
  22. #include "graph/operator_reg.h"
  23. namespace ge {
  24. /**
  25. *@brief Binding dataset and GetNext
  26. *@par Attributes: None
  27. *@par Inputs: Dataset and GetNext operator
  28. *@par Restrictions:
  29. *Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
  30. */
  31. REG_OP(MakeIterator)
  32. .INPUT(x, TensorType::ALL())
  33. .INPUT(x1, TensorType::ALL())
  34. .ATTR(_kernel, String, "dp")
  35. .OP_END_FACTORY_REG(MakeIterator)
  36. /**
  37. *@brief Dataset iterator
  38. *@par Attributes:
  39. *output_types: Data type of output
  40. *output_shapes: Shapes of output
  41. *container: Iterator container name
  42. *shared_name: Iterator id
  43. *@par Inputs: None
  44. *@par Outputs: Dataset
  45. *@par Restrictions:
  46. *Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
  47. */
  48. REG_OP(IteratorV2)
  49. .OUTPUT(y, TensorType::ALL())
  50. .ATTR(output_types, ListInt, {})
  51. .ATTR(output_shapes,ListListInt, {{}, {}})
  52. .ATTR(container, String, "")
  53. .ATTR(shared_name, String, "")
  54. .OP_END_FACTORY_REG(IteratorV2)
  55. /**
  56. *@brief Dataset GetNext iterator
  57. *@par Attributes:
  58. *output_types: Data type of output
  59. *output_shapes: Shapes of output
  60. *output_num: Num of output
  61. *@par Inputs: Queue data
  62. *@par Outputs: Input of computer graph
  63. *@par Restrictions:
  64. *Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
  65. */
  66. REG_OP(IteratorGetNext)
  67. .INPUT(x, TensorType::ALL())
  68. .DYNAMIC_OUTPUT(y, TensorType::ALL())
  69. .ATTR(output_types, ListInt, {})
  70. .ATTR(output_shapes, ListListInt, {{},{}})
  71. .ATTR(output_num, Int, 1)
  72. .ATTR(_kernel, String, "dp")
  73. .OP_END_FACTORY_REG(IteratorGetNext)
  74. /**
  75. *@brief Device queue data area.
  76. *@par Attributes:
  77. *output_types: Data type of output
  78. *output_shapes: Shapes of output
  79. *channel_name: Channel ID corresponding to TDT
  80. *@par Inputs: None
  81. *@par Outputs: Dataset GetNext iterator
  82. *@par Restrictions:
  83. *Warning: THIS FUNCTION IS EXPERIMENTAL. Please do not use.
  84. */
  85. REG_OP(DeviceQueueDataset)
  86. .OUTPUT(y, TensorType::ALL())
  87. .ATTR(output_types, ListInt, {})
  88. .ATTR(output_shapes, ListListInt, {{},{}})
  89. .ATTR(channel_name, String, "")
  90. .ATTR(_iterator_name, String, "IteratorV2")
  91. .OP_END_FACTORY_REG(DeviceQueueDataset)
  92. } // namespace ge
  93. #endif // OPS_BUILT_IN_OP_PROTO_INC_GET_DATA_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