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resource_variable_ops.h 3.2 kB

3 years ago
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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 resource_variable_ops.h
  18. * \brief
  19. */
  20. #ifndef OPS_BUILT_IN_OP_PROTO_INC_RESOURCE_VARIABLE_OPS_H_
  21. #define OPS_BUILT_IN_OP_PROTO_INC_RESOURCE_VARIABLE_OPS_H_
  22. #include "graph/operator.h"
  23. #include "graph/operator_reg.h"
  24. namespace ge {
  25. /**
  26. *@brief Creates a handle to a Variable resource. \n
  27. *@par Outputs:
  28. *y:A Tensor of type resource. \n
  29. *@par Attributes:
  30. * @li container: optional, string.
  31. * @li shared_name: optional, string.
  32. * @li dtype: required, type.
  33. * @li shape: optional, ListInt. \n
  34. *@see VarHandleOp.
  35. */
  36. REG_OP(VarHandleOp)
  37. .ATTR(container, String, "")
  38. .ATTR(shared_name, String, "")
  39. .REQUIRED_ATTR(dtype, Type)
  40. .ATTR(shape, ListInt, ge::UNKNOWN_SHAPE)
  41. .OUTPUT(y, TensorType({DT_RESOURCE}))
  42. .OP_END_FACTORY_REG(VarHandleOp)
  43. /**
  44. *@brief Assigns a new value to a variable. \n
  45. *@par Inputs:
  46. *resource:Handle to the resource in which to store the variable.
  47. *value:The value to set the new tensor to use. \n
  48. *@par Attributes:
  49. * @li dtype: required, type. \n
  50. *@see AssignVariableOp.
  51. */
  52. REG_OP(AssignVariableOp)
  53. .INPUT(resource, TensorType({DT_RESOURCE}))
  54. .INPUT(value, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, \
  55. DT_UINT16, DT_UINT8, DT_INT32, DT_INT64, DT_BOOL, DT_DOUBLE}))
  56. .REQUIRED_ATTR(dtype, Type)
  57. .OP_END_FACTORY_REG(AssignVariableOp)
  58. /**
  59. *@brief Adds a value to the current value of a variable. \n
  60. *@par Inputs:
  61. *resource:Handle to the resource in which to store the variable.
  62. *value:The value by which the variable will be incremented. \n
  63. *@par Attributes:
  64. * @li dtype: required, type. \n
  65. *@see AssignAddVariableOp.
  66. */
  67. REG_OP(AssignAddVariableOp)
  68. .INPUT(resource, TensorType({DT_RESOURCE}))
  69. .INPUT(value, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, \
  70. DT_UINT16, DT_UINT8, DT_INT32, DT_INT64, DT_BOOL, DT_DOUBLE}))
  71. .REQUIRED_ATTR(dtype, Type)
  72. .OP_END_FACTORY_REG(AssignAddVariableOp)
  73. /**
  74. *@brief Subtracts a value to the current value of a variable. \n
  75. *@par Inputs:
  76. *resource:Handle to the resource in which to store the variable.
  77. *value:The value by which the variable will be incremented. \n
  78. *@par Attributes:
  79. * @li dtype: required, type. \n
  80. *@see AssignSubVariableOp.
  81. */
  82. REG_OP(AssignSubVariableOp)
  83. .INPUT(resource, TensorType({DT_RESOURCE}))
  84. .INPUT(value, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, \
  85. DT_UINT16, DT_UINT8, DT_INT32, DT_INT64, DT_BOOL, DT_DOUBLE}))
  86. .REQUIRED_ATTR(dtype, Type)
  87. .OP_END_FACTORY_REG(AssignSubVariableOp)
  88. } // namespace ge
  89. #endif // OPS_BUILT_IN_OP_PROTO_INC_RESOURCE_VARIABLE_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