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lookup_ops.h 4.1 kB

5 years ago
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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_LOOKUP_OPS_H_
  17. #define GE_OP_LOOKUP_OPS_H_
  18. #include "graph/operator_reg.h"
  19. namespace ge {
  20. REG_OP(LookupTableImport)
  21. .INPUT(handle, TensorType({DT_RESOURCE}))
  22. .INPUT(keys, TensorType({DT_BOOL, DT_DOUBLE, \
  23. DT_FLOAT, DT_INT32, DT_INT64}))
  24. .INPUT(values, TensorType({DT_BOOL, DT_DOUBLE, \
  25. DT_FLOAT, DT_INT32, DT_INT64}))
  26. .OP_END_FACTORY_REG(LookupTableImport)
  27. REG_OP(LookupTableInsert)
  28. .INPUT(handle, TensorType({DT_RESOURCE}))
  29. .INPUT(keys, TensorType({DT_BOOL, DT_DOUBLE, DT_FLOAT, \
  30. DT_INT32, DT_INT64}))
  31. .INPUT(values, TensorType({DT_BOOL, DT_DOUBLE, DT_FLOAT, \
  32. DT_INT32, DT_INT64}))
  33. .OP_END_FACTORY_REG(LookupTableInsert)
  34. REG_OP(LookupTableExport)
  35. .INPUT(handle, TensorType({DT_RESOURCE}))
  36. .OUTPUT(keys, TensorType({DT_BOOL, DT_DOUBLE, DT_FLOAT, \
  37. DT_INT32, DT_INT64}))
  38. .OUTPUT(values, TensorType({DT_BOOL, DT_DOUBLE, DT_FLOAT, \
  39. DT_INT32,DT_INT64}))
  40. .REQUIRED_ATTR(Tkeys, Type)
  41. .REQUIRED_ATTR(Tvalues, Type)
  42. .OP_END_FACTORY_REG(LookupTableExport)
  43. REG_OP(LookupTableSize)
  44. .INPUT(handle, TensorType({DT_RESOURCE}))
  45. .OUTPUT(size, TensorType({DT_INT64}))
  46. .OP_END_FACTORY_REG(LookupTableSize)
  47. REG_OP(LookupTableFind)
  48. .INPUT(handle, TensorType({DT_RESOURCE}))
  49. .INPUT(keys, TensorType({DT_DOUBLE, DT_FLOAT, \
  50. DT_INT32, DT_INT64}))
  51. .INPUT(default_value, TensorType({DT_DOUBLE, DT_FLOAT, \
  52. DT_INT32, DT_INT64}))
  53. .OUTPUT(values, TensorType({DT_DOUBLE, DT_FLOAT, DT_INT32, \
  54. DT_INT64}))
  55. .REQUIRED_ATTR(Tout, Type)
  56. .OP_END_FACTORY_REG(LookupTableFind)
  57. REG_OP(HashTable)
  58. .OUTPUT(handle, TensorType({DT_RESOURCE}))
  59. .ATTR(container, String, "")
  60. .ATTR(shared_name, String, "")
  61. .ATTR(use_node_name_sharing, Bool, false)
  62. .REQUIRED_ATTR(key_dtype, Type)
  63. .REQUIRED_ATTR(value_dtype, Type)
  64. .OP_END_FACTORY_REG(HashTable)
  65. REG_OP(InitializeTable)
  66. .INPUT(handle, TensorType({DT_RESOURCE}))
  67. .INPUT(keys, TensorType({DT_INT8, DT_UINT8, DT_INT16, DT_UINT16, \
  68. DT_INT32, DT_INT64, DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
  69. .INPUT(values, TensorType({DT_INT8, DT_UINT8, DT_INT16, DT_UINT16, \
  70. DT_INT32, DT_INT64, DT_FLOAT16, DT_FLOAT, DT_DOUBLE}))
  71. .OP_END_FACTORY_REG(InitializeTable)
  72. REG_OP(MutableDenseHashTable)
  73. .INPUT(empty_key, TensorType({DT_INT32, DT_INT64}))
  74. .INPUT(deleted_key, TensorType({DT_INT32, DT_INT64}))
  75. .OUTPUT(handle, TensorType({DT_RESOURSE}))
  76. .ATTR(container, String, "")
  77. .ATTR(shared_name, String, "")
  78. .ATTR(use_node_name_sharing, Bool, false)
  79. .REQUIRED_ATTR(value_dtype, Type)
  80. .ATTR(value_shape, ListInt, {})
  81. .ATTR(initial_num_buckets, Int, 131072)
  82. .ATTR(max_load_factor, Float, 0.8)
  83. .OP_END_FACTORY_REG(MutableDenseHashTable)
  84. REG_OP(MutableHashTableOfTensors)
  85. .OUTPUT(handle, TensorType({DT_RESOURSE}))
  86. .ATTR(container, String, "")
  87. .ATTR(shared_name, String, "")
  88. .ATTR(use_node_name_sharing, Bool, false)
  89. .REQUIRED_ATTR(key_dtype, Type)
  90. .REQUIRED_ATTR(value_dtype, Type)
  91. .ATTR(value_shape, ListInt, {})
  92. .OP_END_FACTORY_REG(MutableHashTableOfTensors)
  93. REG_OP(MutableHashTable)
  94. .OUTPUT(handle, TensorType({DT_RESOURSE}))
  95. .ATTR(container, String, "")
  96. .ATTR(shared_name, String, "")
  97. .ATTR(use_node_name_sharing, Bool, false)
  98. .REQUIRED_ATTR(key_dtype, Type)
  99. .REQUIRED_ATTR(value_dtype, Type)
  100. .OP_END_FACTORY_REG(MutableHashTable)
  101. } // namespace ge
  102. #endif // GE_OP_LOOKUP_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

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