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logging_ops.h 2.8 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_LOGGING_OPS_H
  17. #define GE_OP_LOGGING_OPS_H
  18. #include "graph/operator.h"
  19. #include "graph/operator_reg.h"
  20. namespace ge {
  21. /**
  22. *@brief Provides the time since epoch in seconds.
  23. *@par Outputs:
  24. *y: A Tensor of type float64. The timestamp as a double for seconds since \n
  25. the Unix epoch.
  26. *@attention Constraints: \n
  27. *The timestamp is computed when the op is executed, not when it is added to \n
  28. the graph.
  29. *@par Third-party framework compatibility
  30. *Compatible with tensorflow Timestamp operator.
  31. */
  32. REG_OP(Timestamp)
  33. .OUTPUT(y, TensorType({DT_DOUBLE}))
  34. .OP_END_FACTORY_REG(Timestamp)
  35. /**
  36. *@brief Asserts that the given condition is true.
  37. *@par Inputs:
  38. *If input_condition evaluates to false, print the list of tensors in data. \n
  39. Inputs include: \n
  40. *@li input_condition: The condition to evaluate.
  41. *@li input_data: The tensors to print out when condition is false.
  42. *@par Attributes:
  43. *summarize: Print this many entries of each tensor.
  44. *@par Third-party framework compatibility
  45. *Compatible with tensorflow Assert operator.
  46. */
  47. REG_OP(Assert)
  48. .INPUT(input_condition, TensorType{DT_BOOL})
  49. .DYNAMIC_INPUT(input_data, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8,
  50. DT_INT16, DT_UINT16, DT_UINT8, DT_INT32, DT_INT64, DT_UINT32,
  51. DT_UINT64, DT_BOOL, DT_DOUBLE, DT_STRING}))
  52. .ATTR(summarize, Int, 3)
  53. .OP_END_FACTORY_REG(Assert)
  54. /**
  55. *@brief Prints a tensor.
  56. *@par Inputs:
  57. *x: The tensor to print, it is a dynamic_input.
  58. *Compatible with aicpu Print operator.
  59. */
  60. REG_OP(Print)
  61. .DYNAMIC_INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT16, DT_UINT8, DT_INT32,
  62. DT_INT64, DT_UINT32, DT_UINT64, DT_DOUBLE, DT_STRING}))
  63. .OP_END_FACTORY_REG(Print)
  64. /**
  65. *@brief Prints a string scalar.
  66. *@par Inputs:
  67. *The dtype of input x must be string. Inputs include: \n
  68. *x: The string scalar to print.
  69. *@par Attributes:
  70. *output_stream: A string specifying the output stream or logging level \n
  71. to print to.
  72. *@par Third-party framework compatibility
  73. *Compatible with tensorflow PrintV2 operator.
  74. */
  75. REG_OP(PrintV2)
  76. .INPUT(x, TensorType({DT_STRING}))
  77. .ATTR(output_stream, String, "stderr")
  78. .OP_END_FACTORY_REG(PrintV2)
  79. } // namespace ge
  80. #endif // GE_OP_LOGGING_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