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npu_loss_scale_ops.h 2.7 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_NN_LOSS_SCALE_OPS_H
  17. #define GE_OP_NN_LOSS_SCALE_OPS_H
  18. #include "graph/operator_reg.h"
  19. namespace ge {
  20. /**
  21. *@brief Computes NPU alloc float status operator function.
  22. *@par Outputs:
  23. *data: A Tensor of data value. Must be float32.
  24. */
  25. REG_OP(NPUAllocFloatStatusOperator)
  26. .OUTPUT(data, TensorType({DT_FLOAT}))
  27. .OP_END_FACTORY_REG(NPUAllocFloatStatusOperator)
  28. /**
  29. *@brief Computes NPU clear float status operator function.
  30. *@par Inputs:
  31. *addr: A Tensor of data memory address. Must be float32.
  32. *@par Outputs:
  33. *data: A Tensor of data value. Must be float32.
  34. */
  35. REG_OP(NPUClearFloatStatusOperator)
  36. .INPUT(addr, TensorType{DT_FLOAT})
  37. .OUTPUT(data, TensorType({DT_FLOAT}))
  38. .OP_END_FACTORY_REG(NPUClearFloatStatusOperator)
  39. /**
  40. *@brief Computes NPU get float status operator function.
  41. *@par Inputs:
  42. *addr: A Tensor of data memory address. Must be float32.
  43. *@par Outputs:
  44. *data: A Tensor of data value. Must be float32.
  45. */
  46. REG_OP(NPUGetFloatStatusOperator)
  47. .INPUT(addr, TensorType{DT_FLOAT})
  48. .OUTPUT(data, TensorType({DT_FLOAT}))
  49. .OP_END_FACTORY_REG(NPUGetFloatStatusOperator)
  50. /**
  51. *@brief Produces a variable with 0 in memory.
  52. *@par Outputs:
  53. *y: A Tensor of type int32, output eight numbers with a value of zero.
  54. */
  55. REG_OP(NPUAllocFloatStatus)
  56. .OUTPUT(data, TensorType({DT_FLOAT}))
  57. .OP_END_FACTORY_REG(NPUAllocFloatStatus)
  58. /**
  59. *@brief Set the value of address 0x40000 to 0 in each core.
  60. *@par Inputs:
  61. *addr: A tensor of type float32.
  62. *@par Outputs:
  63. *data: A Tensor of type float32.
  64. */
  65. REG_OP(NPUClearFloatStatus)
  66. .INPUT(addr, TensorType{DT_FLOAT})
  67. .OUTPUT(data, TensorType({DT_FLOAT}))
  68. .OP_END_FACTORY_REG(NPUClearFloatStatus)
  69. /**
  70. *@brief Get the value of address 0x40000.
  71. *@par Inputs:
  72. *addr: A tensor of type float32.
  73. *@par Outputs:
  74. *data: A Tensor of type float32.
  75. */
  76. REG_OP(NPUGetFloatStatus)
  77. .INPUT(addr, TensorType{DT_FLOAT})
  78. .OUTPUT(data, TensorType({DT_FLOAT}))
  79. .OP_END_FACTORY_REG(NPUGetFloatStatus)
  80. } // namespace ge
  81. #endif // GE_OP_NN_LOSS_SCALE_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