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avg_pool_1d_ops.h 1.9 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 avg_pool_1d_ops.h
  18. * \brief
  19. */
  20. #ifndef OPS_BUILT_IN_OP_PROTO_INC_AVGPOOL1DOPS_H_
  21. #define OPS_BUILT_IN_OP_PROTO_INC_AVGPOOL1DOPS_H_
  22. #include "graph/operator_reg.h"
  23. namespace ge {
  24. /**
  25. *@brief Generate an auxiliary matrix . \n
  26. *@par Inputs:
  27. * @li x: A tensor. Must be one of the following types:uint8, int8,int16, int32,
  28. int64, float16, float, double.The format must be NHWC NCHW NC1HWC0.
  29. *@par Attributes:
  30. *@li ksize: Kernel size. Input type is int.
  31. *@li strides: Input type is int.
  32. *@li pads: Input type is listInt .
  33. *@li ceil_mode: Bool, default value is false.
  34. *@li count_include_pad: Bool, default value is false. \n
  35. *@par Outputs:
  36. *y_tensor: A tensor with the same types as "x" . \n
  37. *@par Third-party framework compatibility
  38. *Compatible with the TensorFlow operator Unbatch.
  39. */
  40. REG_OP(AvgPool1DAvgMatrix)
  41. .INPUT(x, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT8,
  42. DT_INT32, DT_INT64, DT_DOUBLE}))
  43. .OUTPUT(y, TensorType({DT_FLOAT, DT_FLOAT16, DT_INT8, DT_INT16, DT_UINT8,
  44. DT_INT32, DT_INT64, DT_DOUBLE}))
  45. .REQUIRED_ATTR(ksize, Int)
  46. .REQUIRED_ATTR(strides, Int)
  47. .REQUIRED_ATTR(pads, ListInt)
  48. .ATTR(ceil_mode, Bool, false)
  49. .ATTR(count_include_pad, Bool, false)
  50. .OP_END_FACTORY_REG(AvgPool1DAvgMatrix)
  51. }
  52. #endif

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