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warp_perspective_ops.h 1.8 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. /*!
  17. * \file warp_perspective_ops.h
  18. * \brief
  19. */
  20. #ifndef GE_OP_WARP_PERSPECTIVE_OPS_H_
  21. #define GE_OP_WARP_PERSPECTIVE_OPS_H_
  22. #include "graph/operator_reg.h"
  23. #include "graph/operator.h"
  24. namespace ge {
  25. /**
  26. *@brief Applies a perspective transformation to an image.
  27. *@par Inputs:
  28. *@li x: input tensor, format NCHW, type must be float.
  29. *@li matrix: transformation matrix, format ND , shape must be (N, 9), type must be float.
  30. *@par Attributes:
  31. *@li out_height:output height.
  32. *@li out_width:output width.
  33. *@li borderType:border processing way, only support BORDER_CONSTANT and BORDER_REPLICATE, default BORDER_CONSTANT.
  34. *@li constant: border processed value when borderType is BORDER_CONSTANT.
  35. *@par Outputs:
  36. *@li y: output tensor, format NCHW, type must be float.
  37. */
  38. REG_OP(WarpPerspective)
  39. .INPUT(x, TensorType({DT_FLOAT}))
  40. .INPUT(matrix, TensorType({DT_FLOAT}))
  41. .OUTPUT(y, TensorType({DT_FLOAT}))
  42. .REQUIRED_ATTR(out_height, Int)
  43. .REQUIRED_ATTR(out_width, Int)
  44. .ATTR(border_type, String, "BORDER_CONSTANT")
  45. .ATTR(constant, Float, 0)
  46. .OP_END_FACTORY_REG(WarpPerspective)
  47. } // namespace ge
  48. #endif // GE_OP_WARP_PERSPECTIVE_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