class_docstr: DetailAggregateLoss's implementation based on PaddlePaddle.
  
  The original article refers to Meituan
  Fan, Mingyuan, et al. "Rethinking BiSeNet For Real-time Semantic Segmentation."
  (https://arxiv.org/abs/2104.13188)
  
  Args:
      ignore_index (int64, optional): Specifies a target value that is ignored
          and does not contribute to the input gradient. Default ``255``.
code: def __init__(self, ignore_index=255):
      super(DetailAggregateLoss, self).__init__()
      self.ignore_index = ignore_index
      self.laplacian_kernel = paddle.to_tensor(
          [-1, -1, -1, -1, 8, -1, -1, -1, -1], dtype="float32"
      ).reshape((1, 1, 3, 3))
      self.fuse_kernel = paddle.create_parameter(
          [1, 3, 1, 1], dtype="float32"
      )
  
file_path: PaddleSeg/paddleseg/models/losses/detail_aggregate_loss.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
label_desc: Use image node_id 1 to create a new DetailAggregateLoss object from inherited base classes: nn with example: obj = DetailAggregateLoss(ignore_index)