code: def __init__(
      self, smoothing=False, with_all=False, ignore_index=-1, **kwargs
  ):
      super(CELoss, self).__init__()
      if ignore_index >= 0:
          self.loss_func = nn.CrossEntropyLoss(
              reduction="mean", ignore_index=ignore_index
          )
      else:
          self.loss_func = nn.CrossEntropyLoss(reduction="mean")
      self.smoothing = smoothing
      self.with_all = with_all
  
imports: import paddle
  from paddle import nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new CELoss object from inherited base classes: nn with example: obj = CELoss(smoothing, with_all, ignore_index)