code: def forward(
      self, input: paddle.Tensor, target: paddle.Tensor
  ) -> paddle.Tensor:
      if len(target.shape) == len(input.shape):
          assert target.shape[1] == 1
          target = target[:, 0]
      input = input.transpose(
          [0, *[i for i in range(2, input.ndim)], 1]
      )
      return super().forward(input, target.astype("int64"))
  
file_path: PaddleSeg/contrib/MedicalSeg/nnunet/losses/dice_and_ce_loss.py
imports: import numpy
  import paddle
  from paddle import nn
  import paddle.nn.functional
  from medicalseg.cvlibs import manager
label_desc: Use image node_id 1 for calling the RobustCrossEntropyLoss obj's underlying member method code with example usage: obj.forward(input, target) and returns: super