code: def postprocess(self, logits, labels):
      logits = [logits.transpose((2, 1, 0, 3, 4))]
      labels = labels.squeeze(2)
      return logits, labels
  
imports: import copy
  import math
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from medicalseg.cvlibs import manager
  from medicalseg.utils import load_pretrained_model
label_desc: Use image node_id 3 for calling the TransUNet obj's underlying member method code with example usage: obj.postprocess(logits, labels) and returns: logits,  labels