code: def select_random_different_label(
      labels: torch.Tensor, n_classes: int
  ):
      # select a random label different from the given one
      for label in enumerate(labels):
          samples = torch.randint(0, n_classes, (1,))
          while samples[0] == label:
              samples = torch.randint(0, n_classes, (1,))
          yield samples[0]
  
imports: from typing import List
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: select_random_different_label(labels, n_classes) without return types