code: def preprocess_cell_inputs(
      num_predecessors: int,
      *inputs: Union[List[torch.Tensor], torch.Tensor],
  ) -> List[torch.Tensor]:
      if len(inputs) == 1 and isinstance(inputs[0], list):
          processed_inputs = list(inputs[0])  # shallow copy
      else:
          processed_inputs = cast(List[torch.Tensor], list(inputs))
      assert (
          len(processed_inputs) == num_predecessors
      ), "The number of inputs must be equal to `num_predecessors`."
      return processed_inputs
  
imports: import copy
  import logging
  import warnings
  from typing import Callable, Dict, List, Union, Optional, Tuple, Sequence, Union, cast
  import torch
  import torch.nn
  from nni.mutable import Sample, label_scope
  from nni.nas.space import model_context
  from .choice import ChosenInputs, LayerChoice, InputChoice
  from .base import MutableModule
label_desc: Use image node_id 2 for calling a global function with example usage: preprocess_cell_inputs(num_predecessors) and returns: processed_inputs