code: def _prep_inputs(*inputs):
      _inputs = []
  
      for inp in inputs:
          inp = deepcopy(inp)
          if torch.is_tensor(inp):
              inp = inp.to(get_accelerator().device_name())
          _inputs.append(inp)
  
      return tuple(_inputs)
  
imports: import pytest
  import torch
  import deepspeed
  from deepspeed.accelerator import get_accelerator
  from copy import deepcopy
  from unit.common import DistributedTest
label_desc: Use image node_id 2 for calling a global function with example usage: _prep_inputs() and returns: tuple