code: def run_and_compare(
      f: Union[nn.Module, Callable],
      x: torch.Tensor,
      requires_backward=False,
  ) -> Any:
      x.requires_grad = requires_backward
      meta_x = MetaTensor(x)
      x_out, meta_out = f(x), f(meta_x)
      compare_all(x_out, meta_out)
      if requires_backward:
          x_out.sum().backward()
          meta_out.sum().backward()
          compare_all(x.grad, meta_x.grad)
  
file_path: ColossalAI/tests/test_fx/test_meta/test_aten.py
imports: from typing import Any, Callable, Union
  import pytest
  import torch
  import torch.nn
  from colossalai.fx._compatibility import is_compatible_with_meta
  from colossalai.testing import clear_cache_before_run
label_desc: Use image node_id 2 for calling a global function with example usage: run_and_compare(f, x, requires_backward) without return types