code: def run_and_compare(model):
      x = torch.rand(2, 3, 224, 224, requires_grad=True)
      x_out = model(x)
      with MetaTensorMode():
          meta_x = torch.rand(2, 3, 224, 224, requires_grad=True)
          meta_out = model(meta_x)
      compare_all(x_out, meta_out)
      x_out.sum().backward()
      meta_out.sum().backward()
      compare_all(x.grad, meta_x.grad)
  
file_path: ColossalAI/tests/test_analyzer/test_subclasses/test_meta_mode.py
imports: import pytest
  import torch
  import torchvision.models
  from packaging import version
  from colossalai.testing import clear_cache_before_run, parameterize
  from tests.test_analyzer.test_fx.zoo import tm_models, tmm_models
label_desc: Use image node_id 2 for calling a global function with example usage: run_and_compare(model) without return types