code: def test_timm_models():
      for m in tmm_models:
          model = m()
          data = torch.rand(100000, 3, 224, 224, device="meta")
          model(
              MetaTensor(data, fake_device=torch.device("cpu"))
          ).sum().backward()
  
file_path: ColossalAI/tests/test_fx/test_meta/test_backward.py
imports: import pytest
  import timm.models
  import torch
  import torchvision.models
  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: test_timm_models() without return types