code: def test_torchvision_profile(
      m, verbose=False, bias_addition_split=False
  ):
      with MetaTensorMode():
          model = m()
          data = torch.rand(8, 3, 224, 224)
      meta_args = {
          "x": data,
      }
      gm = symbolic_trace(
          model,
          meta_args=meta_args,
          bias_addition_split=bias_addition_split,
      )
      symbolic_profile(gm, data, verbose=verbose)
      _check_gm_validity(gm)
  
file_path: colossalai/tests/test_analyzer/test_fx/test_symbolic_profile.py
imports: import pytest
  import torch
  from packaging import version
  from colossalai.testing.utils 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: test_torchvision_profile(m, verbose, bias_addition_split) without return types