code: def assert_tensor_sizes_match_torchvision(self, model_name):
      classy_model = build_model({"name": model_name})
      torchvision_model = getattr(torchvision.models, model_name)(
          pretrained=False
      )
      classy_sizes = self.tensor_sizes(
          classy_model.get_classy_state()["model"]["trunk"]
      )
      torchvision_sizes = self.tensor_sizes(
          torchvision_model.state_dict()
      )
      self.assertEqual(
          classy_sizes,
          torchvision_sizes,
          f"{model_name} tensor shapes do not match torchvision",
      )
  
imports: import collections
  import unittest
  import torch
  import torchvision.models
  from classy_vision.generic.util import get_torch_version
  from classy_vision.models import build_model, ResNeXt
  from test.generic.utils import compare_model_state
label_desc: Use image node_id 2 for calling the TestTorchvisionEquivalence obj's underlying member method code with example usage: obj.assert_tensor_sizes_match_torchvision(model_name) without return types