code: def test_load_hubconf(self):
      path = os.path.join(
          os.path.dirname(os.path.realpath(__file__)),
          "..",
      )
      input_channel = 3
      input_clip_length = 4
      input_crop_size = 56
      model = torch.hub.load(
          repo_or_dir=path,
          source="local",
          model="csn_r101",
          pretrained=False,
      )
      self.assertIsNotNone(model)
  
      # Test forwarding.
      for tensor in TestCSN._get_inputs(
          input_channel, input_clip_length, input_crop_size
      ):
          with torch.no_grad():
              if tensor.shape[1] != input_channel:
                  with self.assertRaises(RuntimeError):
                      model(tensor)
                  continue
  
file_path: pytorchvideo/tests/test_models_csn.py
imports: import itertools
  import os
  import unittest
  import numpy
  import torch
  from pytorchvideo.models.csn import create_csn
  from pytorchvideo.models.resnet import create_bottleneck_block
  from torch import nn
label_desc: Use image node_id 4 for calling the TestCSN obj's underlying member method code with example usage: obj.test_load_hubconf() without return types