code: def test_load_hubconf(self):
      path = os.path.join(
          os.path.dirname(os.path.realpath(__file__)),
          "..",
      )
      for model_name in ["slowfast_r50", "slowfast_r101"]:
          model = torch.hub.load(
              repo_or_dir=path,
              source="local",
              model=model_name,
              pretrained=False,
          )
          self.assertIsNotNone(model)
  
          input_clip_length = 32
          input_crop_size = 224
          input_channel = 3
          # Test forwarding.
          for tensor in TestSlowFast._get_inputs(
              input_channel, input_clip_length, input_crop_size
          ):
              with torch.no_grad():
                  if tensor[0].shape[1] != input_channel:
                      with self.assertRaises(RuntimeError):
                          model(tensor)
                      continue
  
file_path: pytorchvideo/tests/test_models_slowfast.py
imports: import itertools
  import os
  import unittest
  from typing import Tuple
  import torch
  from pytorchvideo.models.slowfast import create_slowfast, create_slowfast_with_roi_head
  from pytorchvideo.transforms.functional import uniform_temporal_subsample_repeated
  from torch import nn
label_desc: Use image node_id 2 for calling the TestSlowFast obj's underlying member method code with example usage: obj.test_load_hubconf() without return types