code: def test_load_hubconf(self):
      path = os.path.join(
          os.path.dirname(os.path.realpath(__file__)),
          "..",
      )
      input_channel = 3
      input_clip_length = 2
      input_crop_size = 56
      model = torch.hub.load(
          repo_or_dir=path,
          source="local",
          model="slow_r50",
          pretrained=False,
      )
      self.assertIsNotNone(model)
  
      # Test forwarding.
      for tensor in TestResNet._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
  
imports: import itertools
  import os
  import unittest
  import numpy
  import torch
  from pytorchvideo.models.head import ResNetBasicHead
  from pytorchvideo.models.net import Net
  from pytorchvideo.models.resnet import BottleneckBlock, create_acoustic_bottleneck_block, create_acoustic_resnet, create_bottleneck_block, create_res_block, create_res_stage, create_resnet, create_resnet_with_roi_head, ResBlock, ResStage, SeparableBottleneckBlock
  from pytorchvideo.models.stem import ResNetBasicStem
  from torch import nn
label_desc: Use image node_id 6 for calling the TestResNet obj's underlying member method code with example usage: obj.test_load_hubconf() without return types