code: def test_pytorchvideo_slowfast_r50_encoder(self):
      # instantiate video encoder from pytorchvideo
      # default model is slowfast_r50
      config = OmegaConf.structured(
          encoders.PytorchVideoEncoder.Config()
      )
      encoder = encoders.PytorchVideoEncoder(config)
      fast = torch.rand((1, 3, 32, 224, 224))
      slow = torch.rand((1, 3, 8, 224, 224))
      output = encoder([slow, fast])
      # check output tensor is the expected feature dim size
      # (bs, feature_dim)
      self.assertEqual(output.size(1), 2304)
  
imports: import tempfile
  import unittest
  import torch
  from mmf.modules import encoders
  from omegaconf import OmegaConf
  from tests.test_utils import setup_proxy, skip_if_no_pytorchvideo, skip_if_old_transformers
  from torch import nn
label_desc: Use image node_id 13 for calling the TestEncoders obj's underlying member method code with example usage: obj.test_pytorchvideo_slowfast_r50_encoder() without return types