code: def test_video_swin_transformer(self):
      embed_dim = 72
      depths = [3, 3, 6, 3]
      num_heads = [8, 16, 32, 64]
      window_size = [2, 2, 2]
      md = video_swin_transformer.create_model(
          embed_dim=embed_dim,
          depths=depths,
          num_heads=num_heads,
          window_size=window_size,
      )
      input_tensor = torch.rand(1, 3, 4, 4, 4)
      # torch.Size([144, 576, 1, 1, 1])
      out = md(input_tensor)
      self.assertTrue(out.shape == torch.Size([1, 576, 1, 1, 1]))
      features = md.forward_features(input_tensor)
      self.assertEqual(features.shape, (1, 576))
      score = md.head(features)
      self.assertEqual(score.shape, (1, 1000))
  
imports: import unittest
  import torch
  from towhee.models.video_swin_transformer import video_swin_transformer
label_desc: Use image node_id 1 for calling the VideoSwinTransformerTest obj's underlying member method code with example usage: obj.test_video_swin_transformer() without return types