code: def test_vcdn_forward(vcdn):
      x1 = torch.randn(2, 4)
      x2 = torch.randn(2, 4)
      x3 = torch.randn(2, 4)
      output = vcdn([x1, x2, x3])
      assert output.shape == (2, 4)
  
file_path: pykale/tests/predict/test_decode.py
imports: import pytest
  import torch
  from kale.predict.decode import LinearClassifier, MLPDecoder, VCDN
  from kale.utils.seed import set_seed
label_desc: Use image node_id 6 for calling a global function with example usage: test_vcdn_forward(vcdn) without return types