code: def test_linear_classifier_shape():
      in_dim = 10
      out_dim = 5
      batch_size = 16
      x = torch.randn(batch_size, in_dim)
      model = LinearClassifier(in_dim, out_dim)
      y = model(x)
      # model shape test
      assert model.fc.weight.size() == (out_dim, in_dim)
      # output shape test
      assert y.shape == (batch_size, out_dim)
  
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 2 for calling a global function with example usage: test_linear_classifier_shape() without return types