code: def test_lenet_output_shapes():
      input_channels = 3
      output_channels = 6
      additional_layers = 2
      lenet = LeNet(input_channels, output_channels, additional_layers)
      x = torch.randn(16, 3, 32, 32)
      output = lenet(x)
      assert output.shape == (16, 24, 4, 4), "Unexpected output shape"
  
file_path: pykale/tests/embed/test_image_cnn.py
imports: import pytest
  import torch
  from kale.embed.image_cnn import Flatten, Identity, LeNet, ResNet18Feature, ResNet34Feature, ResNet50Feature, ResNet101Feature, ResNet152Feature, SimpleCNNBuilder, SmallCNNFeature
label_desc: Use image node_id 4 for calling a global function with example usage: test_lenet_output_shapes() without return types