code: def test_simplecnnbuilder_shapes():
      model = SimpleCNNBuilder(
          conv_layers_spec=[
              [16, 3],
              [32, 3],
              [64, 3],
              [32, 1],
              [64, 3],
              [128, 3],
              [256, 3],
              [64, 1],
          ]
      )
      model.eval()
      output_batch = model(INPUT_BATCH)
      assert output_batch.size() == (BATCH_SIZE, 64, 8, 8)
  
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 2 for calling a global function with example usage: test_simplecnnbuilder_shapes() without return types