code: def test_in_out_tensors():
      layer_sizes = [16, 8]
      activations = ["relu", "relu"]
  
      model = GCNSupervisedGraphClassification(
          layer_sizes=layer_sizes,
          activations=activations,
          generator=generator,
      )
  
      x_in, x_out = model.in_out_tensors()
  
      assert len(x_in) == 3
      assert len(x_in[0].shape) == 3
      assert x_in[0].shape[-1] == 4  # the node feature dimensionality
      assert len(x_out.shape) == 2
      assert x_out.shape[-1] == layer_sizes[-1]
  
file_path: stellargraph/tests/layer/test_graph_classification.py
imports: import numpy
  import tensorflow
  from stellargraph.layer.graph_classification import *
  from stellargraph.layer import SortPooling
  from stellargraph.mapper import PaddedGraphGenerator, FullBatchNodeGenerator
  import pytest
  from ..test_utils.graphs import example_graph_random
  from ..None import test_utils
label_desc: Use image node_id 2 for calling a global function with example usage: test_in_out_tensors() without return types