code: def test_graphsage_zero_neighbours():
      gs = GraphSAGE(
          layer_sizes=[2, 2],
          n_samples=[0, 0],
          bias=False,
          input_dim=2,
          multiplicity=1,
          normalize="none",
          kernel_initializer="ones",
      )
  
      inp = [keras.Input(shape=(i, 2)) for i in [1, 0, 0]]
      out = gs(inp)
      model = keras.Model(inputs=inp, outputs=out)
  
      x = [
          np.array([[[1.5, 1]]]),
          np.zeros((1, 0, 2)),
          np.zeros((1, 0, 2)),
      ]
  
      actual = model.predict(x)
      expected = np.array([[5, 5]])
      assert actual == pytest.approx(expected)
  
imports: from tensorflow import keras
  from tensorflow.keras import initializers, regularizers
  import tensorflow
  import numpy
  import pytest
  from stellargraph.mapper import GraphSAGENodeGenerator
  from stellargraph.layer.graphsage import GraphSAGE, MeanAggregator, MaxPoolingAggregator, MeanPoolingAggregator, AttentionalAggregator
  from ..test_utils.graphs import example_graph
  from ..None import test_utils
label_desc: Use image node_id 26 for calling a global function with example usage: test_graphsage_zero_neighbours() without return types