code: def test_attn_agg_zero_neighbours():
      agg = AttentionalAggregator(
          4, bias=False, act="linear", kernel_initializer="ones"
      )
  
      inp1 = keras.Input(shape=(1, 2))
      inp2 = keras.Input(shape=(1, 0, 2))
  
      out = agg([inp1, inp2])
      model = keras.Model(inputs=[inp1, inp2], outputs=out)
  
      x1 = np.array([[[1, 1]]])
      x2 = np.zeros((1, 1, 0, 2))
  
      actual = model.predict([x1, x2])
      expected = np.array([[[2, 2, 2, 2]]])
      assert expected == pytest.approx(actual)
  
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 19 for calling a global function with example usage: test_attn_agg_zero_neighbours() without return types