code: def test_mean_hin_zero_neighbours():
      agg = MeanHinAggregator(
          2, bias=False, act=lambda z: z, kernel_initializer="ones"
      )
      inp = [
          keras.Input(shape=(1, 2)),
          keras.Input(shape=(1, 0, 2)),
          keras.Input(shape=(1, 0, 4)),
      ]
      out = agg(inp)
  
      # Check weights added only for first input
      assert all(w is None for w in agg.w_neigh)
  
      model = keras.Model(inputs=inp, outputs=out)
  
      x = [
          np.array([[[1, 1]]]),
          np.zeros((1, 1, 0, 2)),
          np.zeros((1, 1, 0, 4)),
      ]
  
      actual = model.predict(x)
      expected = np.array([[[2, 0]]])
      assert actual == pytest.approx(expected)
  
imports: import pytest
  import numpy
  import networkx
  from tensorflow import keras
  from tensorflow.keras import regularizers
  from stellargraph import StellarGraph
  from stellargraph.layer.hinsage import *
  from stellargraph.mapper import *
  from ..test_utils.graphs import example_hin_1
  from ..None import test_utils
label_desc: Use image node_id 5 for calling a global function with example usage: test_mean_hin_zero_neighbours() without return types