code: def test_matching_tensor_layer():
      s1_value = np.array(
          [
              [[1, 2], [2, 3], [3, 4]],
              [[0.1, 0.2], [0.2, 0.3], [0.3, 0.4]],
          ]
      )
      s2_value = np.array([[[1, 2], [2, 3]], [[0.1, 0.2], [0.2, 0.3]]])
      s3_value = np.array(
          [
              [[1, 2], [2, 3]],
              [[0.1, 0.2], [0.2, 0.3]],
              [[0.1, 0.2], [0.2, 0.3]],
          ]
      )
      s1_tensor = K.variable(s1_value)
      s2_tensor = K.variable(s2_value)
      s3_tensor = K.variable(s3_value)
      for init_diag in [True, False]:
          model = MatchingTensorLayer(init_diag=init_diag)
          _ = K.eval(model([s1_tensor, s2_tensor]))
      with pytest.raises(ValueError):
          MatchingTensorLayer()([s1_tensor, s3_tensor])
  
file_path: MatchZoo/tests/unit_test/test_layers.py
imports: import numpy
  import pytest
  from keras import backend
  from matchzoo import layers
  from matchzoo.contrib.layers import SpatialGRU
  from matchzoo.contrib.layers import MatchingTensorLayer
label_desc: Use image node_id 3 for calling a global function with example usage: test_matching_tensor_layer() without return types