code: def test_keras_model():
      model = tf.keras.Sequential()
      model.add(tf.keras.layers.Dense(64, activation="relu"))
      model.add(tf.keras.layers.Dense(64, activation="relu"))
      model.add(tf.keras.layers.Dense(1, activation="softmax"))
      mcc = MatthewsCorrelationCoefficient(num_classes=1)
      model.compile(
          optimizer="Adam",
          loss="binary_crossentropy",
          metrics=["accuracy", mcc],
      )
      # data preparation
      data = np.random.random((10, 1))
      labels = np.random.random((10, 1))
      labels = np.where(labels > 0.5, 1.0, 0.0)
      model.fit(data, labels, epochs=1, batch_size=32, verbose=0)
  
file_path: addons/tensorflow_addons/metrics/tests/matthews_correlation_coefficient_test.py
imports: import tensorflow
  import numpy
  from tensorflow_addons.metrics import MatthewsCorrelationCoefficient
  from sklearn.metrics import matthews_corrcoef
label_desc: Use image node_id 5 for calling a global function with example usage: test_keras_model() without return types