code: def test_keras_model():
      model = tf.keras.Sequential()
      model.add(layers.Dense(64, activation="relu"))
      model.add(layers.Dense(3, activation="softmax"))
      h1 = HammingLoss(mode="multiclass")
      model.compile(
          optimizer="rmsprop",
          loss="categorical_crossentropy",
          metrics=[h1],
      )
      data = np.random.random((100, 10))
      labels = np.random.random((100, 3))
      model.fit(data, labels, epochs=1, batch_size=32, verbose=0)
  
file_path: addons/tensorflow_addons/metrics/tests/hamming_test.py
imports: import numpy
  import tensorflow
  from tensorflow.keras import layers
  from tensorflow_addons.metrics import HammingLoss, hamming_distance
label_desc: Use image node_id 8 for calling a global function with example usage: test_keras_model() without return types