code: def test_mask_right_padding():
      x_np, y_np = get_test_data()
      mask = np.array([[1, 1, 1], [1, 1, 0]])
  
      x = tf.keras.layers.Input(shape=x_np.shape[1:])
  
      crf_layer_outputs = CRF(5)(x, mask=tf.constant(mask))
  
      base_model = tf.keras.Model(x, crf_layer_outputs)
      model = ModelWithCRFLoss(base_model)
  
      # check shape inference
      model.compile("adam")
      old_weights = model.get_weights()
      model.fit(x_np, y_np)
      new_weights = model.get_weights()
  
      # we check that the weights were updated during the training phase.
      with pytest.raises(AssertionError):
          assert_all_equal(old_weights, new_weights)
  
      model.predict(x_np)
  
imports: import itertools
  import os
  import math
  import tempfile
  import pytest
  import numpy
  import tensorflow
  from tensorflow_addons.layers.crf import CRF
  from tensorflow_addons.text.crf import crf_log_likelihood
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 8 for calling a global function with example usage: test_mask_right_padding() without return types