code: def test_unmasked_viterbi_decode():
      x_np, y_np = get_test_data()
  
      transitions = np.ones([5, 5])
      boundary_value = np.ones(5)
  
      layer = CRF(
          units=5,
          use_kernel=False,  # disable kernel transform
          chain_initializer=tf.keras.initializers.Constant(transitions),
          use_boundary=True,
          boundary_initializer=tf.keras.initializers.Constant(
              boundary_value
          ),
      )
  
      decoded_sequence, _, _, _ = layer(x_np)
      decoded_sequence = decoded_sequence.numpy()
      np.testing.assert_equal(decoded_sequence, y_np)
      assert decoded_sequence.dtype == np.int32
  
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 4 for calling a global function with example usage: test_unmasked_viterbi_decode() without return types