Make crf TF 2.0 compatible (#433)

* Replace tf.get_variable with tf.Variable
* Add test case for above

Author: Squadrick

tensorflow_addons/text/crf.py

@@ -188,8 +188,9 @@ def crf_log_likelihood(inputs,
 
     # Get the transition matrix if not provided.
     if transition_params is None:
-        transition_params = tf.get_variable("transitions",
-                                            [num_tags, num_tags])
+        initializer = tf.initializers.GlorotUniform()
+        transition_params = tf.Variable(
+            initializer([num_tags, num_tags]), "transitions")
 
     sequence_scores = crf_sequence_score(inputs, tag_indices, sequence_lengths,
                                          transition_params)

tensorflow_addons/text/crf_test.py

@@ -229,6 +229,12 @@ def testCrfLogLikelihood(self):
         tf_total_log_likelihood = self.evaluate(total_log_likelihood)
         self.assertAllClose(tf_total_log_likelihood, 0.0)
 
+        # check if `transition_params = None` raises an error
+        text.crf_log_likelihood(
+            inputs=tf.expand_dims(inputs, 0),
+            tag_indices=tf.expand_dims(tag_indices, 0),
+            sequence_lengths=tf.expand_dims(sequence_lengths, 0))
+
     def testViterbiDecode(self):
         inputs = np.array([[4, 5, -3], [3, -1, 3], [-1, 2, 1], [0, 0, 0]],
                           dtype=np.float32)