cleanup of deprecated test methods

PiperOrigin-RevId: 716240546

Author: tensorflower-gardener

tf_keras/engine/input_layer_test.py

@@ -267,31 +267,31 @@ def run_model(inp):
 
     @test_combinations.generate(test_combinations.combine(mode=["eager"]))
     def testNoMixingArgsWithTypeSpecArg(self):
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, "all other args except `name` must be None"
         ):
             input_layer_lib.Input(
                 shape=(4, 7), type_spec=tf.TensorSpec((2, 7, 32), tf.float32)
             )
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, "all other args except `name` must be None"
         ):
             input_layer_lib.Input(
                 batch_size=4, type_spec=tf.TensorSpec((7, 32), tf.float32)
             )
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, "all other args except `name` must be None"
         ):
             input_layer_lib.Input(
                 dtype=tf.int64, type_spec=tf.TensorSpec((7, 32), tf.float32)
             )
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, "all other args except `name` must be None"
         ):
             input_layer_lib.Input(
                 sparse=True, type_spec=tf.TensorSpec((7, 32), tf.float32)
             )
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, "all other args except `name` must be None"
         ):
             input_layer_lib.Input(

tf_keras/layers/normalization/batch_normalization_dtensor_test.py

@@ -120,7 +120,7 @@ def value_fn(value_context):
         )
         if training and not synchronized and renorm:
             # This is an unsupported case at the moment.
-            with self.assertRaisesRegexp(NotImplementedError, "not supported"):
+            with self.assertRaisesRegex(NotImplementedError, "not supported"):
                 self._run_bn_training_with_strategy(
                     dtensor_strategy, value_fn, bn_layer_1, run_kwargs
                 )

tf_keras/saving/legacy/saved_model/json_utils_test.py

@@ -70,7 +70,7 @@ def test_encode_decode_type_spec(self):
             "serialized": None,
         }
         string = json_utils.Encoder().encode(invalid_type_spec)
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, "No TypeSpec has been registered"
         ):
             loaded = json_utils.decode(string)

tf_keras/utils/data_utils_test.py

@@ -134,7 +134,7 @@ def test_get_file_and_validate_it(self):
             )
             os.remove(path)
 
-        with self.assertRaisesRegexp(
+        with self.assertRaisesRegex(
             ValueError, 'Please specify the "origin".*'
         ):
             _ = keras.utils.data_utils.get_file()

tf_keras/utils/dataset_utils_test.py

@@ -457,7 +457,7 @@ def test_invalid_float_left_and_right_sizes(self):
             r"^(.*?(\bleft_size\b).*?(\bshould be\b)"
             r".*?(\bwithin the range\b).*?(\b0\b).*?(\b1\b))"
         )
-        with self.assertRaisesRegexp(ValueError, expected_regex):
+        with self.assertRaisesRegex(ValueError, expected_regex):
             dataset = [
                 np.ones(shape=(200, 32, 32)),
                 np.zeros(shape=(200, 32, 32)),