Remove the mock dependency from TensorFlow Privacy, this is now part of the Python standard library.

PiperOrigin-RevId: 424681527

tensorflow_privacy/privacy/dp_query/restart_query_test.py

@@ -11,11 +11,12 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-"""Tests for `restart_query`."""
-from absl.testing import parameterized
-import mock
 
+import unittest
+
+from absl.testing import parameterized
 import tensorflow as tf
+
 from tensorflow_privacy.privacy.dp_query import restart_query
 from tensorflow_privacy.privacy.dp_query import tree_aggregation_query
 
@@ -77,7 +78,7 @@ class TimeRestartIndicatorTest(tf.test.TestCase, parameterized.TestCase):
     # the `PeriodicTimeRestartIndicator` to unroll the mock test.
     return_time = tf.Variable(
         1627018868.452365)  # 22:41pm PST 5:41am UTC, July 22, initialize
-    with mock.patch.object(
+    with unittest.mock.patch.object(
         tf, 'timestamp', return_value=return_time) as mock_func:
       time_stamps = [
           1627022468.452365,  # 23:41pm PST 5:41am UTC, July 22, 1 hr, False

tensorflow_privacy/privacy/optimizers/dp_optimizer_test.py

@@ -13,9 +13,9 @@
 # limitations under the License.
 
 import os
+import unittest
 
 from absl.testing import parameterized
-import mock
 import numpy as np
 import tensorflow.compat.v1 as tf
 
@@ -175,7 +175,7 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
       # Test standard deviation is close to l2_norm_clip * noise_multiplier.
       self.assertNear(np.std(grads), 2.0 * 4.0 / num_microbatches, 0.5)
 
-  @mock.patch('absl.logging.warning')
+  @unittest.mock.patch('absl.logging.warning')
   def testComputeGradientsOverrideWarning(self, mock_logging):
 
     class SimpleOptimizer(tf.train.Optimizer):

tensorflow_privacy/privacy/optimizers/dp_optimizer_vectorized_test.py

@@ -12,8 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import unittest
+
 from absl.testing import parameterized
-import mock
 import numpy as np
 import tensorflow.compat.v1 as tf
 
@@ -112,7 +113,7 @@ class DPOptimizerTest(tf.test.TestCase, parameterized.TestCase):
       # Test standard deviation is close to l2_norm_clip * noise_multiplier.
       self.assertNear(np.std(grads), 4.0 * 8.0, 0.5)
 
-  @mock.patch('absl.logging.warning')
+  @unittest.mock.patch('absl.logging.warning')
   def testComputeGradientsOverrideWarning(self, mock_logging):
 
     class SimpleOptimizer(tf.train.Optimizer):