Remove irrelevant callbacks warning with distribute strategies.

PiperOrigin-RevId: 244263923

tensorflow/python/keras/distribute/distributed_training_utils.py

@@ -175,19 +175,6 @@ def validate_callbacks(input_callbacks, optimizer):
   """
   if input_callbacks:
     for callback in input_callbacks:
-      if not isinstance(callback,
-                        (callbacks.TensorBoard, callbacks.ReduceLROnPlateau,
-                         callbacks.LearningRateScheduler, callbacks.CSVLogger,
-                         callbacks.EarlyStopping, callbacks.ModelCheckpoint,
-                         callbacks.TerminateOnNaN, callbacks.ProgbarLogger,
-                         callbacks.History, callbacks.RemoteMonitor)):
-        logging.warning('Your input callback is not one of the predefined '
-                        'Callbacks that supports DistributionStrategy. You '
-                        'might encounter an error if you access one of the '
-                        'model\'s attributes as part of the callback since '
-                        'these attributes are not set. You can access each of '
-                        'the individual distributed models using the '
-                        '`_grouped_model` attribute of your original model.')
       if isinstance(callback, (callbacks.LearningRateScheduler,
                                callbacks.ReduceLROnPlateau)):
 

tensorflow/python/keras/distribute/distributed_training_utils_test.py

@@ -57,30 +57,6 @@ class DistributedTrainingUtilsTest(test.TestCase):
 
     self.assertEqual(0, mock_warning.call_count)
 
-  @test.mock.patch.object(logging, 'warning', autospec=True)
-  def test_validate_callbacks_custom_callback(self, mock_warning):
-
-    class CustomCallback(callbacks.Callback):
-      pass
-
-    distributed_training_utils.validate_callbacks([CustomCallback()],
-                                                  adam.Adam())
-
-    self.assertEqual(1, mock_warning.call_count)
-
-    call_args, call_kwargs = mock_warning.call_args
-
-    self.assertEqual(('Your input callback is not one of the predefined '
-                      'Callbacks that supports DistributionStrategy. You '
-                      'might encounter an error if you access one of the '
-                      'model\'s attributes as part of the callback since '
-                      'these attributes are not set. You can access each of '
-                      'the individual distributed models using the '
-                      '`_grouped_model` attribute of your original model.',),
-                     call_args)
-
-    self.assertEqual(0, len(call_kwargs))
-
 
 if __name__ == '__main__':
   test.main()