Clean up callback warnings

PiperOrigin-RevId: 328969711
Change-Id: I28109e56f38138fe75b7f0cc257b1fddc579b051

tensorflow/python/keras/callbacks.py

@@ -1264,16 +1264,6 @@ class ModelCheckpoint(Callback):
       self.save_weights_only = True
 
   def on_train_begin(self, logs=None):
-    # pylint: disable=protected-access
-    if self.model._in_multi_worker_mode:
-      logging.warning(
-          'Automatic model reloading for interrupted job was removed from '
-          'the `ModelCheckpoint` callback in multi-worker mode, please use the '
-          '`keras.callbacks.experimental.BackupAndRestore` callback instead. '
-          'See this tutorial for details: '
-          'https://www.tensorflow.org/tutorials/distribute/'
-          'multi_worker_with_keras#backupandrestore_callback.'
-      )
     if self.load_weights_on_restart:
       filepath_to_load = (
           self._get_most_recently_modified_file_matching_pattern(self.filepath))
@@ -2422,7 +2412,7 @@ class ReduceLROnPlateau(Callback):
     """Resets wait counter and cooldown counter.
     """
     if self.mode not in ['auto', 'min', 'max']:
-      logging.warning('Learning Rate Plateau Reducing mode %s is unknown, '
+      logging.warning('Learning rate reduction mode %s is unknown, '
                       'fallback to auto mode.', self.mode)
       self.mode = 'auto'
     if (self.mode == 'min' or
@@ -2443,7 +2433,7 @@ class ReduceLROnPlateau(Callback):
     logs['lr'] = K.get_value(self.model.optimizer.lr)
     current = logs.get(self.monitor)
     if current is None:
-      logging.warning('Reduce LR on plateau conditioned on metric `%s` '
+      logging.warning('Learning rate reduction is conditioned on metric `%s` '
                       'which is not available. Available metrics are: %s',
                       self.monitor, ','.join(list(logs.keys())))