message: Delete "RuntimeWarning" it is not having the intended effect.
  These `RuntimeWarning` are being interpreted as arguments to the string formatting, raising "TypeError: not all arguments converted during string formatting" errors.
diff: @@ -424,7 +424,7 @@ class ModelCheckpoint(Callback):
  if mode not in ['auto', 'min', 'max']:
  logging.warning('ModelCheckpoint mode %s is unknown, '
  - 'fallback to auto mode.', (mode), RuntimeWarning)
  + 'fallback to auto mode.', mode)
  mode = 'auto'
  if mode == 'min':
  @@ -451,7 +451,7 @@ class ModelCheckpoint(Callback):
  current = logs.get(self.monitor)
  if current is None:
  logging.warning('Can save best model only with %s available, '
  - 'skipping.', self.monitor, RuntimeWarning)
  + 'skipping.', self.monitor)
  else:
  if self.monitor_op(current, self.best):
  if self.verbose > 0:
  @@ -515,7 +515,7 @@ class EarlyStopping(Callback):
  if mode not in ['auto', 'min', 'max']:
  logging.warning('EarlyStopping mode %s is unknown, '
  - 'fallback to auto mode.', mode, RuntimeWarning)
  + 'fallback to auto mode.', mode)
  mode = 'auto'
  if mode == 'min':
  @@ -544,7 +544,7 @@ class EarlyStopping(Callback):
  if current is None:
  logging.warning('Early stopping conditioned on metric `%s` '
  'which is not available. Available metrics are: %s',
  - self.monitor, ','.join(list(logs.keys())), RuntimeWarning)
  + self.monitor, ','.join(list(logs.keys())))
  return
  if self.monitor_op(current - self.min_delta, self.best):
  self.best = current
  @@ -898,7 +898,7 @@ class ReduceLROnPlateau(Callback):
  """
  if self.mode not in ['auto', 'min', 'max']:
  logging.warning('Learning Rate Plateau Reducing mode %s is unknown, '
  - 'fallback to auto mode.', self.mode, RuntimeWarning)
  + 'fallback to auto mode.', self.mode)
  self.mode = 'auto'
  if (self.mode == 'min' or
  (self.mode == 'auto' and 'acc' not in self.monitor)):
  @@ -920,7 +920,7 @@ class ReduceLROnPlateau(Callback):
  if current is None:
  logging.warning('Reduce LR on plateau conditioned on metric `%s` '
  'which is not available. Available metrics are: %s',
  - self.monitor, ','.join(list(logs.keys())), RuntimeWarning)
  + self.monitor, ','.join(list(logs.keys())))
  else:
  if self.in_cooldown():
  