def onShortcutUnindentWithBackspace(self):
        """Backspace pressed, unindent
        """
        assert self._qpart.textBeforeCursor().endswith(self.text())

        charsToRemove = len(self._qpart.textBeforeCursor()) % len(self.text())
        if charsToRemove == 0:
            charsToRemove = len(self.text())

        cursor = self._qpart.textCursor()
        cursor.setPosition(cursor.position() - charsToRemove, QTextCursor.KeepAnchor)
        cursor.removeSelectedText()
def batch_norm(inputs, training, data_format, name=''):
  """Performs a batch normalization using a standard set of parameters."""
  # We set fused=True for a significant performance boost. See
  # https://www.tensorflow.org/performance/performance_guide#common_fused_ops
  return tf.compat.v1.layers.batch_normalization(
      inputs=inputs,
      axis=1 if data_format == 'channels_first' else 3,
      momentum=_BATCH_NORM_DECAY,
      epsilon=_BATCH_NORM_EPSILON,
      center=True,
      scale=True,
      training=training,
      fused=True,
      name=name)