class_docstr: RenameFeatureGenerator renames the columns without altering their values.
  This can be used to avoid column name collisions when transforming the same feature in multiple ways,
  or to highlight that a feature was derived from a particular pipeline.
  
  Parameters
  ----------
  name_prefix : str, default None
      Name prefix to add to all output feature names.
  name_suffix : str, default None
      Name suffix to add to all output feature names.
  inplace : bool, default False
      If True, then the column names are renamed inplace without copying the input data.
      This will alter the input data outside of the scope of this function.
  **kwargs :
      Refer to :class:`AbstractFeatureGenerator` documentation for details on valid key word arguments.
code: def _get_renamed_features(self, X: DataFrame) -> (DataFrame, dict):
      X_columns_orig = list(X.columns)
      X_columns_new = list(X.columns)
      if self._name_prefix:
          X_columns_new = [
              self._name_prefix + column for column in X_columns_new
          ]
      if self._name_suffix:
          X_columns_new = [
              column + self._name_suffix for column in X_columns_new
          ]
      if X_columns_orig != X_columns_new:
          is_updated_name = True
      else:
          is_updated_name = False
      column_rename_map = {
          orig: new for orig, new in zip(X_columns_orig, X_columns_new)
      }
      return column_rename_map, is_updated_name
  
file_path: autogluon/features/src/autogluon/features/generators/rename.py
imports: import copy
  import logging
  from pandas import DataFrame
  from .abstract import AbstractFeatureGenerator
label_desc: Use image node_id 4 for calling the RenameFeatureGenerator obj's underlying member method code with example usage: obj._get_renamed_features(X) and returns: column_rename_map,  is_updated_name