class_docstr: Converts category features to int features by mapping to the category codes.
code: def _fit_transform(self, X: DataFrame, **kwargs) -> (DataFrame, dict):
      X_out = self._transform(X)
      feature_metadata_out_type_group_map_special = copy.deepcopy(
          self.feature_metadata_in.type_group_map_special
      )
      if (
          S_TEXT_AS_CATEGORY
          in feature_metadata_out_type_group_map_special
      ):
          feature_metadata_out_type_group_map_special.pop(
              S_TEXT_AS_CATEGORY
          )
      return X_out, feature_metadata_out_type_group_map_special
  
file_path: autogluon/features/src/autogluon/features/generators/label_encoder.py
imports: import copy
  import logging
  from pandas import DataFrame
  from autogluon.common.features.types import R_CATEGORY, S_TEXT_AS_CATEGORY
  from .abstract import AbstractFeatureGenerator
label_desc: Use image node_id 1 for calling the LabelEncoderFeatureGenerator obj's underlying member method code with example usage: obj._fit_transform(X) and returns: X_out,  feature_metadata_out_type_group_map_special