code: def _gpm_fast(x1: str, x2: str) -> float:
      return SequenceMatcher(None, str(x1), str(x2)).quick_ratio()
  
imports: from difflib import SequenceMatcher
  from typing import Optional, Union, List
  import numpy
  import pandas
  from sklearn.utils.validation import check_is_fitted
  from feature_engine._docstrings.fit_attributes import _feature_names_in_docstring, _n_features_in_docstring, _variables_attribute_docstring
  from feature_engine._docstrings.init_parameters import _ignore_format_docstring, _variables_categorical_docstring
  from feature_engine._docstrings.methods import _fit_transform_docstring
  from feature_engine._docstrings.substitute import Substitution
  from feature_engine.dataframe_checks import _check_contains_na, check_X
  from feature_engine.encoding.base_encoder import CategoricalInitMixin, CategoricalMethodsMixin
label_desc: Use image node_id 1 for calling a global function with example usage: _gpm_fast(x1, x2) and returns: SequenceMatcher