code: def _fit_transform_one(
      transformer, X=None, y=None, message=None, **fit_params
  ):
      """Fit and transform the data using one transformer."""
      transformer = _fit_one(transformer, X, y, message, **fit_params)
      X, y = _transform_one(transformer, X, y)
  
      return X, y, transformer
  
imports: import platform
  import warnings
  from copy import deepcopy
  from inspect import signature
  import imblearn.pipeline
  import sklearn.pipeline
  from sklearn.base import clone
  from sklearn.utils import _print_elapsed_time
  from sklearn.utils.metaestimators import available_if
  from sklearn.utils.validation import check_memory
  from pycaret.utils._show_versions import _get_deps_info
  from pycaret.utils.generic import get_all_object_vars_and_properties, variable_return
label_desc: Use image node_id 6 for calling a global function with example usage: _fit_transform_one(transformer, X, y, message) and returns: X,  y,  transformer