code: def validate_feature_engineer(
      candidate: Union[dict, FeatureEngineer], template: FeatureEngineer
  ) -> Union[bool, dict, FeatureEngineer]:
      """Check `candidate` "feature_engineer" compatibility with `template` and sanitize `candidate`.
      This is mostly a wrapper around :func:`validate_fe_steps` to ensure different inputs are
      handled properly and to return False, rather than raising `IncompatibleCandidateError`
  
      Parameters
      ----------
      candidate: Dict, or FeatureEngineer
          Candidate "feature_engineer" to compare to `template`. If compatible with `template`, a
          sanitized version of `candidate` will be returned (described below)
      template: FeatureEngineer
          Template "feature_engineer" to which `candidate` will be compared after processing
  
      Returns
      -------
      Boolean, dict, or FeatureEngineer
          False if `candidate` is deemed incompatible with `template`. Else, a sanitized `candidate`
          with reinitialized :class:`~hyperparameter_hunter.feature_engineering.EngineerStep` steps
          and with :class:`~hyperparameter_hunter.spaces.dimensions.RejectedOptional` filling in
          missing :class:`~hyperparameter_hunter.spaces.dimensions.Categorical` steps that were
          declared as :attr:`~hyperparameter_hunter.spaces.dimensions.Categorical.optional` by the
          `template`"""
      # Extract `steps` from `candidate`
      if isinstance(candidate, FeatureEngineer):
          steps = candidate.steps
      else:  # `candidate` must be a dict
          steps = candidate["steps"]
  
      # Dataset hashes in `feature_engineer` and candidates can be ignored, since it is assumed
      #   that candidates here had matching `Environment`s
  
      try:
          steps = validate_fe_steps(steps, template)
  
          if isinstance(candidate, FeatureEngineer):
              candidate.steps = steps
          else:  # `candidate` must be a dict
              candidate["steps"] = steps
  
          return candidate
      except IncompatibleCandidateError:
          return False
  
imports: from hyperparameter_hunter.feature_engineering import EngineerStep, FeatureEngineer
  from hyperparameter_hunter.i_o.exceptions import IncompatibleCandidateError
  from hyperparameter_hunter.compat.keras_helper import keras_callback_to_dict, keras_initializer_to_dict
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.space.dimensions import Categorical, RejectedOptional
  from hyperparameter_hunter.space.space_core import Space
  from hyperparameter_hunter.utils.boltons_utils import remap, get_path
  from hyperparameter_hunter.utils.general_utils import multi_visit
  from hyperparameter_hunter.utils.optimization_utils import does_fit_in_space, get_ids_by, get_scored_params
  from copy import deepcopy
  from numbers import Number
  from pathlib import Path
  from typing import Dict, List, Tuple, Union
  import wrapt
label_desc: Use image node_id 4 for calling a global function with example usage: validate_feature_engineer(candidate, template) and returns: candidate, False