code: def _score(est, X, y, scorer):
      if est is FIT_FAILURE:
          return FIT_FAILURE
      if isinstance(scorer, Mapping):
          return {
              k: v(est, X) if y is None else v(est, X, y)
              for k, v in scorer.items()
          }
      return scorer(est, X) if y is None else scorer(est, X, y)
  
imports: from __future__ import absolute_import, division, print_function
  import warnings
  from collections import defaultdict
  from threading import Lock
  from timeit import default_timer
  import numpy
  import packaging.version
  from dask.base import normalize_token
  from scipy import sparse
  from scipy.stats import rankdata
  from sklearn.exceptions import FitFailedWarning
  from sklearn.pipeline import FeatureUnion, Pipeline
  from sklearn.utils.validation import check_consistent_length
  from toolz import pluck
  from .._compat import Mapping
  from .utils import _index_param_value, _num_samples, _safe_indexing, copy_estimator
label_desc: Use image node_id 13 for calling a global function with example usage: _score(est, X, y, scorer) and returns: unknown, FIT_FAILURE, unknown