code: def _aggregate_score_dicts(scores):
      """Aggregate the list of dict to dict of np ndarray
  
      The aggregated output of _aggregate_score_dicts will be a list of dict
      of form [{'prec': 0.1, 'acc':1.0}, {'prec': 0.1, 'acc':1.0}, ...]
      Convert it to a dict of array {'prec': np.array([0.1 ...]), ...}
  
      Parameters
      ----------
  
      scores : list of dict
          List of dicts of the scores for all scorers. This is a flat list,
          assumed originally to be of row major order.
  
      Example
      -------
  
      >>> scores = [{'a': 1, 'b':10}, {'a': 2, 'b':2}, {'a': 3, 'b':3},
      ...           {'a': 10, 'b': 10}]                         # doctest: +SKIP
      >>> _aggregate_score_dicts(scores)                        # doctest: +SKIP
      {'a': array([1, 2, 3, 10]),
       'b': array([10, 2, 3, 10])}
      """
      return {
          key: (
              np.asarray([score[key] for score in scores])
              if isinstance(scores[0][key], numbers.Number)
              else [score[key] for score in scores]
          )
          for key in scores[0]
      }
  
imports: import numbers
  import time
  import warnings
  from collections import Counter
  from contextlib import suppress
  from functools import partial
  from numbers import Real
  from traceback import format_exc
  import numpy
  import scipy.sparse
  from joblib import logger
  from ..base import clone, is_classifier
  from ..exceptions import FitFailedWarning
  from ..metrics import check_scoring, get_scorer_names
  from ..metrics._scorer import _check_multimetric_scoring, _MultimetricScorer
  from ..preprocessing import LabelEncoder
  from ..utils import _safe_indexing, check_random_state, indexable
  from ..utils._param_validation import HasMethods, Integral, Interval, StrOptions, validate_params
  from ..utils.metaestimators import _safe_split
  from ..utils.parallel import Parallel, delayed
  from ..utils.validation import _check_fit_params, _num_samples
  from ._split import check_cv
label_desc: Use image node_id 19 for calling a global function with example usage: _aggregate_score_dicts(scores) and returns: unknown