code: def _split_infeasible_trials(
      trials: Sequence[FrozenTrial], n_below: int
  ) -> tuple[list[FrozenTrial], list[FrozenTrial]]:
      n_below = min(n_below, len(trials))
      sorted_trials = sorted(trials, key=_get_infeasible_trial_score)
      return sorted_trials[:n_below], sorted_trials[n_below:]
  
imports: from __future__ import annotations
  import math
  from typing import Any
  from typing import Callable
  from typing import cast
  from typing import Dict
  from typing import Optional
  from typing import Sequence
  import warnings
  import numpy
  from optuna._hypervolume import WFG
  from optuna._hypervolume.hssp import _solve_hssp
  from optuna.distributions import BaseDistribution
  from optuna.distributions import CategoricalChoiceType
  from optuna.exceptions import ExperimentalWarning
  from optuna.logging import get_logger
  from optuna.samplers._base import _CONSTRAINTS_KEY
  from optuna.samplers._base import _process_constraints_after_trial
  from optuna.samplers._base import BaseSampler
  from optuna.samplers._lazy_random_state import LazyRandomState
  from optuna.samplers._random import RandomSampler
  from optuna.samplers._tpe.parzen_estimator import _ParzenEstimator
  from optuna.samplers._tpe.parzen_estimator import _ParzenEstimatorParameters
  from optuna.search_space import IntersectionSearchSpace
  from optuna.search_space.group_decomposed import _GroupDecomposedSearchSpace
  from optuna.search_space.group_decomposed import _SearchSpaceGroup
  from optuna.study import Study
  from optuna.study._study_direction import StudyDirection
  from optuna.trial import FrozenTrial
  from optuna.trial import TrialState
label_desc: Use image node_id 12 for calling a global function with example usage: _split_infeasible_trials(trials, n_below) and returns: sorted_trials,  sorted_trials