code: def _sampling_strategy_list(sampling_strategy, y, sampling_type):
      """With cleaning methods, sampling_strategy can be a list to target the
      class of interest."""
      if sampling_type != "clean-sampling":
          raise ValueError(
              "'sampling_strategy' cannot be a list for samplers "
              "which are not cleaning methods."
          )
  
      target_stats = _count_class_sample(y)
      # check that all keys in sampling_strategy are also in y
      set_diff_sampling_strategy_target = set(sampling_strategy) - set(
          target_stats.keys()
      )
      if len(set_diff_sampling_strategy_target) > 0:
          raise ValueError(
              f"The {set_diff_sampling_strategy_target} target class is/are not "
              f"present in the data."
          )
  
      return {
          class_sample: min(target_stats.values())
          for class_sample in sampling_strategy
      }
  
imports: import warnings
  from collections import OrderedDict
  from functools import wraps
  from inspect import Parameter, signature
  from numbers import Integral, Real
  import numpy
  from sklearn.base import clone
  from sklearn.neighbors import NearestNeighbors
  from sklearn.utils import check_array, column_or_1d
  from sklearn.utils.multiclass import type_of_target
  from sklearn.utils.validation import _num_samples
  from .fixes import _is_pandas_df
label_desc: Use image node_id 12 for calling a global function with example usage: _sampling_strategy_list(sampling_strategy, y, sampling_type) and returns: unknown