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 Real
  from typing import Any, Dict
  import numpy
  from sklearn.utils import column_or_1d
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 9 for calling a global function with example usage: _sampling_strategy_list(sampling_strategy, y, sampling_type) and returns: unknown