docstr: Class to create sentinels representing dataset input/target values
  
  Parameters
  ----------
  dataset_type: Str
      Dataset type, suffixed with '_input', or '_target', for which a sentinel should be
      created. Acceptable values are as follows: ['train_input', 'train_target',
      'validation_input', 'validation_target', 'holdout_input', 'holdout_target']
  dataset_hash: Str
      The hash of the dataset for which a sentinel should be created that was generated while
      creating :attr:`hyperparameter_hunter.environment.Environment.cross_experiment_key`
  cv_type: Str, or None, default=None
      If None, `dataset_type` should be one of ['holdout_input', 'holdout_target']. Else,
      should be a string that is one of the following: 1) a string attribute of
      `sklearn.model_selection._split`, or 2) a hash produced while creating
      :attr:`hyperparameter_hunter.environment.Environment.cross_experiment_key`
  global_random_seed: Int, or None, default=None
      If None, `dataset_type` should be one of ['holdout_input', 'holdout_target']. If int,
      should be :attr:`hyperparameter_hunter.environment.Environment.global_random_seed`
  random_seeds: List, or None, default=None
      If None, `dataset_type` should be one of ['holdout_input', 'holdout_target']. If list,
      should be :attr:`hyperparameter_hunter.environment.Environment.random_seeds`
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code: def __init__(
      self,
      dataset_type,
      dataset_hash,
      cv_type=None,
      global_random_seed=None,
      random_seeds=None,
  ):
      """Class to create sentinels representing dataset input/target values
  
      Parameters
      ----------
      dataset_type: Str
          Dataset type, suffixed with '_input', or '_target', for which a sentinel should be
          created. Acceptable values are as follows: ['train_input', 'train_target',
          'validation_input', 'validation_target', 'holdout_input', 'holdout_target']
      dataset_hash: Str
          The hash of the dataset for which a sentinel should be created that was generated while
          creating :attr:`hyperparameter_hunter.environment.Environment.cross_experiment_key`
      cv_type: Str, or None, default=None
          If None, `dataset_type` should be one of ['holdout_input', 'holdout_target']. Else,
          should be a string that is one of the following: 1) a string attribute of
          `sklearn.model_selection._split`, or 2) a hash produced while creating
          :attr:`hyperparameter_hunter.environment.Environment.cross_experiment_key`
      global_random_seed: Int, or None, default=None
          If None, `dataset_type` should be one of ['holdout_input', 'holdout_target']. If int,
          should be :attr:`hyperparameter_hunter.environment.Environment.global_random_seed`
      random_seeds: List, or None, default=None
          If None, `dataset_type` should be one of ['holdout_input', 'holdout_target']. If list,
          should be :attr:`hyperparameter_hunter.environment.Environment.random_seeds`
      """
      self.dataset_type = dataset_type
      self.dataset_hash = dataset_hash
      self.cv_type = cv_type
      self.global_random_seed = global_random_seed
      self.random_seeds = random_seeds
      super().__init__()
  
file_path: hyperparameter_hunter/hyperparameter_hunter/sentinels.py
imports: from hyperparameter_hunter.data.data_core import BaseDataset
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.utils.boltons_utils import remap
  from abc import ABCMeta, abstractmethod
label_desc: Use image node_id 1 to create a new DatasetSentinel object from inherited base classes: Sentinel with example: obj = DatasetSentinel(dataset_type, dataset_hash, cv_type, global_random_seed, random_seeds)