docstr: Helper method for retrieving train/validation sentinel parameters
docstr_tok: ["Helper","method","for","retrieving","train\/validation","sentinel","parameters"]
code: def _dataset_sentinel_helper(self):
      """Helper method for retrieving train/validation sentinel parameters"""
      params = self.cross_experiment_key.parameters
      return dict(
          dataset_hash=params["train_dataset"],
          cv_type=params["cross_experiment_params"].get(
              "cv_type",
              params["cross_experiment_params"].get(
                  "cross_validation_type", None
              ),
          ),
          global_random_seed=params["cross_experiment_params"][
              "global_random_seed"
          ],
          random_seeds=params["cross_experiment_params"][
              "random_seeds"
          ],
      )
  
imports: from hyperparameter_hunter.callbacks.bases import BaseCallback
  from hyperparameter_hunter.i_o.reporting import ReportingHandler
  from hyperparameter_hunter.keys.makers import CrossExperimentKeyMaker
  from hyperparameter_hunter.metrics import format_metrics
  from hyperparameter_hunter.sentinels import DatasetSentinel
  from hyperparameter_hunter.settings import G, ASSETS_DIRNAME, RESULT_FILE_SUB_DIR_PATHS
  from hyperparameter_hunter.utils.boltons_utils import remap
  from hyperparameter_hunter.utils.file_utils import make_dirs, ParametersFromFile
  from hyperparameter_hunter.utils.general_utils import Alias
  from hyperparameter_hunter.utils.result_utils import format_predictions, default_do_full_save
  from inspect import signature, isclass
  import numpy
  import os.path
  import pandas
  from pandas.api.types import is_numeric_dtype
  from typing import List, Optional, Tuple, Union
  from sklearn.model_selection import _split
label_desc: Use image node_id 37 for calling the Environment obj's underlying member method code with example usage: obj._dataset_sentinel_helper() and returns: dict