code: def get_potential_values(
      item: Dict[str, Any]
  ) -> List[Union[ParameterBaseTypes, List[ParameterBaseTypes]]]:
      """Returns a list of values to explore for a config parameter.
  
      Param:
          item: config parameter-specific dictionary. Considered as a leaf in the schema. Contains type, default, and
              parameter metadata, etc.
      """
      temp = []
      # Case where we're using OneOf (e.g. to allow batch size 'auto' and integers)
      if isinstance(item["type"], list):
          for property_type in item["type"]:
              temp += handle_property_type(property_type, item)
      else:
          temp += handle_property_type(item["type"], item)
  
      # Make sure values are unique. Not using set because some values are unhashable.
      unique_temp = []
      for temp_item in temp:
          if temp_item not in unique_temp:
              unique_temp.append(temp_item)
      return unique_temp
  
imports: import copy
  import random
  from collections import deque, namedtuple
  from typing import Any, Deque, Dict, List, Tuple, Union
  import pandas
  from ludwig.config_sampling.parameter_sampling import handle_property_type, ParameterBaseTypes
  from ludwig.constants import SEQUENCE, TEXT, TIMESERIES
  from ludwig.data.dataset_synthesizer import build_synthetic_dataset_df
  from ludwig.schema.model_types.base import ModelConfig
  from ludwig.types import ModelConfigDict
  from ludwig.utils.misc_utils import merge_dict
label_desc: Use image node_id 5 for calling a global function with example usage: get_potential_values(item) and returns: unique_temp