class_docstr: A class for defining parameter distributions.
  
  Intended for robust optimization use cases. This could be used to specify the
  distribution of an environmental variable or the distribution of the input noise.
class_docstr_tok: ["A","class","for","defining","parameter","distributions",".","Intended","for","robust","optimization","use","cases",".","This","could","be","used","to","specify","the","distribution","of","an","environmental","variable","or","the","distribution","of","the","input","noise","."]
docstr: The parameters of the distribution.
docstr_tok: ["The","parameters","of","the","distribution","."]
code: def distribution_parameters(self) -> Dict[str, Any]:
      r"""The parameters of the distribution."""
      return self._distribution_parameters
  
file_path: Ax/ax/core/parameter_distribution.py
imports: from __future__ import annotations
  from copy import deepcopy
  from importlib import import_module
  from typing import Any, Dict, List, Optional, TYPE_CHECKING
  from ax.exceptions.core import UserInputError
  from ax.utils.common.base import SortableBase
label_desc: Use image node_id 4 for calling the ParameterDistribution obj's underlying member method code with example usage: obj.distribution_parameters() and returns: self