class_docstr: Specifies the parameters for a DP mechanism.
  
  MechanismType defines the kind of noise distribution.
  _noise_standard_deviation is the minimized noise standard deviation.
  (_eps, _delta) are parameters of (eps, delta)-differential privacy
class_docstr_tok: ["Specifies","the","parameters","for","a","DP","mechanism",".","MechanismType","defines","the","kind","of","noise","distribution",".","_noise_standard_deviation","is","the","minimized","noise","standard","deviation",".","(","_eps",",","_delta",")","are","parameters","of","(","eps",",","delta",")","-differential","privacy"]
docstr: Set parameters for (eps, delta)-differential privacy.
  
  Raises:
      AssertionError: eps must not be None.
docstr_tok: ["Set","parameters","for","(","eps",",","delta",")","-differential","privacy",".","Raises",":","AssertionError",":","eps","must","not","be","None","."]
code: def set_eps_delta(self, eps: float, delta: Optional[float]) -> None:
      """Set parameters for (eps, delta)-differential privacy.
  
      Raises:
          AssertionError: eps must not be None.
      """
      if eps is None:
          raise AssertionError("eps must not be None.")
      self._eps = eps
      self._delta = delta
      return
  
imports: import abc
  import collections
  import logging
  import math
  from typing import Optional
  from dataclasses import dataclass
  import pipeline_dp.aggregate_params
  from pipeline_dp import input_validators
label_desc: Use image node_id 5 for calling the MechanismSpec obj's underlying member method code with example usage: obj.set_eps_delta(eps, delta) without return types