code: def _gaussian_zcdp_to_epsilon(
      zcdp: float,
      target_delta: float = 1e-10,
      accountant: Optional[dp_accounting.PrivacyAccountant] = None,
  ) -> float:
      """Transforms zCDP of Gaussian Mechanism to (epsilon, delta)-DP.
  
      Args:
        zcdp: Input zCDP value.
        target_delta: Specified target delta for (epsilon, delta)-DP.
        accountant: Defaults to PLD accounting. Other options including RDP, i.e.,
          dp_accounting.rdp.RdpAccountant()
  
      Returns:
        Epsilon under given delata for (epsilon, delta)-DP.
      """
      if accountant is None:
          accountant = dp_accounting.pld.PLDAccountant()
      noise_multiplier = 1.0 / (zcdp * 2) ** 0.5
      accountant.compose(
          dp_accounting.GaussianDpEvent(noise_multiplier), 1
      )
      return accountant.get_epsilon(target_delta)
  
file_path: privacy/tensorflow_privacy/privacy/analysis/tree_aggregation_accountant.py
imports: import functools
  import math
  from typing import Collection, Optional, Union
  import dp_accounting
  import numpy
label_desc: Use image node_id 11 for calling a global function with example usage: _gaussian_zcdp_to_epsilon(zcdp, target_delta, accountant) and returns: accountant