code: def test_gaussian_zcdp_to_epsilon(self):
      # The example below is reported in
      # https://ai.googleblog.com/2022/02/federated-learning-with-formal.html
      # Uses updated default RDP order (i.e., orders=None) can achieve better
      # guarantees. Uses PLD accounting (dp_accounting.pld.PLDAccountant) can
      # usually be tigher than RDP.
      zcdp = 0.81
      orders = [1 + x / 10.0 for x in range(1, 100)] + list(
          range(12, 64)
      )
      eps = tree_aggregation_accountant._gaussian_zcdp_to_epsilon(
          zcdp, accountant=dp_accounting.rdp.RdpAccountant(orders)
      )
      self.assertNear(eps, 8.92, err=0.01)
  
file_path: privacy/tensorflow_privacy/privacy/analysis/tree_aggregation_accountant_test.py
imports: from absl.testing import parameterized
  import dp_accounting
  import tensorflow
  from tensorflow_privacy.privacy.analysis import tree_aggregation_accountant
label_desc: Use image node_id 12 for calling the TreeAggregationTest obj's underlying member method code with example usage: obj.test_gaussian_zcdp_to_epsilon() without return types