code: def test_max_tree_sensitivity_square_sum_every_step(self, steps):
      max_participation, min_separation = steps, 0
      # If a sample will appear in every leaf node, we can infer the total
      # sensitivity by adding all the nodes.
      steps_bin = bin(steps)[2:]
      depth = [
          len(steps_bin) - 1 - i
          for i, v in enumerate(steps_bin)
          if v == "1"
      ]
      expected = sum([2**d * (2 ** (d + 1) - 1) for d in depth])
      self.assertEqual(
          expected,
          tree_aggregation_accountant._max_tree_sensitivity_square_sum(
              max_participation, min_separation, steps
          ),
      )
  
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 7 for calling the TreeAggregationTest obj's underlying member method code with example usage: obj.test_max_tree_sensitivity_square_sum_every_step(steps) without return types