code: def test_sum(
      self,
      records_num,
      record_dim,
      noise_multiplier,
      seed,
      total_steps,
      clip,
      use_efficient,
  ):
      record_specs = tf.TensorSpec(shape=[record_dim])
      query = tree_aggregation_query.TreeResidualSumQuery.build_l2_gaussian_query(
          clip_norm=clip,
          noise_multiplier=noise_multiplier,
          record_specs=record_specs,
          noise_seed=seed,
          use_efficient=use_efficient,
      )
      sum_query = tree_aggregation_query.TreeCumulativeSumQuery.build_l2_gaussian_query(
          clip_norm=clip,
          noise_multiplier=noise_multiplier,
          record_specs=record_specs,
          noise_seed=seed,
          use_efficient=use_efficient,
      )
      global_state = query.initial_global_state()
      sum_global_state = sum_query.initial_global_state()
  
      cumsum_result = tf.zeros(shape=[record_dim])
      for _ in range(total_steps):
          records = [
              tf.random.uniform(shape=[record_dim], maxval=records_num)
              for _ in range(records_num)
          ]
          query_result, global_state = test_utils.run_query(
              query, records, global_state
          )
          sum_query_result, sum_global_state = test_utils.run_query(
              sum_query, records, sum_global_state
          )
          cumsum_result += query_result
          self.assertAllClose(
              cumsum_result, sum_query_result, rtol=1e-6
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.dp_query import test_utils
  from tensorflow_privacy.privacy.dp_query import tree_aggregation
  from tensorflow_privacy.privacy.dp_query import tree_aggregation_query
label_desc: Use image node_id 1 for calling the TreeResidualQueryTest obj's underlying member method code with example usage: obj.test_sum(records_num, record_dim, noise_multiplier, seed, total_steps, clip, use_efficient) without return types