code: def test_sum_with_clip_no_noise(self):
      record1 = tf.constant([-6.0, 8.0])  # Clipped to [-3.0, 4.0].
      record2 = tf.constant([4.0, -3.0])  # Not clipped.
  
      query = (
          quantile_adaptive_clip_sum_query.QuantileAdaptiveClipSumQuery(
              initial_l2_norm_clip=5.0,
              noise_multiplier=0.0,
              target_unclipped_quantile=1.0,
              learning_rate=0.0,
              clipped_count_stddev=0.0,
              expected_num_records=2.0,
          )
      )
  
      query_result, _ = test_utils.run_query(query, [record1, record2])
      result = query_result.numpy()
      expected = [1.0, 1.0]
      self.assertAllClose(result, expected)
  
file_path: privacy/tensorflow_privacy/privacy/dp_query/quantile_adaptive_clip_sum_query_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.dp_query import quantile_adaptive_clip_sum_query
  from tensorflow_privacy.privacy.dp_query import test_utils
label_desc: Use image node_id 2 for calling the QuantileAdaptiveClipSumQueryTest obj's underlying member method code with example usage: obj.test_sum_with_clip_no_noise() without return types