class_docstr: Iterative process to estimate target quantile of a univariate distribution.
  
  Unlike the base class, this uses a NoPrivacyQuery to estimate the fraction
  below estimate with an exact denominator, so there are no privacy guarantees.
code: def _construct_below_estimate_query(
      self, below_estimate_stddev, expected_num_records
  ):
      del below_estimate_stddev
      del expected_num_records
      return no_privacy_query.NoPrivacyAverageQuery()
  
imports: import collections
  import tensorflow
  from tensorflow_privacy.privacy.dp_query import dp_query
  from tensorflow_privacy.privacy.dp_query import gaussian_query
  from tensorflow_privacy.privacy.dp_query import no_privacy_query
  from tensorflow_privacy.privacy.dp_query import normalized_query
  from tensorflow_privacy.privacy.dp_query import tree_aggregation_query
label_desc: Use image node_id 2 for calling the NoPrivacyQuantileEstimatorQuery obj's underlying member method code with example usage: obj._construct_below_estimate_query(below_estimate_stddev, expected_num_records) and returns: no_privacy_query