class_docstr: DPQuery to estimate target quantile of a univariate distribution.
  
  Uses the algorithm of Andrew et al. (https://arxiv.org/abs/1905.03871). See
  the paper for details and suggested hyperparameter settings.
docstr: Implements `tensorflow_privacy.DPQuery.derive_metrics`.
docstr_tok: ["Implements","`","tensorflow_privacy.DPQuery.derive_metrics","`","."]
code: def derive_metrics(self, global_state):
      """Implements `tensorflow_privacy.DPQuery.derive_metrics`."""
      return collections.OrderedDict(
          estimate=global_state.current_estimate
      )
  
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 8 for calling the QuantileEstimatorQuery obj's underlying member method code with example usage: obj.derive_metrics(global_state) and returns: collections