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_sample_params`.
docstr_tok: ["Implements","`","tensorflow_privacy.DPQuery.derive_sample_params","`","."]
code: def derive_sample_params(self, global_state):
      """Implements `tensorflow_privacy.DPQuery.derive_sample_params`."""
      below_estimate_params = (
          self._below_estimate_query.derive_sample_params(
              global_state.below_estimate_state
          )
      )
      return self._SampleParams(
          global_state.current_estimate, below_estimate_params
      )
  
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 4 for calling the QuantileEstimatorQuery obj's underlying member method code with example usage: obj.derive_sample_params(global_state) and returns: self