class_docstr: `DPQuery` for tree aggregation queries with adaptive clipping.
  
  The implementation is based on tree aggregation noise for cumulative sum in
  "Practical and Private (Deep) Learning without Sampling or Shuffling"
  (https://arxiv.org/abs/2103.00039) and quantile-based adaptive clipping in
  "Differentially Private Learning with Adaptive Clipping"
  (https://arxiv.org/abs/1905.03871).
  
  The quantile value will be continuously estimated, but the clip norm is only
  updated when `reset_state` is called, and the tree state will be reset. This
  will force the clip norm (and corresponding stddev) in a tree unchanged.
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docstr: Implements `tensorflow_privacy.DPQuery.get_noised_result`.
docstr_tok: ["Implements","`","tensorflow_privacy.DPQuery.get_noised_result","`","."]
code: def get_noised_result(self, sample_state, global_state):
      """Implements `tensorflow_privacy.DPQuery.get_noised_result`."""
      (
          noised_vectors,
          sum_state,
          sum_event,
      ) = self._sum_query.get_noised_result(
          sample_state.sum_state, global_state.sum_state
      )
  
      (
          _,
          quantile_estimator_state,
          quantile_event,
      ) = self._quantile_estimator_query.get_noised_result(
          sample_state.quantile_estimator_state,
          global_state.quantile_estimator_state,
      )
  
      new_global_state = self._GlobalState(
          global_state.noise_multiplier,
          sum_state,
          quantile_estimator_state,
      )
      event = dp_accounting.ComposedDpEvent(
          events=[sum_event, quantile_event]
      )
      return noised_vectors, new_global_state, event
  
file_path: privacy/tensorflow_privacy/privacy/dp_query/quantile_adaptive_clip_tree_query.py
imports: import collections
  import dp_accounting
  import tensorflow
  from tensorflow_privacy.privacy.dp_query import dp_query
  from tensorflow_privacy.privacy.dp_query import quantile_estimator_query
  from tensorflow_privacy.privacy.dp_query import tree_aggregation_query
label_desc: Use image node_id 6 for calling the QAdaClipTreeResSumQuery obj's underlying member method code with example usage: obj.get_noised_result(sample_state, global_state) and returns: noised_vectors,  new_global_state,  event