class_docstr: `DPQuery` for queries with a `DPQuery` numerator and fixed denominator.
  
  If the number of records per round is a public constant R, `NormalizedQuery`
  could be used with a sum query as the numerator and R as the denominator to
  implement an average. Under some sampling schemes, such as Poisson
  subsampling, the actual number of records in a sample is a private quantity,
  so we cannot use it directly. Using this class with the expected number of
  records as the denominator gives an unbiased estimate of the average.
docstr: Implements `tensorflow_privacy.DPQuery.initial_global_state`.
code: def initial_global_state(self):
      """Implements `tensorflow_privacy.DPQuery.initial_global_state`."""
      denominator = tf.cast(self._denominator, tf.float32)
      return self._GlobalState(
          self._numerator.initial_global_state(), denominator
      )
  
file_path: privacy/tensorflow_privacy/privacy/dp_query/normalized_query.py
imports: import collections
  import tensorflow
  from tensorflow_privacy.privacy.dp_query import dp_query
label_desc: Use image node_id 2 for calling the NormalizedQuery obj's underlying member method code with example usage: obj.initial_global_state() and returns: self