cec011e2a797a32a9b102a69d2d799256de7ca98,tensorflow_privacy/privacy/dp_query/quantile_adaptive_clip_sum_query.py,QuantileAdaptiveClipSumQuery,initial_global_state,#QuantileAdaptiveClipSumQuery#,118

Before Change

  def initial_global_state(self):
    See base class.
    initial_l2_norm_clip = tf.cast(self._initial_l2_norm_clip, tf.float32)
    noise_multiplier = tf.cast(self._noise_multiplier, tf.float32)
    target_unclipped_quantile = tf.cast(self._target_unclipped_quantile,
                                        tf.float32)
    learning_rate = tf.cast(self._learning_rate, tf.float32)
    sum_stddev = initial_l2_norm_clip * noise_multiplier

    sum_query_global_state = self._sum_query.make_global_state(
        l2_norm_clip=initial_l2_norm_clip,
        stddev=sum_stddev)

    return self._GlobalState(
        noise_multiplier,
        target_unclipped_quantile,
        learning_rate,
        sum_query_global_state,
        self._clipped_fraction_query.initial_global_state())

  def derive_sample_params(self, global_state):
    See base class.

After Change

  def initial_global_state(self):
    See base class.
    return self._GlobalState(
        tf.cast(self._noise_multiplier, tf.float32),
        self._sum_query.initial_global_state(),
        self._quantile_estimator_query.initial_global_state())

  def derive_sample_params(self, global_state):
    See base class.
    return self._SampleParams(

Instances