Remove QuantileAdaptiveClipAverageQuery. Users can simply wrap QuantileAdaptiveClipSumQuery with a NormalizedQuery.
@@ -146,15 +146,15 @@ class DifferentiallyPrivateFactory(factory.UnweightedAggregationFactory):
f'`clipped_count_stddev` you may want to increase it. Or you may '
f'need more `clients_per_round`.')
- query = tfp.QuantileAdaptiveClipAverageQuery(
+ query = tfp.QuantileAdaptiveClipSumQuery(
initial_l2_norm_clip=initial_l2_norm_clip,
noise_multiplier=value_noise_multiplier,
- denominator=clients_per_round,
target_unclipped_quantile=target_unclipped_quantile,
learning_rate=learning_rate,
clipped_count_stddev=clipped_count_stddev,
expected_num_records=clients_per_round,
geometric_update=True)
+ query = tfp.NormalizedQuery(query, denominator=clients_per_round)
return cls(query)
