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Creates an aggregation factory for quantization and entropy coding.

step_size A positive float that determines the step size between adjacent quantization levels; suggested range [0.1, 10.0].
zeroing A boolean indicating whether to add zeroing out extreme client updates (True) or not (False).
clipping A boolean indicating whether to add clipping to large client updates (True) or not (False).
weighted A boolean indicating whether client model weights should be averaged in a weighted manner (True) or unweighted manner (False).
debug_measurements_fn A callable to add measurements suitable for debugging learning algorithms, with possible values as None, tff.learning.add_debug_measurements or tff.learning.add_debug_measurements_with_mixed_dtype.

A tff.aggregators.AggregationFactory.

TypeError if debug_measurement_fn yields an aggregation factory whose weight type does not match weighted.
ValueError if step_size is not a positive float.