tff.aggregators.EncodedSumFactory

UnweightedAggregationFactory for encoded sum.

Inherits From: UnweightedAggregationFactory

tff.aggregators.EncodedSumFactory(
    encoder_fn: _EncoderConstructor
)

Used in the notebooks

Used in the tutorials
Tuning recommended aggregations for learning

The created tff.templates.AggregationProcess aggregates values placed at CLIENTS according to the provided GatherEncoder objects, and outputs the result placed at SERVER.

A GatherEncoder defines encode and decode methods, which are applied by CLIENTS before aggregation and by SERVER after aggregation. Usually these are such that the encoded representation communicated from CLIENTS to SERVER is smaller than communicating the original value, possibly at a cost of communicating slightly inaccurate values. A common example is to apply quantization. In addition, GatherEncoder enables the decoding logic to be split based on which part of its decode part commutes with sum, which is automatically utilized by the implementation.

Note: The current implementation does not allow for specification of an "inner" aggregation factory. This will be possible in a future version, when used together with a GatherEncoder of which the entire decode logic commutes with sum, as per its fully_commutes_with_sum property. Contributions welcome.

Args
encoder_fn	A one-arg callable, mapping a tf.TensorSpec, to a GatherEncoder.

Methods

create

View source

create(
    value_type: factory.ValueType
) -> tff.templates.AggregationProcess

Creates a tff.aggregators.AggregationProcess without weights.

The provided value_type is a non-federated tff.Type, that is, not a tff.FederatedType.

The returned tff.aggregators.AggregationProcess will be created for aggregation of values matching value_type placed at tff.CLIENTS. That is, its next method will expect type <S@SERVER, {value_type}@CLIENTS>, where S is the unplaced return type of its initialize method.

Args
value_type	A non-federated tff.Type.

Returns
A tff.templates.AggregationProcess.

quantize_above_threshold

View source

@classmethod
quantize_above_threshold(
    quantization_bits=8, threshold=20000, **kwargs
)

Quantization of values with at least threshold elements.

Given a value_type in the create method, this classmethod configures the EncodedSumFactory to apply uniform quantization to all instances of tff.TensorType in the value_type which have more than threshold elements.

Precisely, for each tensor t, this operation corresponds to t = round((t - min(t)) / (max(t) - min(t)) * (2**quantizaton_bits - 1)).

If a type does not have more than threshold elements, it is summed directly without being modified.

Args
quantization_bits	A integer specifying the quantization bitwidth.
threshold	A non-negative integer. Only tensors with more than this number of elements are quantized.
**kwargs	Keyword arguments.

Returns
An EncodedSumFactory.