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tff.aggregators.UnweightedReservoirSamplingFactory

An UnweightedAggregationFactory for reservoir sampling values.

Inherits From: UnweightedAggregationFactory

The created tff.templates.AggregationProcess samples values placed at CLIENTS, and outputs the sample placed at SERVER.

The process has empty state. The measurements of this factory counts the number of non-finite (NaN or Inf values) leaves in the client values before sampling. Specifically, the returned measurements has the same structure as the client value, and every leaf node is a tf.int64 scalar tensor counting the number of clients having non-finite value in that leaf.

For example, suppose we are aggregating from three clients:

  client_value_1 = collections.OrderedDict(a=[1.0, 2.0], b=[1.0, np.nan])
  client_value_2 = collections.OrderedDict(a=[np.nan, np.inf], b=[1.0, 2.0])
  client_value_3 = collections.OrderedDict(a=[1.0, 2.0], b=[np.inf, np.nan])

Then measurements will be:

  collections.OrderedDict(a=tf.constant(1, dtype=int64),
                          b=tf.constant(2, dtype=int64)

For more about reservoir sampling see https://en.wikipedia.org/wiki/Reservoir_sampling

Methods

create

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Creates a tff.aggregators.AggregationProcess without weights.

The provided value_type is a non-federated tff.Type object, that is, value_type.is_federated() should return False.

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 (value_type.is_federated() returns False).

Returns
A tff.templates.AggregationProcess.