Module: tff.utils

Libraries for using and developing Federated algorithms.

Functions

assign(...): Creates an op that assigns target from source.

build_adaptive_zeroing_mean_process(...): Builds tff.templates.MeasuredProcess for averaging with adaptive zeroing.

build_dp_aggregate_process(...): Builds a MeasuredProcess for tensorflow_privacy DPQueries.

build_dp_query(...): Makes a DPQuery to estimate vector averages with differential privacy.

build_encoded_broadcast_process(...): Builds MeasuredProcess for value_type, to be encoded by encoders.

build_encoded_mean_process(...): Builds MeasuredProcess for value_type, to be encoded by encoders.

build_encoded_sum_process(...): Builds MeasuredProcess for value_type, to be encoded by encoders.

create_variables(...): Creates a set of variables that matches the given type_spec.

federated_max(...): Aggregation to find the maximum value from the tff.CLIENTS.

federated_min(...): Aggregation to find the minimum value from the tff.CLIENTS.

federated_sample(...): Aggregation to produce uniform sample of at most max_num_samples values.

identity(...): Applies tf.identity pointwise to source.

secure_quantized_sum(...): Quantizes and sums values securely.

update_state(...): Returns a new state with new values for fields in kwargs.