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Libraries for developing Federated Learning algorithms.
Classes
class ClientDeltaFn
: Represents a client computation that produces an update to a model.
class ClientOutput
: Structure for outputs returned from clients during federated optimization.
class EnhancedModel
: A wrapper around a Model that adds sanity checking and metadata helpers.
class ModelWeights
: A container for the trainable and non-trainable variables of a Model
.
class ServerState
: Represents the state of the server carried between rounds.
Functions
build_encoded_broadcast_process_from_model(...)
: Builds MeasuredProcess
for weights of model returned by model_fn
.
build_encoded_mean_process_from_model(...)
: Builds MeasuredProcess
for weights of model returned by model_fn
.
build_encoded_sum_process_from_model(...)
: Builds MeasuredProcess
for weights of model returned by model_fn
.
build_model_delta_optimizer_process(...)
: Constructs tff.templates.IterativeProcess
for Federated Averaging or SGD.
build_stateless_broadcaster(...)
: Builds a MeasuredProcess
that wraps tff.federated_broadcast
.
build_stateless_mean(...)
: Builds a MeasuredProcess
that wrapstff.federated_mean
.
enhance(...)
: Wraps a tff.learning.Model
as an EnhancedModel
.
parameter_count_from_model(...)
: Computes count of trainable parameters for a model
.
weights_type_from_model(...)
: Creates a tff.Type
from a tff.learning.Model
or callable that constructs a model.