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Libraries for running Federated Learning simulations.
Modules
datasets
module: Datasets for running Federated Learning simulations.
models
module: Models for running Federated Learning simulations.
Classes
class CSVMetricsManager
: Utility class for saving/loading experiment metrics via a CSV file.
class ClientData
: Object to hold a federated dataset.
class FileCheckpointManager
: A checkpoint manager backed by a file system.
class FilePerUserClientData
: A tf.simulation.ClientData
that maps a set of files to a dataset.
class FromTensorSlicesClientData
: ClientData based on tf.data.Dataset.from_tensor_slices
.
class HDF5ClientData
: A tff.simulation.ClientData
backed by an HDF5 file.
class MetricsManager
: An abstract base class for metrics managers.
class TensorBoardManager
: Utility class for saving metrics using tf.summary
.
class TransformingClientData
: Transforms client data, potentially expanding by adding pseudo-clients.
Functions
build_uniform_client_sampling_fn(...)
: Builds a function that (pseudo-)randomly samples clients.
compose_dataset_computation_with_computation(...)
: Builds a new tff.Computation
which constructs datasets on clients.
compose_dataset_computation_with_iterative_process(...)
: Builds a new iterative process which constructs datasets on clients.
run_server(...)
: Runs a gRPC server hosting a simulation component in this process.
server_context(...)
: Context manager yielding gRPC server hosting simulation component.