Module: tff

The TensorFlow Federated library.

Modules

aggregators module: Libraries for constructing federated aggregation.

backends module: Backends for constructing, compiling, and executing computations.

framework module: Libraries for extending the TensorFlow Federated core library.

learning module: Libraries for using Federated Learning algorithms.

simulation module: Libraries for running Federated Learning simulations.

templates module: Templates for commonly used computations.

test module: Libraries for testing TensorFlow Federated.

utils module: Libraries for using and developing Federated algorithms.

Classes

class Computation: An abstract interface for all classes that represent computations.

class FederatedType: An implementation of tff.Type representing federated types in TFF.

class FunctionType: An implementation of tff.Type representing functional types in TFF.

class SequenceType: An implementation of tff.Type representing types of sequences in TFF.

class StructType: An implementation of tff.Type representing structural types in TFF.

class StructWithPythonType: A representation of a structure paired with a Python container type.

class TensorType: An implementation of tff.Type representing types of tensors in TFF.

class Type: An abstract interface for all classes that represent TFF types.

class TypedObject: An abstract interface for things that possess TFF type signatures.

class Value: An abstract base class for all values in the bodies of TFF computations.

Functions

check_returns_type(...): Checks that the decorated function returns values of the provided type.

federated_aggregate(...): Aggregates value from tff.CLIENTS to tff.SERVER.

federated_apply(...): Applies a given function to a federated value on tff.SERVER (deprecated).

federated_broadcast(...): Broadcasts a federated value from the tff.SERVER to the tff.CLIENTS.

federated_collect(...): Returns a federated value from tff.CLIENTS as a tff.SERVER sequence.

federated_computation(...): Decorates/wraps Python functions as TFF federated/composite computations.

federated_eval(...): Evaluates a federated computation at placement, returning the result.

federated_map(...): Maps a federated value pointwise using a mapping function.

federated_mean(...): Computes a tff.SERVER mean of value placed on tff.CLIENTS.

federated_reduce(...): Reduces value from tff.CLIENTS to tff.SERVER using a reduction op.

federated_secure_sum(...): Computes a sum at tff.SERVER of a value placed on the tff.CLIENTS.

federated_sum(...): Computes a sum at tff.SERVER of a value placed on the tff.CLIENTS.

federated_value(...): Returns a federated value at placement, with value as the constituent.

federated_zip(...): Converts an N-tuple of federated values into a federated N-tuple value.

sequence_map(...): Maps a TFF sequence value pointwise using a given function mapping_fn.

sequence_reduce(...): Reduces a TFF sequence value given a zero and reduction operator op.

sequence_sum(...): Computes a sum of elements in a sequence.

tf_computation(...): Decorates/wraps Python functions and defuns as TFF TensorFlow computations.

to_type(...): Converts the argument into an instance of tff.Type.

to_value(...): Converts the argument into an instance of the abstract class tff.Value.

type_at_clients(...): Constructs a federated type of the form {T}@CLIENTS.

type_at_server(...): Constructs a federated type of the form T@SERVER.

CLIENTS

SERVER

version '0.17.0'