Module: tff

The TensorFlow Federated library.

Modules

aggregators module: Libraries for constructing federated aggregation.

analytics module: Libraries for using Federated Analytics algorithms.

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

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

jax module: Libraries for interacting with a JAX frontend and XLA backend.

learning module: Libraries for building federated learning algorithms.

profiler module: Utility functions for instrumenting code with timing and tracing data.

program module: Libraries for creating federated programs.

simulation module: Libraries for running TensorFlow Federated simulations.

structure module: Container for structures with named and/or unnamed fields.

templates module: Templates for commonly used computations.

tensorflow module: Libraries for interacting with a TensorFlow frontend and backend.

test module: Libraries for testing TensorFlow Federated.

types module: Libraries for interacting with the type of a computation.

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: A generic base class for values that appear in TFF computations.

Functions

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

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

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_max(...): Computes a max at tff.SERVER of a value placed on the tff.CLIENTS.

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

federated_min(...): Computes a min at tff.SERVER of a value placed on the tff.CLIENTS.

federated_secure_select(...): Sends privately-selected values from a server database to clients.

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

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

federated_select(...): Sends selected values from a server database to 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.

jax_computation(...): Decorates/wraps Python functions containing JAX code as TFF computations.

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

CLIENTS Instance of tff.framework.PlacementLiteral
SERVER Instance of tff.framework.PlacementLiteral
version '0.83.0'