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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
.
Other Members | |
---|---|
CLIENTS |
Instance of tff.framework.PlacementLiteral
|
SERVER |
Instance of tff.framework.PlacementLiteral
|
version |
'0.85.0'
|