Tensorflow-federated

Major Features and Improvements

* Enabled, improved, and fixed Python type annotations in some modules.
* Added the interface of `loss_fn` to `tff.learning.models.FunctionalModel`,
along with serialization and deserialization methods.
* Updated the composing executor to forward the `type` field of `Intrinsic`
protos that are sent to child executors.
* Added an executor binding for `DTensor` based executor.

Breaking Changes

* Deprecated `tff.framework.DataBackend`. Python execution is deprecated
instead use CPP Execution.

Bug Fixes

* Fixed the formulation of the JIT constructed mapped selection computation
that is sent to the remote machine in streaming mode.
* Fixed the usage of `np.bytes_` types that incorrectly truncate byte string
with null terminator.

Major Features and Improvements

* Added client learning rate measurements to
`tff.learning.algorithms.build_weighted_fed_avg_with_optimizer_schedule`
* Added support for streaming federated structure values to the C++
RemoteExecutor.
* Added a C++ executor for executing TF graphs using TF2 DTensor APIs when
layout information is specified for input parameters or variables in the
graph.

Breaking Changes

* Deprecated the following API, Python execution is deprecated instead use CPP
execution:
* `tff.framework.local_executor_factory`
* `tff.framework.remote_executor_factory_from_stubs`
* `tff.framework.DataExecutor`
* `tff.framework.EagerTFExecutor`
* Removed the following API, Python execution is deprecated instead use CPP
execution:
* `tff.backends.native.create_local_python_execution_context`
* `tff.backends.native.create_remote_python_execution_context
* `tff.framework.remote_executor_factory`
* Remove the `executors_errors` module from the `tff.framework` API, use
`tff.framework.RetryableError` instead.

Bug Fixes

* Fixed potential lifetime issue in C++ RemoteExecutor
* Enabled and fixed python type annotations in many packages.
* Fixed one-off error in evaluation criteria in training program logic.

Major Features and Improvements

* Created the Baselines API of the GLDv2 (landmark) dataset for simulation,
with a GLDv2 preprocessing function, a GLDv2 tasks function, and a Google
mirror of the GLDv2 baselines tasks.

Breaking Changes

* Temporarily removed `tff.program.PrefetchingDataSource`, the
PrefetchingDataSourceIterator tests are flaky and it's not immediately clear
if this is due to the implementation of the PrefetchingDataSourceIterator or
due to a bug in the test.
* Deprecated the following API, Python execution is deprecated instead use CPP
execution:
* `tff.backends.native.create_local_python_execution_context`
* `tff.backends.native.create_remote_python_execution_context`
* `tff.backends.native.create_remote_async_python_execution_context`
* `tff.backends.native.set_remote_async_python_execution_context`
* Removed the following API, Python execution is deprecated instead use CPP
execution:
* `tff.backends.native.set_local_python_execution_context`
* `tff.backends.native.set_remote_python_execution_context`
* `tff.framework.FederatingExecutor`
* `tff.framework.ComposingExecutorFactory`
* `tff.framework.ExecutorValue`
* `tff.framework.Executor`
* `tff.framework.FederatedComposingStrategy`
* `tff.framework.FederatedResolvingStrategy`
* `tff.framework.FederatingStrategy`
* `tff.framework.ReconstructOnChangeExecutorFactory`
* `tff.framework.ReferenceResolvingExecutor`
* `tff.framework.RemoteExecutor`
* `tff.framework.ResourceManagingExecutorFactory`
* `tff.framework.ThreadDelegatingExecutor`
* `tff.framework.TransformingExecutor`
* `tff.framework.UnplacedExecutorFactory`
* Removed duplicate API from `tff.framework`, instead use:
* `tff.types.type_from_tensors`
* `tff.types.type_to_tf_tensor_specs`
* `tff.types.deserialize_type`
* `tff.types.serialize_type`
* Renamed `tff.learning.Model` to `tff.learning.models.VariableModel`.
* Renamed the
`cpp_execution_context.(create|set)_local_async_cpp_execution_context`
function to match the name of
`execution_context.(create|set)_(sync|async)_local_cpp_execution_context`.

Bug Fixes

* Fixed bug in FLAIR download URLs.
* Enabled and fixed python type annotations in many packages.

Major Features and Improvements

* Implemented divisive split logic needed by DistributeAggregateForm, which is
currently under development and will replace MapReduceForm and BroadcastForm
in the future.

Breaking Changes

* Renamed the `cpp_execution_context.(create|set)_local_cpp_execution_context`
function to match the name of
`execution_context.(create|set)_(sync|async)_local_cpp_execution_context`.
* Deleted the sizing Python execution context and executor.
* Deleted the thread debugging Python execution context and executor.
* Removed `ExecutorService` from the public API.
* Deleted the local async python execution context.

Bug Fixes

* Enabled and fixed python type annotations in some modules in the
`executors`, `types`, and `core` package.

Major Features and Improvements

* Added a `LayoutMap` message in the computation proto for TensorFlow
`DTensor` based execution.

Breaking Changes

* Removed the `compiler_fn` parameter from the high level
`*_mergeable_execution_context` functions.

Bug Fixes

* Aligned the context types allowed by the
`tff.program.NativeFederatedContext` and the
`tff.program.PrefetchingDataSource`.
* Updated `build_functional_model_delta_update` to use `ReduceDataset` ops to
rely on MLIR Bridge for XLA compilation and TPU usage.

Major Features and Improvements

* Added parameter and implementation for C++ remote executor to stream the
values in a structure across the gRPC interface.
* Added `tff.backends.native.desugar_and_transform_to_native` to the public
API.
* Replaced `GroupNorm` implementation with implementation from Keras.
* Added `tff.simulations.datasets.flair` APIs for the FLAIR dataset.

Breaking Changes

* Removed file extension for `model_output_manager` used in
`tff.learning.programs`

Bug Fixes

* Enabled and fixed python type annotations in some modules.
* Changed `tff.learning.algorithms.build_weighted_fed_prox` parameter
validation to allow `proximal_strength = 0.0`, matching the pydoc.