Tensorflow-federated

Major Features and Improvements

* Allow functional models to return a structure.

Breaking Changes

* Removed support for handling `attrs` as containers in the `tff.program` API.
* Migrated the `personalization_eval` module to the algorithms package.
* Deleted the `tff.learning.build_local_evaluation` API.
* Migrated `tff.learning.reconstruction` to the `tff.learning.algorithms`
package.
* Updated to `dm-tree` version `0.1.8`.
* Updated to `dp-accounting` version `0.4.1`.
* Updated to `tensorflow-privacy` version `0.8.9`.

Major Features and Improvements

* Added Vizier backed tuning program logic to `tff.learning`.
* Updated the `tff.learning.programs.EvaluationManager` to clean up states
after recording the evaluation is completed.

Breaking Changes

* Removed deprecated `tff.learning.framework.ServerState` symbol.

Major Features and Improvements

* Removed `nest_asyncio` dependency from tutorials.
* Added a new
aggregatorr`tff.aggregators.DifferentiallyPrivateFactory.tree_adaptive` for
combining DP-FTRL (https://arxiv.org/abs/2103.00039) and adaptive clipping
(https://arxiv.org/abs/1905.03871).
* Updated `tff.learning.programs.EvaluationManager` to set the evaluation
deadline from the start time.

Breaking Changes

* Python runtime deleted; C++ runtime covers all known use-cases.

Bug Fixes

* Fixed a bug attempting to push `tf.data.Dataset` iterator ops onto GPUs.

Major Features and Improvements

* Added attributes to `tff.learning.programs.EvaluationManager`, this enables
constructing new `EvaluationManager`s from existing ones.
* Added Subsample Process abstract class and the implementation of Threshold
Sampling Process Remove introducing dependency on relayout op for control
edges.
* Replaced usage of `attrs` in `tff.aggregators` with `typing.NamedTuple`.
* Removed introducing dependency on relayout op for control edges.

Breaking Changes

* Removed `run_server` and `server_context` from the `tff.simulation` API.
* Removed the following symbols from the `tff.framework` API:
* `tff.framework.local_executor_factory`
* `tff.framework.DataBackend`
* `tff.framework.DataExecutor`
* `tff.framework.EagerTFExecutor`

Bug Fixes

* Removed use of deprecated tff.learning symbols, and clear cell image
outputs.

Major Features and Improvements

* Updated TF version to 2.12.0.
* Relaxed runtime type checks on `tff.learning.templates.LearningProcess` to
allow non-sequence CLIENTS arguments.
* `tff.simulation.compose_dataset_computation_with_learning_process` now
returns a `tff.learning.templates.LearningProcess`.
* Updated the `tff.program.FederatedDataSourceIterator`s so that they can be
serialized.

Breaking Changes

* Deleted the `forward_pass` attribute from the `FunctionalModel` interface.
* Removed `from_keras_model`, `MetricsFinalizersType`, `BatchOutput`, `Model`,
and `ModelWeights` symbols from the `tff.learning` package. Users should
instead use the `tff.learning.models` package for these symbols.
* Removed deprecated `tff.learning.federated_aggregate_keras_metric` function.
* Removed implicit attribute forwarding on
`tff.simulation.compose_dataset_computation_with_learning_process`.
* Removed deprecated `tff.framework.remote_executor_factory_from_stubs`.
* Removed deprecated `tff.backends.xla` APIs.
* Renamed the `tff.backends.test` APIs to:
`tff.backends.test.(create|set)_(sync|async)_test_cpp_execution_context`.

Major Features and Improvements

* Exposed `tff.backends.mapreduce.consolidate_and_extract_local_processing` as
public API.
* Updated the federated program API to be able to handle `tff.Serializable`
objects.

Breaking Changes

* Deprecated handling `attrs` classes as containers in the `tff.program` API.
* Updated `tff.learning.algorithms` implementations to use
`tff.learning.models.FunctionalModel.loss` instead of
`FunctionalModel.forward_pass`.

Bug Fixes

* Avoid using `sys.stdout` and `sys.stderr` in `subprocess.Popen` when
executing inside an IPython context.
* Added a `SequenceExecutor` to the C++ execution stack to handle `sequence_*`
intrinsics.