Tensorflow-federated

Breaking Changes

* Removed the capability to pass a `tf.TensorShape` as the shape of a
`tff.TensorType`.

Bug Fixes

* Correctly materialize `SERVER` placed values out of the C++ execution stack
when using StreamingRemoteExecutor instead of returning an error about
placement not found.

Major Features and Improvements

* Update the representation of a `tff.TensorType.shape` to be a
`tff.types.ArrayShape` instead of `tf.TensorShape`.

* Updated `type_to_py_container``to be able to handle`tff.SequenceTypes` with
an unknown Python type.

Breaking Changes

* Moved `tff.structure_from_tensor_type_tree` to
`tff.types.structure_from_tensor_type_tree`.
* Remove the capability to pass an `int` as the shape of a `tff.TensorType`.

Major Features and Improvements

* Updated the TFF project and the Python package to be compatible with Python
3.11.
* Updated `train_process` to `train_process_factory` in vizier program logic
to support multiple trials in parallel.
* Added support for using non-OrderedDict mapping types.

Breaking Changes

* Updated the version of `grpc` to `v1.59.1`.
* Updated the version of `bazel` to `6.1.0`.
* Updated the version of `tensorflow` to `2.14.0`.
* Updated the version of `numpy` to `~=1.25`.
* Updated the version of `com_google_googletest` to `1.12.1`.

Bug Fixes

* Fixed import path for Vizier in federated program example.
* Fixed serialization of TenshorShape in error message to be human readable.
* Fixed bug in `tff.program.FileProgramStateManager` removing old program
state.

Major Features and Improvements

* Added `tff.federated_min` and `tff.federated_max` intrinsics.
* Added a `get_value()` method to `tff.program.SavedModelFileReleaseManager,`
for retrieving values that were previously released.
* Added `tff.program.PeriodicReleaseManager` to release values at regular
intervals.
* Learning program logic now saves next evaluation time so that it can be
loaded upon computation restarts.
* `DistributeAggregateForm` now skips normalizing the all_equal bit.
* Added parallelism to Vizier program logic.
* Enabled building protos with certain Bazel versions.

Breaking Changes

* Updated the version of `attrs` to `23.1`.
* Updated the version of `cachetools` to `~=5.3`.
* Updated the version of `dp-accounting` to `0.4.3`.
* Updated the version of `google-vizier` to `0.1.11`.
* Updated the version of `jax` to `0.4.14`.
* Updated the version of `portpicker` to `~=1.6`.
* Updated the version of `tensorflow` to `2.13.0`.
* Updated the version of `tensorflow-model-optimization` to `0.7.5`.
* Updated the version of `tensorflow-privacy` to `0.8.11`.
* Updated the version of `typing-extensions` to `~=4.5.0`.
* Increased `TF_CUDA_VERSION` to `12`.
* Removed the `tff.program.Capabilities` enum from the iterator.
* Deleted Python executors.
* Removed the deprecated `is_{foo}` functions from `tff.Type`s. Users should
use `isinstance` checks instead.
* Deleted go-related BUILD targets for TFF proto files.

Bug Fixes

* Removed non-existent GCP doc from TFF guides.
* Cleaned up exceptions in the `tff.program` package for consistency and
clarity.
* Fixed various pytype errors.
* Fixed various `undefined-variable` lint errors.
* Fixed a `UnicodeDecodeError` in the FedRecon tutorial.
* Fixed Python 3.11 related errors.

Breaking Changes

* Removed `context` argument from
`tff.learning.algorithms.build_personalization_eval_computation`. Now a
personalization function only takes a model, a train dataset, and a test
dataset as arguments.

Bug Fixes

* Fix a rare infinite loop issue caused by very small float values when using
`tff.learning.ddp_secure_aggregator`.

Major Features and Improvements

* Updated the type annotation for the `dtype` parameter to `tff.TensorType`.
* Added adaptive tuning function to `ThresholdSampling` class.
* Added
`tff.learning.models.ReconstructionModel.from_keras_model_and_variables`,
which provides a way to get a `ReconstructionModel` from a Keras model and
lists of global and local trainable/non_trainable *variables*.
* Switched `tff.learning.algorithms.build_fed_recon_eval` to use a stateful
metrics aggregator.

Breaking Changes

* Removed `tff.learning.models.ReconstructionModel.from_keras_model`, which
has been replaced by
`tff.learning.models.ReconstructionModel.from_keras_model_and_layers`.
* Removed the following functions from the py_typecheck module: `check_len`,
`check_callable`, `is_dataclass`,`is_attrs`, `check_subclass` and
`check_not_none`. They are unused or can be replaced by Python type
annotations.

Bug Fixes

* Fixed a small bug in the TFF SGDM optimizer, to only track momentum as a
hparam if it is both specified and nonzero.