TensorFlow Federated 0.88.0

Release 0.88.0

Added

• tff.tensorflow.to_type.
• Added pack_args_into_struct and unpack_args_from_struct to the public
  API under framework.

Deprecated

• tff.types.tensorflow_to_type, use tff.tensorflow.to_type instead.

Changed

• Updated to use an environment-agnostic way to represent a sequence of data.
• Updated JAX computations and contexts to be able to handle sequence types.
• Moved tff.types.structure_from_tensor_type_tree and
  tff.types.type_to_tf_tensor_specs to the tff.tensorflow package.

Removed

• tff.framework.merge_cardinalities
• tff.framework.CardinalityCarrying
• tff.framework.CardinalityFreeDataDescriptor
• tff.framework.CreateDataDescriptor
• tff.framework.DataDescriptor
• tff.framework.Ingestable

TensorFlow Federated 0.87.0

Release 0.87.0

Added

• Added an implementation of AdamW to tff.learning.optimizers.

Changed

• Support None gradients in tff.learning.optimizers. This mimics the
  behavior of tf.keras.optimizers - gradients that are None will be
  skipped, and their corresponding optimizer output (e.g. momentum and
  weights) will not be updated.
• The behavior of DPGroupingFederatedSum::Clamp: it now sets negatives to 0.
  Associated test code has been updated. Reason: sensitivity calculation for
  DP noise was calibrated for non-negative values.
• Change tutorials to use tff.learning.optimizers in conjunction with
  tff.learning computations.
• tff.simulation.datasets.TestClientData only accepts dictionaries whose
  leaf nodes are not tf.Tensors.

Fixed

• A bug where tff.learning.optimizers.build_adafactor would update its step
  counter twice upon every invocation of .next().
• A bug where tensor learning rates for tff.learning.optimizers.build_sgdm
  would fail with mixed dtype gradients.
• A bug where different optimizers had different behavior on empty weights
  structures. TFF optimizers now consistently accept and function as no-ops on
  empty weight structures.
• A bug where tff.simulation.datasets.TestClientData.dataset_computation
  yielded datasets of indeterminate shape.

Removed

• tff.jax_computation, use tff.jax.computation instead.
• tff.profiler, this API is not used.
• Removed various stale tutorials.
• Removed structure from tff.program.SavedModelFileReleaseManager's
  get_value method parameters.
• Removed support for tf.keras.optimizers in tff.learning.

TensorFlow Federated 0.86.0

Release 0.86.0

Added

• tff.tensorflow.transform_args and tff.tensorflow.transform_result, these
  functions are intended to be used when instantiating and execution context
  in a TensorFlow environment.

Changed

• Replaced the tensor on the Value protobuf with an array field and
  updated the serialization logic to use this new field.

TensorFlow Federated 0.85.0

Release 0.85.0

Added

• The dp_noise_mechanisms header and source files: contains functions that
  generate differential_privacy::LaplaceMechanism or
  differential_privacy::GaussianMechanism, based upon privacy parameters and
  norm bounds. Each of these functions return a DPHistogramBundle struct,
  which contains the mechanism, the threshold needed for DP open-domain
  histograms, and a boolean indicating whether Laplace noise was used.
• Added some TFF executor classes to the public API (CPPExecutorFactory,
  ResourceManagingExecutorFactory, RemoteExecutor, RemoteExecutorGrpcStub).
• Added support for bfloat16 dtypes from the ml_dtypes package.

Fixed

• A bug where tf.string was mistakenly allowed as a dtype to
  tff.types.TensorType. This now must be np.str_.

Changed

• tff.Computation and tff.framework.ConcreteComputation to be able to
  transform the arguments to the computation and result of the computation.
• DPClosedDomainHistogram::Report and DPOpenDomainHistogram::Report: they
  both use the DPHistogramBundles produced by the CreateDPHistogramBundle
  function in dp_noise_mechanisms.
• DPGroupByFactory::CreateInternal: when delta is not provided, check if
  the right norm bounds are provided to compute L1 sensitivity (for the
  Laplace mech).
• CreateRemoteExecutorStack now allows the composing executor to be specified
  and assigns client values to leaf executors such that all leaf executors
  receive the same number of clients, except for potentially the last leaf
  executor, which may receive fewer clients.
• Allow tff.learning.programs.train_model to accept a should_discard_round
  function to decide whether a round should be discarded and retried.

Removed

• tff.structure.to_container_recursive, this should not be used externally.

TensorFlow Federated 0.84.0

Release 0.84.0

Added

• Added some TFF executor classes to the public API (ComposingExecutor,
  ExecutorTestBase, MockExecutor, ThreadPool).
• Added some compiler transformation helper functions to the public API
  (replace_intrinsics_with_bodies, unique_name_generator,
  transform_preorder, to_call_dominant).
• Added a method to get the number of checkpoints aggregated to the
  CheckpointAggregator API.
• The function DPClosedDomainHistogram::IncrementDomainIndices. It allows
  calling code to iterate through the domain of composite keys (in a do-while
  loop).

Changed

• Fixed a bug in tff.jax.computation that raised an error when the
  computation had unused arguments.
• Fixed a bug when using tff.backends.xla execution stack that raised errors
  when single element structures were returned from tff.jax.computation
  wrapped methods.
• Modified the model output release frequency to every 10 rounds and the final
  round in tff.learning.programs.train_model.
• Loosened the kEpsilonThreshold constant and updated the tests of
  DPOpenDomainHistogram accordingly.
• The behavior of DPClosedDomainHistogram::Report(): it now produces an
  aggregate for each possible combinations of keys. Those composite keys that
  GroupByAggregator did not already assign an aggregate to are assigned 0.
  Future CL will add noise.
• Modified tff.learning.algorithms.build_weighted_fed_avg to generate
  different training graphs when use_experimental_simulation_loop=True and
  model_fn is of type tff.learning.models.FunctionalModel.

TensorFlow Federated 0.83.0

Release 0.83.0

Changed

• The tff.learning.programs.train_model program logic to save a deep copy of
  the data source iterator within the program state.
• The file-backed native program components to not flatten and unflatten
  values.

Removed

• Unused functions from tensorflow_utils.
• Serializing raw tf.Tensor values to the Value protobuf.
• Partial support for dataclasses.

TensorFlow Federated 0.82.0

Release 0.82.0

Added

• Add a serialized raw array content field to the Array proto.
• A function to DPCompositeKeyCombiner that allows retrieval of an ordinal.
  Intended for use by the closed-domain DP histogram aggregation core.
• Constants for invalid ordinals and default l0_bound_.

Changed

• How DPCompositeKeyCombiner handles invalid l0_bound_ values.
• The default l0_bound_ value in DPCompositeKeyCombiner to new constant.
• Organization of DP histogram code. Previously, open-domain histogram class +
  factory class lived side-by-side in dp_group_by_aggregator.h/cc. Now split
  into dp_open_domain_histogram.h/cc and dp_group_by_factory.h/cc, which
  will ease future addition of code for closed-domain histogram.
• Moved tff.federated_secure_modular_sum to the mapreduce backend, use
  tff.backends.mapreduce.federated_secure_modular_sum instead.

TensorFlow Federated 0.81.0

Release 0.81.0

Added

• A helper function to get a vector of strings for the elements of a tensor in
  order to aid in formatting.
• A field string_val to the tensor proto to allow representing string
  values explicitly.

Changed

• The format of the release notes (i.e., RELEASE.md) to be based on
  https://keepachangelog.com/en/1.1.0/.
• Moved constraint on linfinity_bound from DPGroupingFederatedSumFactory
  to DPGroupByFactory, because closed-domain histogram algorithm will use
  DPGroupingFederatedSum but not demand a positive linfinity_bound.

Removed

• The dependency on semantic-version.
• The tff.async_utils package, use asyncio instead.

TensorFlow Federated 0.80.0

Release 0.80.0

Breaking Changes

• Move the tools package to the root of the repository.
• Updated bazel to version 6.5.0.
• Updated rules_python to version 0.31.0.
• Deleted deprecated tff.learning.build_federated_evaluation, which was superseded by tff.learning.algorithms.build_fed_eval.

TensorFlow Federated 0.79.0

Release 0.79.0

Major Features and Improvements

• Enable support for models with non-trainable variables in
  tff.learning.models.functional_model_from_keras.

Breaking Changes

• Removed farmhashpy dependency.
• Updated com_github_grpc_grpc to version 1.50.0.
• Moved the TFF repository from https://github.com/tensorflow/federated to
  https://github.com/google-parfait/tensorflow-federated.