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TensorFlow Federated v0.20.0

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@michaelreneer michaelreneer released this 23 Feb 02:46
v0.20.0
b3d8166

Release 0.20.0

Major Features and Improvements

  • Added tff.program API; this API is still in active development but can be
    used to compose shared and platform specific: program logic, components, and
    privacy concepts to create federated programs.
  • Added support for Python 3.9.
  • Added CelebA and iNaturalist datasets to tff.simulation.datasets.
  • Added tff.analytics API for federated analytics, including private heavy
    hitters algorithms.
  • Added tff.learning.algorithms API, including TFF implementations of
    FedProx, FedAvg with learning rate scheduling, federated k-Means, and
    MimeLite.
  • Added tff.learning.metrics API to support easy configuration of
    cross-client metrics aggregation via the new metrics_aggregator argument.
  • Added metrics_aggregator argument to
    tff.learning.build_federated_averaging_process and
    tff.learning.build_federated_evaluation.
  • Added report_local_unfinalized_metrics and metric_finalizers methods to
    tff.learning.Model and deprecated report_local_outputs and
    federated_output_computation.
  • Added tff.learning.optimizers API for building purely functional
    optimizers and implementations of SGD, Adagrad, Rmsprop, Adam, Yogi,
  • Added tff.learning.reconstruction API for building partially local
    federated learning algorithms, including Federated Reconstruction.
  • Added tff.learning.templates API to support building learning algorithms
    in a modular fashion.
  • Added tff.simulation.baselines API to support evaluating learning
    algorithms on a suite of representative tasks.
  • Added tff.aggregators.DifferentiallyPrivateFactory.tree_aggregation to
    support the DP-FTRL algorithm.
  • Added tff.aggrgators.SecureModularSumFactory
  • Added tff.aggregators.DiscreteFourierTransformFactory and
    tff.aggregators.HadamardTransformFactory to support rotation-based
    aggregators.
  • Added tff.aggregators.concat_factory for aggregating structures as a
    single tensor.
  • Added tff.backends.native.create_mergeable_comp_execution_context,
    tff.backends.native.set_mergeable_comp_execution_context; these can be
    used with a distributed runtime to scale to tens of thousands of clients.
  • Improved performance of many tff.simulation.datasets.ClientData
    subclasses.
  • Added tff.simulation.datasets.ClientData.serializable_dataset_fn
    attribute, enabling dataset creation within TF/TFF computations.
  • Added debug_measurements option to aggregators in tff.learning.
  • Added support for unambiguous zero-client aggregations.
  • Added support for Python dataclasses as function parameters and return
    values for TFF computations.
  • Added automatic insertion of tff.federated_zip to invocation of
    user-defined TFF federated computations.
  • Added utilities to tff.simulation.datasets for saving federated datasets
    to a SQL database compatible with tff.simulation.datasets.SqlClientData.
  • Added tff.learning.models.FunctionalModel and
    tff.learning.models.functional_model_from_keras.
  • Increased max flow of tensors. Tensors now flow here, there, and everywhere.
  • Updated the Python dependencies:
  • Updated absl-py to version 1.0.0.
  • Updated attrs to version 21.2.0.
  • Added farmhashpy version 0.4.0.
  • Updated jax to version 0.2.27.
  • Updated jaxlib to version 0.1.76.
  • Updated numpy to version 1.21.4.
  • Removed retrying.
  • Updated tensorflow-model-optimization to version 0.7.1.
  • Updated tensorflow-model-optimization to version 0.7.3.
  • Updated tensorflow to version 2.8.0.
  • Added support for building many dependencies including tensorflow using
    Bazel.
  • Updated the Bazel dependencies:
  • Updated rules_python to version 0.5.0.
  • Updated com_google_protobuf to version v3.18.0-rc1.
  • Added absl_py version 1.0.0.
  • Added com_google_googletest version release-1.11.0.
  • Added io_bazel_rules_go version v0.29.0.
  • Added bazel_skylib version 1.0.3.
  • Added pybind11_abseil.
  • Added pybind11_bazel.
  • Added pybind11_protobuf.
  • Added com_google_absl version 20211102.0.
  • Added tensorflow_org version v2.8.0.

Breaking Changes

  • Removed support for building source on MacOS.
  • Removed support for Python 3.6.
  • Removed symbol tff.framework.type_contains, use tff.types.contains
    instead.
  • Removed many symbols from tff.simulation, these can be found in
    tff.program instead.
  • Removed support for converting non-OrderedDict mapping types to
    tff.Values.
  • Removed tff.simulation.datasets.ClientData.from_clients_and_fn in favor of
    tff.simulation.datasets.ClientData.from_clients_and_tf_fn.
  • Restricted tff.simulation.datasets.ClientData.preprocess to only support
    TF-serializable functions.
  • Removed tff.backends.reference, and the reference context it contained.
  • Removed tff.learning.build_federated_sgd_process in favor of
    tff.learning.algorithms.build_fed_sgd.
  • Removed tff.simulation.run_simulation in favor of
    tff.simulation.run_training_process.
  • Removed tff.learning.framework.EnhancedModel.
  • Removed tff.learning.framework.build_stateless_mean.

Bug Fixes

  • Fixed broken links in documentation.
  • Fixed many pytype errors.
  • Fixed some inconsistencies in Bazel visibility.
  • Fixed bug where tff.simulation.datasets.gldv2.load_data() would result in
    an error.
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