TensorFlow Federated 0.37.0

Release 0.37.0

Major Features and Improvements

• Added support for Python 3.10.
• Improved support for numpy values in the tff.program API.
• Increased dataset serialization size limit to 100MB.
• Added a new method tff.learning.ModelWeights.convert_variables_to_arrays.
• Added new metrics aggregation factories under tff.learning.metrics.
• Parallelized aggregation in tff.framework.ComposingExecutorFactory.

Breaking Changes

• Updated to use jax and jaxlib version 0.3.14.
• Renamed tff.program.CoroValueReference to
  tff.program.AwaitableValueReference to reflect the relaxed contract.

Bug Fixes

• Improved documentation for tff.simulation.build_uniform_sampling_fn,
  tff.learning.robust_aggregator,
  tff.aggregators.PrivateQuantileEstimationProcess.
• Fixed documentation bug for tutorial “High-performance Simulation with
  Kubernetes”.
• Fixed bug where momentum hyperparameters were added to SGDM optimizer when
  momentum was set to 0.
• Removed assertion that preprocessed datasets in a
  tff.simulation.baselines.BaselineTask have the same element structure.
• Fixed a memory leak when moving numpy arrays across the Python and C++
  boundary in the C++ executor.
• Fixed bug in the federated program API when using multiple release managers
  to release the same value.

Thanks to our Contributors

This release contains contributions from many people at Google, as well as:
Madhava Jay, nbishdev@