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.