TensorFlow Federated 0.17.0
Pre-release
Pre-release
Major Features and Improvements
- New
tff.aggregators
package with interfaces for stateful aggregation
compositions. - New Google Landmark Dataset
tff.simulations.dataset.gldv2
- New convenience APIs
tff.type_clients
andtff.type_at_server
- Invert control of computation tracing methods to produce clearer Python
stack traces on error. - Move executor creation to a factory pattern in executor service, allowing
distributed runtimes to be agnostic to number of clients. - Significant improvements of type serialization/deserialization
- New
tff.simulations.compose_dataset_computation_with_iterative_process
API
to move execution of client dataset construction to executor stack leaves. - Extend parameterization of
tff.learning.build_federated_averaging_process
withuse_experimental_simulation_loop
argument to better utilize multi-GPU
setups.
Breaking Changes
- Removed
tff.utils.StatefulFn
, replaced bytff.templates.MeasuredProcess
. - Removed
tff.learning.assign_weights_to_keras_model
- Stop removing
OptimizeDataset
ops fromtff.tf_computation
s. - The
research/
directory has been moved to
http://github.com/google-research/federated. - Updates to
input_spec
argument fortff.learning.from_keras_model
. - Updated TensorFlow dependency to
2.3.0
. - Updated TensorFlow Model Optimization dependency to
0.4.0
.
Bug Fixes
- Fixed streaming mode hang in remote executor.
- Wrap
collections.namedtuple._asdict
calls incollections.OrderedDict
to
support Python 3.8. - Correctly serialize/deserialize
tff.TensorType
with unknown shapes. - Cleanup TF lookup HashTable resources in TFF execution.
- Fix bug in Shakespeare dataset where OOV and last vocab character were the
same. - Fix TFF ingestion of Keras models with shared embeddings.
- Closed hole in compilation to CanonicalForm.
Known Bugs
- "Federated Learning for Image Classification" tutorial fails to load
projector
plugin for tensorboard (https://github.com/tensorflow/federated/issues/914). - Certain Keras models with activity regularization fail in execution with
unliftable error (https://github.com/tensorflow/federated/issues/913).
Thanks to our Contributors
This release contains contributions from many people at Google, as well as: