Neural Structured Learning v1.1.0

Release 1.1.0

Major Features and Improvements

• Introduces nsl.tools.build_graph, a function for graph building.

• Introduces nsl.tools.pack_nbrs, a function to prepare input for
  graph-based NSL.

• Adds tf.estimator.Estimator support for NSL. In particular, this release
  introduces two new wrapper functions named
  nsl.estimator.add_graph_regularization and
  nsl.estimator.add_adversarial_regularization to wrap existing
  tf.estimator.Estimator-based models with NSL. These APIs are currently
  supported only for TF 1.x.

Bug Fixes and Other Changes

• Adds version information to the NSL package, which can be queried as
  nsl.__version__.

• Fixes loss computation with Loss objects in AdversarialRegularization.

• Adds a new parameter to nsl.keras.adversarial_loss which can be used to
  pass additional arguments to the model.

• Fixes typos in documentation and notebooks.

• Updates notebooks to use the release version of TF 2.0.

Thanks to our Contributors

This release contains contributions from many people at Google.