New features and improvements

• Two new losses based on standard Keras cross-entropy losses with a settable temperature for softmax:
  • TauSparseCategoricalCrossentropy equivalent to Keras SparseCategoricalCrossentropy
  • TauBinaryCrossentropy equivalent to Keras BinaryCrossentropy
• New module deel.lip.compute_layer_sv to compute the largest and lowest singular values of layers compute_layer_sv() or of a whole model compute_model_sv().
• Power iteration algorithm for convolution.
• New "Getting Started" tutorial to introduce 1-Lipschitz neural networks.
• Documentation migration from Sphinx to MkDocs.

API changes

• Activations are now imported via deel.lip.layers submodule, e.g. deel.lip.layers.GroupSort instead of deel.lip.activations.GroupSort. We adopted the same convention as Keras. The legacy submodule is still available for retro-compatibility but will be removed in a future release.
• Unconstrained layers must now be imported using deel.lip.layers.unconstrained submodule, e.g. deel.lip.layers.unconstrained.PadConv2D.

Fixes

• Fix InvertibleUpSampling __call__() returning None.

Full changelog: v1.4.0...v1.5.0