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1.0.3b

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Major (Breaking)

1. Coupling layers were refactored to ensure consistency. Old checkpoints may no longer load.

Minor (Features)

1. Added ``attention.py`` module containing helper networks for building transformers
2. Added ``SetTransformer`` class in ``summary_networks.py`` as a viable alternative to ``DeepSet`` summary networks.
3. Added ``TimeSeriesTransformer`` class in ``summary_networks.py`` as a viable alternative to ``SequentialNetworks`` summary networks.
4. Added ``plot_z_score_contraction()`` diagnostic in ``diagnostics.py`` for gauging global inferential adequacy
5. Added ``Orthogonal`` in ``helper_networks.py`` for learnable generalized permutations.

1.0.2b

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Minor

1. Added option for residual networks in coupling blocks using a ``residual=True`` in the coupling layer config.

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