Use PyTorch as the reference deep learning framework/architecture for future projects

[antoinecarme]

PyAF will use PyTorch as its deep learning architecture for future projects. A few reasons for this :

1. Pytorch is fully open source. Green (Ensure that PyAF is and remains Green #176 )
2. PyTorch internal/technical choices are very sane. It works even in very hash environments : SPARC64 architecture.
3. SPARC64 architecture : abandoned years ago, no commercial support, very strong technically ( manycore, > 128 threads), with approximate OS (Debian rocks here ;), was able to build a set of packages for PyTorch from scratch : https://github.com/antoinecarme/sparc-t3-data/tree/master/debian-sparc64/packages
4. PyAF runs OK with PyTorch on SPARC64 and uses all the 128 threads for some complex hierarchical forecasting models.

[antoinecarme]

Get rid of Keras and tensorflow. And now that we have pytorch working (#199 ), no need for scikeras in a pyaf context neither.

Less is better. Minimal is beautiful.

DeprecationWarning: KerasRegressor is deprecated, use Sci-Keras (https://github.com/adriangb/scikeras) instead. See https://www.adriangb.com/scikeras/stable/migration.html for help migrating.

[antoinecarme]

Closing.