Initial release of Model Zoo

We have added a large set of baseline results and pretrained models available for download in the pycls Model Zoo; including the simple, fast, and effective RegNet models that we hope can serve as solid baselines across a wide range of flop regimes.

New features included in this release:

• Cache model weight URLs provided in configs locally | 4e470e2
• Allow optional weight decay fine-tuning for BN params, changes the default BN weight decay | 4e470e2
• Support Squeeze & Excitation in AnyNet | ec18863
• RegNet model abstraction | 4f5b5da, 708d429, 24a2805
• Run precise time in test_net and count acts for a model | ad01b81

Other changes:

• Updated README | 4acac2b
• New Model Zoo | 4acac2b, 4f5b5da
• New configs for models from Designing Network Design Spaces paper | 44bcfa7, e9c1ef4