Provide state-of-the-art models with performances as close as possible to the original models:

We provide at least one example for each architecture which reproduces a result provided by the official authors
    of said architecture.

The code is usually as close to the original code base as possible which means some PyTorch code may be not as
    pytorchic as it could be as a result of being converted TensorFlow code and vice versa.

A few other goals: