v6.10.0: CPU efficiency improvements, refactoring

✨ Major features and improvements

• Provisional CUDA 9 support. CUDA 9 removes a compilation flag we require for CUDA 8. As a temporary workaround, you can build on CUDA 9 by setting the environment variable CUDA9=1. For example:

CUDA9=1 pip install thinc==6.10.0

• Improve efficiency of NumpyOps.scatter_add, when the indices only have a single dimension. This function was previously a bottle-neck for spaCy.
• Remove redundant copies in backpropagation of maxout non-linearity
• Call floating-point versions of sqrt, exp and tanh functions.
• Remove calls to tensordot, instead reshaping to make 2d dot calls.
• Improve efficiency of Adam optimizer on CPU.
• Eliminate redundant code in thinc.optimizers. There's now a single Optimizer class. For backwards compatibility, SGD and Adam functions are used to create optimizers with the Adam recipe or vanilla SGD recipe.

👥 Contributors

Thanks to @RaananHadar for the pull request!