An official release candidate of PyTorch 1.0, the Python-centric deep learning framework created by Facebook, is available for developer testing. One of the most touted features of the new release is the ability to define models by writing Python code that can be selectively accelerated—similar to how competing frameworks work.

Python’s traditional role in machine learning has been to wrap high-speed, back-end code libraries with easy-to-use, front-end syntax. Anyone who writes machine learning modules in Python quickly discovers that native Python isn’t nearly fast enough for performance-critical research work or production use.

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