Facebook’s PyTorch has grown to become one of the most popular deep learning frameworks in the world, and today it’s getting new libraries and big upgrades, including stable C++ frontend API support and library upgrades like TorchServe, a model-serving library developed in collaboration with Amazon Web Services.

The TorchServe library comes with support for both Python and TorchScript models; it provides the ability to run multiple versions of a model at the same time or even roll back to previous versions in a model archive.

PyTorch 1.5 also includes TorchElastic, a library developed to allow AI practitioners to scale up or down cloud training resources based on needs or if things go wrong.

An AWS integration with Kubernetes for TorchElastic enables container orchestration and fault

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