Microsoft today announced PyTorch Enterprise, a new Azure service that provides developers with additional support when using PyTorch on Azure. It's basically Microsoft's commercial support offering for PyTorch.
PyTorch is a Python-centric open-source machine learning framework with a focus on computer vision and natural language processing. It was originally developed by Facebook and is, at least to some degree, comparable to Google's popular TensorFlow framework.
Frank X. Shaw, Microsoft's corporate VP for communications, described the new PyTorch Enterprise service as providing developers with "a more reliable production experience for organizations using PyTorch in their data sciences work."
With PyTorch Enterprise, members of Microsoft's Premier and Unified support program will get benefits like prioritized requests, hands-on support and solutions for hotfixes, bugs and security patches, Shaw explained. Every year, Microsoft will also select one PyTorch version for long-term support.
Azure already made it relatively easy to use PyTorch, and Microsoft has long invested in the library by, for example, taking over the development of PyTorch for Windows last year. As Microsoft noted in today's announcement, the latest release of PyTorch will be integrated with Azure Machine Learning and the company promises to feed back to the public PyTorch distribution the PyTorch code it gets from developers.
Enterprise support will be available for PyTorch version 1.8.1 and up on Windows 10 and a number of popular Linux distributions.
"This new enterprise-level offering by Microsoft closes an important gap. PyTorch gives our researchers unprecedented flexibility in designing their models and running their experiments," said Jeremy Jancsary, senior principal research scientist at Nuance. "Serving these models in production, however, can be a challenge. The direct involvement of Microsoft lets us deploy new versions of PyTorch to Azure with confidence."
With this new offering, Microsoft is taking a page out of the open-source monetization playbook for startups by offering additional services on top of an open-source project. Since PyTorch wasn't developed by a startup, only to have a major cloud provider then offer its own commercial version on top of the open-source code, this feels like a rather uncontroversial move.