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Re:ONNX: The Open Standard for Seamless Machine Learning Int... by morkalork on Thursday August 15, 2024 @11:00AM (#41256904)
Well, it's definitely an improvement over raw dogging deserialized pickled ML models.
Re:ONNX: The Open Standard for Seamless Machine Learning Int... by bunderbunder on Thursday August 15, 2024 @11:10AM (#41257003)
Unfortunately, at least as of last time I evaluated it, it still can't handle certain things that are currently only done with pickling in the Python ecosystem. Much of what's covered by scikit-learn's feature_extraction package, for example.

Not, I think, for any reason that's inherent to what those components are doing; a lot of it's just that much of the existing Python ML ecosystem was not engineered with robust productionization in mind. Possibly because the very existence of Pickle means everyone has an easy (if horrifying) way to get the job done for 0 effort. As the sklearn maintainers remind people every time they close an issue that asks for it, robust and secure model serialization is something that would have had to have been designed into the project from day 1, and doing it now would essentially require a rewrite.

Re:ONNX: The Open Standard for Seamless Machine Learning Int... by kitchen_sink on Thursday August 15, 2024 @11:20AM (#41257093)
It’s still a WIP but skops (https://skops.readthedocs.io/en/stable/) may be of interest (for secure sklearn serialization)