Hi people, A year ago I raised a topic on -devel, pointing out the "deep learning v.s. software freedom" issue. We drew no conclusion at that time, and linux distros who care about software freedom may still have doubt on some fundamental problems, e.g. "is this piece of deep learning software really free"?
People do lazy execution on this problem. Now that a related package entered my packaging radar, and I think I'd better write a draft and shed some light on a safety area. Then here is the first humble attempt: https://salsa.debian.org/lumin/deeplearning-policy (issue tracker is enabled) This draft is conservative and overkilling, and currently only focus on software freedom. That's exactly where we start, right? Specifically, I defined 3 types of pre-trained machine learning models / deep learning models: Free Model, ToxicCandy Model. Non-free Model Developers who'd like to touch DL software should be cautious to the "ToxicCandy" models. Details can be found in my draft. Apart from that, I pointed out in the draft that software associated with any critical task should be considered carefully as deep neural networks introduced a new kind of vulnerability, that a network's response can be disrupted or even controlled by some carefully designed perturbations added to the network put. Hence, I suggest that packaging an intelligent software must be discussed on -devel if the piece of software is associated with any kind of critical task, including but not limited to * authentication (e.g. login via face verification or identification) * program execution (e.g. intelligent voice assistants: "Hey, Siri! sudo rm -rf / --no-preserve-root") * physical object manipulation (e.g. mechanical arms in non-educational occasion, cars i.e. auto pilot), etc. See my draft for details. The package that entered my packaging radar is nltk_data. https://github.com/nltk/nltk_data The 2 most widely used python-based computational linguistics toolkit, NLTK and Spacy, require these data (datasets + models) to enable most of their functionalities. Best, Mo.