These questions came up in a FESCo ticket [1] recently and the primary purpose of this thread is to have some public record of the conversation around the handling of pre-trained weights for AI/ML models as packaged for Fedora. [1] https://pagure.io/fesco/issue/3175 Intro and Definitions ===================== Previous conversations have involved a decent amount of confusion around terminology and I want to be clear about what I'm asking so I'm starting with a few definitions in the context of my questions. Artificial Neural Network (ANN) - effectively structured data consisting of neurons (nodes containing some value) organized into layers with various connections between the neurons. There are connections between neurons which control the flow of data through the entire network. The exact value of how the connections affect flow through the network is found through the training process and these values are generally referred to as weights. Model - A model by itself is a description of a specific ANN - how layers are configured, how they interact with each other, how model training is done, how data needs to be structured for using a trained model and so on. A model by itself is rarely, if ever useful. Models generally need to be trained on data before they can be used but many models offer a mechanism through which weights can be loaded from a model which has already been trained. An untrained model without pre-trained weights or training is pretty much code. Pre-Trined Weights - Pre-trained weights are essentially the data contained in a model after training the model on some input data. Training modern ANN models is a very expensive and time consuming process; pre-trained weights allow people to use models without having to train the model locally or even have access to data needed to train the model. Questions ========= 1. Are pre-trained weights considered to be normal non-code content/data or do they require special handling? 2. If an upstream offers pre-trained weights and indicates that those weights are available under a license which is acceptable for non-code content in Fedora, can those pre-trained weights be included in Fedora packages? 3. Extending question 2, is it considered sufficient for an upstream to have a license on pre-trained weights or would a packager/reviewer need to verify that the data used to train those weights is acceptable? 4. Is it acceptable to package code which downloads pre-trained weights from a non-Fedora source upon first use post-installation by a user if that model and its associated weights are a. For a specific model? b. For a user-defined model which may or may not exist at the time of packaging? I can provide examples of any of these situations if that would be helpful. Thanks, Tim -- _______________________________________________ legal mailing list -- legal@xxxxxxxxxxxxxxxxxxxxxxx To unsubscribe send an email to legal-leave@xxxxxxxxxxxxxxxxxxxxxxx Fedora Code of Conduct: https://docs.fedoraproject.org/en-US/project/code-of-conduct/ List Guidelines: https://fedoraproject.org/wiki/Mailing_list_guidelines List Archives: https://lists.fedoraproject.org/archives/list/legal@xxxxxxxxxxxxxxxxxxxxxxx Do not reply to spam, report it: https://pagure.io/fedora-infrastructure/new_issue
