Advanced PyTorch Graph Manipulation: FX Graph Mode Quantization Coding tutorial - Part 3/3
If you need help with anything quantization or ML related (e.g. debugging code) feel free to book a 30 minute consultation session! https://calendly.com/oscar-savolainen
I'm also available for long-term freelance work, e.g. for training / productionizing models, teaching AI concepts, etc.
Video Summary:
In this video, in part 3/3 of our coding tutorial on how to quantize a PyTorch ResNet with FX Graph Mode Quantization, we look at two advanced graph manipulation techniques.
The first is how one can iteratively propagate a tensor through the graph, and access intermediary tensors in a way that is reminiscent of forward hooks. The second is how one can swap out nodes: we use the example of using BatchNorm layers into their preceding Convolution layers.
Timestamps:
00:00 Intro
02:39 Iterating through the graph
11:17 Replacing nodes in the graph
18:42 Outro
Links:
Github for code: https://github.com/OscarSavolainen/Qu...
Connect on LinkedIn: / oscar-savolainen-phd-b88277121
На этой странице сайта вы можете посмотреть видео онлайн Advanced PyTorch Graph Manipulation: FX Graph Mode Quantization Coding tutorial - Part 3/3 длительностью часов минут секунд в хорошем качестве, которое загрузил пользователь Oscar Savolainen 22 Март 2024, поделитесь ссылкой с друзьями и знакомыми, на youtube это видео уже посмотрели 528 раз и оно понравилось 17 зрителям. Приятного просмотра!
