SwifterSwift
pytorch-lightning
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| SwifterSwift | pytorch-lightning | |
|---|---|---|
| 2 | 8 | |
| 13,635 | 26,883 | |
| 0.7% | 2.0% | |
| 7.5 | 9.9 | |
| 1 day ago | 2 days ago | |
| Swift | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SwifterSwift
- What’s your must have Extensions?
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Weekly Developer Roundup #23 - Sun Nov 22 2020
SwifterSwift/SwifterSwift (Swift): A handy collection of more than 500 native Swift extensions to boost your productivity.
pytorch-lightning
- Lightning AI Studios – A persistent GPU cloud environment
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Como empezar con inteligencia artificial?
https://see.stanford.edu/Course/CS229 https://lightning.ai/ https://www.youtube.com/watch?v=00s9ireCnCw&t=57s https://towardsdatascience.com/
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Best practice for saving logits/activation values of model in PyTorch Lightning
I've been wondering on what is the recommended method of saving logits/activations using PyTorch Lightning. I've looked at Callbacks, Loggers and ModelHooks but none of the use-cases seem to be for this kind of activity (even if I were to create my own custom variants of each utility). The ModelCheckpoint Callback in its utility makes me feel like custom Callbacks would be the way to go but I'm not quite sure. This closed GitHub issue does address my issue to some extent.
- New to ML, which is easier to learn - Tensorflow or PyTorch?
- PyTorch Lightning – DL framework to train, deploy, and ship AI fast
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We just release a complete open-source solution for accelerating Stable Diffusion pretraining and fine-tuning!
Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase , lucidrains, Stable Diffusion, Lightning and Hugging Face. Thanks for open-sourcing!
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An elegant and strong PyTorch Trainer
For lightweight use, pytorch-lightning is too heavy, and its source code will be very difficult for beginners to read, at least for me.
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[D] Mixed Precision Training: Difference between BF16 and FP16
For the A100 GPU, theoretical performance is the same for FP16/BF16 and both rely on the same number of bits, meaning memory should be the same. However since it's quite newly added to PyTorch, performance seems to still be dependent on underlying operators used (pytorch lightning debugging in progress here).
What are some alternatives?
EZSwiftExtensions - :smirk: How Swift standard types and classes were supposed to work.
lnd - Lightning Network Daemon ⚡️
SwiftyUtils - All the reusable code that we need in each project
Eclair - A scala implementation of the Lightning Network.
Reusable - A Swift mixin for reusing views easily and in a type-safe way (UITableViewCells, UICollectionViewCells, custom UIViews, ViewControllers, Storyboards…)
mmdetection - OpenMMLab Detection Toolbox and Benchmark
Pluralize.swift - Great Swift String Pluralize Extension
composer - Supercharge Your Model Training
R.swift - Strong typed, autocompleted resources like images, fonts and segues in Swift projects
umbrel - A beautiful home server OS for self-hosting with an app store. Buy a pre-built Umbrel Home with umbrelOS, or install on a Raspberry Pi 4, Pi 5, any Ubuntu/Debian system, or a VPS.
SwiftGen - The Swift code generator for your assets, storyboards, Localizable.strings, … — Get rid of all String-based APIs!
Keras - Deep Learning for humans