pytorch-lightning
awesome
pytorch-lightning | awesome | |
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19 | 145 | |
19,188 | 301,348 | |
- | - | |
9.9 | 7.3 | |
almost 2 years ago | 9 days ago | |
Python | Shell | |
Apache License 2.0 | Creative Commons Zero v1.0 Universal |
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pytorch-lightning
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Problem with pytorch lightning and optuna with multiple callbacks
def on_validation_end(self, trainer: Trainer, pl_module: LightningModule) -> None: # Trainer calls `on_validation_end` for sanity check. Therefore, it is necessary to avoid # calling `trial.report` multiple times at epoch 0. For more details, see # https://github.com/PyTorchLightning/pytorch-lightning/issues/1391. if trainer.sanity_checking: return
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Please comment on my planned research project structure
Under the hood, the ModelWrapper object will create a ML model based on the config (so far, an XGBoost model and a PyTorch Lightning model). Each of those will have a wrapper that conducts training and evaluation (since from my understanding of Lightning, Trainers are required to be outside of the class). In lack of a better name, I call these wrappers Fitters. For uniformity, I thought about adding a common interface IFitter, which is inherited by all model wrappers as outlined below.
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Watch out for the (PyTorch) Lightning
Join their Slack to ask the community questions and check out the GitHub here.
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[P] Composer: a new PyTorch library to train models ~2-4x faster with better algorithms
Pytorch lightning benchmarks against pytorch on every PR (benchmarks to make sure that it is mot slower.
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[D] What Repetitive Tasks Related to Machine Learning do You Hate Doing?
There is already a ton of momentum around automating ML workflows. I would suggest you contribute to a preexisting project like, for instance, PyTorch Lightning or fast.ai.
- PyTorch Lightening
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[D] Are you using PyTorch or TensorFlow going into 2022?
Is the problem the sheer number of options, or the fact that they are all together in one place? Would it be better if they were organized into the different trainer entrypoints (fit, validate, ...)? If that is the case, there was an RFC proposing this which you might find interesting, feel free to drop by and comment on the issue: https://github.com/PyTorchLightning/pytorch-lightning/issues/10444
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[D] Colab TPU low performance
I wanted to make a quick performance comparison between the GPU (Tesla K80) and TPU (v2-8) available in Google Colab with PyTorch. To do so quickly, I used an MNIST example from pytorch-lightning that trains a simple CNN.
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[D] How to avoid CPU bottlenecking in PyTorch - training slowed by augmentations and data loading?
We've noticed GPU 0 on our 3 GPU system is sometimes idle (which would explain performance differences). However its unclear to us why that may be. Similar to this issue
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[P] An introduction to PyKale https://github.com/pykale/pykaleโ, a PyTorch library that provides a unified pipeline-based API for knowledge-aware multimodal learning and transfer learning on graphs, images, texts, and videos to accelerate interdisciplinary research. Welcome feedback/contribution!
If you want a good example for reference, take a look at Pytorch Lightning's readme (https://github.com/PyTorchLightning/pytorch-lightning) It answers the 3 questions of "what is this", "why should I care", and "how do i use it" almost instantly
awesome
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AI-generated content, other unfavorable practices get CNET on Wikipedia banlist
In the days before "google it" was a synonym for "find it", we had different curated link sites, and even pyhsical magazines with hand-curated lists of links that people interested in a certain topic might find interesting. This still exists today in some forms, for example the "awesome lists" that you see for some programming topics, for example https://github.com/sindresorhus/awesome .
Just like there was a time when 90%-99% of all email traffic was viagra spam, I imagine in the future most of the internet by volume will be AI-generated trash, and those in the know will still circulate lists of where the other 1% can be found.
An even brighter scenario is that someone, maybe a kid tinkering in their garage, figures out how to make a search engine that finds the good stuff, doesn't immediately die to AI bot farms' SEO efforts, and is financially viable.
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Resources I wish I knew when I started my career
2. Awesome Lists
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The Top 10 GitHub Repositories Making Waves ๐๐
Software Engineering Blogs
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Kyutai AI research lab with a $330M budget that will make everything open source
He appears to be the original creator of the โAwesome Xโ repo: https://github.com/sindresorhus/awesome
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โจ7 Github Repositories to Master React
Awesome React
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Do you know any books about programming worth reading?
I'm just going to leave this here: awesome git repo
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No More Problems With GitHub Issues
You don't need any particular requirement to consult issues section on GitHub. If you need a place to follow along this post, my chosen repository for today's blog post is Awesome.
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Artist for Hire?
I have an awesome list GitHub repository that needs a few icons & a banner made. I was wondering if any students in graphic design would be willing to commission a few for me? I'm willing to pay either hourly, or by the project and can pay cash or venmo. Note that the art will end up as CC0, so you'd essentially be waiving any right to the artwork.
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Pulling my site from Google over AI training
yah, come to think of it in the curated space, this reminds me of that awesome X family of github pages. Looks like someone compiled a bunch of them here https://github.com/sindresorhus/awesome#databases. I have found those to be highly valuable treasure troves pregnant with rich and relevant information.
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Top 10 "Must Have" Repositories for Web Developers
10. Awesome
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