jax-models
elegy
jax-models | elegy | |
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6 | 5 | |
138 | 463 | |
- | 0.0% | |
0.0 | 0.0 | |
almost 2 years ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | MIT License |
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jax-models
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[D] How to contribute to open source ML and DL without having access to high quality setup?
I was in the same position as you are and the best thing you can do is to start reproducing papers (that's what I did with jax-models). This will
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[D] Should We Be Using JAX in 2022?
I've been using JAX, especially Flax for quite some time now for my reproducibility initiative (jax_models) and this is what I really appreciate about the framework
- Weekly updated open sourced model implementations in Flax
- Weekly updated open sourced deep learning model implementations in Flax
- [P] Weekly updated open sourced model implementations in Flax
elegy
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is Elegy framework for JAX abandoned?
I wonder if https://github.com/poets-ai/elegy is still an active project or dead because it hasn't had a commit in almost a year. Would be too bad if abandoned because I like it.
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[D] Any less-boilerplate framework for Jax/Flax/Haiku?
Elegy might be worth a look.
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PyTorch vs. TensorFlow in Academic Papers
JAX is really cool, but still somewhat immature. I would love to see it taking more ground and improving wrt e.g. integration with tensorboard and getting all the goodies we have in tensorflow. If you are looking for a higher level framework, I would recommend elegy [0] which is very close to the keras API.
[0] https://github.com/poets-ai/elegy
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[D] Should We Be Using JAX in 2022?
What's your favorite Deep Learning API for JAX - Flax, Haiku, Elegy, something else?
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Best sources to learn JAX?
For a Module library checkout Flax or Haiku, they are well maintained. For a Trainer interface like Keras / Pytorch Lightning checkout Elegy: https://github.com/poets-ai/elegy
What are some alternatives?
datasets - TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
dm-haiku - JAX-based neural network library
flax - Flax is a neural network library for JAX that is designed for flexibility.
jax-resnet - Implementations and checkpoints for ResNet, Wide ResNet, ResNeXt, ResNet-D, and ResNeSt in JAX (Flax).
flaxmodels - Pretrained deep learning models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet, etc.
equinox - Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
GradCache - Run Effective Large Batch Contrastive Learning Beyond GPU/TPU Memory Constraint
scenic - Scenic: A Jax Library for Computer Vision Research and Beyond
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
runtime - A performant and modular runtime for TensorFlow