runtime
elegy
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| runtime | elegy | |
|---|---|---|
| 2 | 5 | |
| 744 | 463 | |
| 0.1% | 1.5% | |
| 9.6 | 0.0 | |
| 3 days ago | over 1 year ago | |
| C++ | Python | |
| Apache License 2.0 | MIT License |
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.
runtime
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If data science uses a lot of computational power, then why is python the most used programming language?
For reference: In Tensorflow and JAX, for example, the tensor gets compiled to the intermediate XLA format (https://www.tensorflow.org/xla), then passed to the XLA complier (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla/service) or the new TFRT runtime (https://github.com/tensorflow/runtime/blob/master/documents/tfrt_host_runtime_design.md), or some more esoteric hardware (https://github.com/pytorch/glow).
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PyTorch vs. TensorFlow in Academic Papers
what are your thoughts on https://github.com/tensorflow/runtime ?
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?
serving - A flexible, high-performance serving system for machine learning models
dm-haiku - JAX-based neural network library
glow - Compiler for Neural Network hardware accelerators
jax-resnet - Implementations and checkpoints for ResNet, Wide ResNet, ResNeXt, ResNet-D, and ResNeSt in JAX (Flax).
julia - The Julia Programming Language
equinox - Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
XLA.jl - Julia on TPUs
flax - Flax is a neural network library for JAX that is designed for flexibility.
tensorflow - An Open Source Machine Learning Framework for Everyone
scenic - Scenic: A Jax Library for Computer Vision Research and Beyond
long-range-arena - Long Range Arena for Benchmarking Efficient Transformers
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more