Jax vs. Julia (Vs PyTorch)

• Enzyme

  16 1,174 9.7 LLVM

  High-performance automatic differentiation of LLVM and MLIR. (by EnzymeAD)

  

Idk, Enzyme is pretty next gen, all the way down to LLVM code.

https://github.com/EnzymeAD/Enzyme

• functorch

  11 1,377 0.0 Jupyter Notebook

  functorch is JAX-like composable function transforms for PyTorch.

  

Tangentially related but there is an effort to get some of the features of JAX into PyTorch: https://pytorch.org/functorch/

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• Flux.jl

  22 4,405 8.7 Julia

  Relax! Flux is the ML library that doesn't make you tensor

  

> In his item #1, he links to https://discourse.julialang.org/t/loaderror-when-using-inter... The issue is actually a Zygote bug, a Julia package for auto-differentiation, and is not directly related to Julia codebase (or Flux package) itself. Furthermore, the problematic code is working fine now, because DiffEqFlux has switched to Enzyme, which doesn't have that bug. He should first confirm whether the problem he is citing is actually a problem or not.

> Item #2, again another Zygote bug.

If flux chose a buggy package as a dependency, that's on them, and users are well justified in steering clear of Flux if it has buggy dependencies. As of today, the Project.toml for both Flux and DiffEqFlux still lists Zygote as a dependency. Neither list Enzyme.

https://github.com/FluxML/Flux.jl/blob/master/Project.toml

• DiffEqFlux.jl

  2 843 9.0 Julia

  Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

  

Suggest a related project