FluxML/Zygote.jl on Hacker News

…everything seems to work better regarding AD. [0]: https://github.com/FluxML/Flux.jl [1]: https://github.com/FluxML/Zygote.jl [2]: https://github.com/JuliaDiff/Diffractor.jl [3]: https://github.com/EnzymeAD/Enzyme.jl

comment by roflmaostc · 2023-12-04 · in Potential of the Julia programming language for high energy physics computing

…GPU libraries ( https://github.com/JuliaGPU/CUDA.jl ), the same automatic differentiation library ( https://github.com/FluxML/Zygote.jl ), and of course the same JIT compiler (Julia itself). These two libraries are far enough apart that…

comment by ChrisRackauckas · 2023-02-28 · in ML would have advanced faster if another front-end language had been adopted?

…over code execution without changing languages, just as you'd get in a self-hosted language. [1] https://github.com/FluxML/Zygote.jl

comment by eigenspace · 2021-10-28 · in Why Lisp? (2015)

…autodiff system for general purpose Python. Like there is for general purpose Julia code? ( https://github.com/FluxML/Zygote.jl ) > I have nothing against supporting GPUs (although I think their use is overrated and most people would do…

comment by UncleOxidant · 2021-03-05 · in PyTorch 1.8, with AMD ROCm support

…about how they would go about it now), but practically with technology like Julia's Zygote: https://github.com/FluxML/Zygote.jl the efficiency of autodiff might be similar to that of an opcode anyway. So, how did DEC do on the Alpha…

comment by koalahedron · 2021-03-02 · in The KimKlone Microcomputer

Well, Julia already got it via https://github.com/FluxML/Zygote.jl

comment by remexre · 2021-02-12 · in Swift for TensorFlow Shuts Down

…all function calls to also tranform their code. It's super powerful For example Zygote.jl ( https://github.com/FluxML/Zygote.jl ) implements reverse mode automatic differentiation, by defining a function that is a generated transformation…

comment by oxinabox · 2021-01-09 · in Ask HN: Show me your half baked project

…to the point where you can easily create your own operators to create the high level blocks. [1] https://github.com/FluxML/Zygote.jl [2] https://github.com/JuliaGPU/CUDAnative.jl [3] https://github.com/FluxML/Flux.jl

comment by ddragon · 2020-04-09 · in Swift: Google’s Bet on Differentiable Programming

…https://github.com/FluxML/Tracker.jl ) - [Yota]( https://github.com/dfdx/Yota.jl ) - [Zygote]( https://github.com/FluxML/Zygote.jl ) - [ReverseDiff]( https://github.com/JuliaDiff/ReverseDiff.jl ) - [AutoGrad.jl](…

comment by oxinabox · 2020-04-08 · in Jax – Composable transformations of Python and NumPy programs

…so much control flow via Zygote, which hooks into the compiler and differentiates the AST: https://github.com/FluxML/Zygote.jl

comment by logicchains · 2020-03-22 · in Julia 1.4

…extensive reuse of code within the Julia ecosystem. Specifically capabilities such as Zygote.jl ( https://github.com/FluxML/Zygote.jl ) for differentiable programming have the potential to dramatically make it easy to apply ML techniques…

comment by ViralBShah · 2019-12-16 · in Jeff Dean interview: Machine learning trends in 2020

…natural than just using the host language. I can't say how it would look using monads though. [1] https://github.com/FluxML/Zygote.jl

comment by ddragon · 2019-11-13 · in Differentiable Programming Manifesto

Julia seems to be making good progress on this front anyways :) https://github.com/FluxML/Zygote.jl

comment by cbkeller · 2019-11-13 · in Differentiable Programming Manifesto

Julia's compiler lets you hook into it and make something mind blowing like Zygote.jl https://github.com/FluxML/Zygote.jl

comment by xiaodai · 2019-11-04 · in Kotlingrad: A shape-safe DSL for differentiable programming

…a source to source differentiator could deal with all these (where well defined of course), e.g.: https://github.com/FluxML/Zygote.jl julia> fs = Dict("sin" => sin, "cos" => cos, "tan" => tan); julia> gradient(x -> fs[readline()](x), 1)…

comment by Certhas · 2019-09-06 · in Differentiable Programming Mega-Proposal

…innovations being implemented in Julia. We have working code to code automatic differentiation: https://github.com/FluxML/Zygote.jl Finally, the core team is paying attention to the problems and addressing them. All my top complaints are…

comment by Certhas · 2019-08-18 · in Giving up on Julia (2016)

Yes https://github.com/FluxML/Zygote.jl "Without compromising on performance, Zygote supports the full flexibility and dynamism of the Julia language, including control flow, recursion, closures, structs, dictionaries, and more."

comment by ddragon · 2019-07-19 · in A Differentiable Programming System to Bridge ML and Scientific Computing

…repos on Github - Zygote.jl, Cassette.jl, ForwardDiff.jl, model zoo in FluxML org and so on. https://github.com/FluxML/Zygote.jl https://github.com/jrevels/Cassette.jl https://github.com/JuliaDiff/ForwardDiff.jl https://github.com/FluxML

comment by ViralBShah · 2019-07-19 · in A Differentiable Programming System to Bridge ML and Scientific Computing

…code, Knet.jl [4], and the Tensorflow bindings [5]. [1] https://github.com/FluxML/Flux.jl [2] https://github.com/FluxML/Zygote.jl [3] https://julialang.org/blog/2019/01/fluxdiffeq [4] https://github.com/denizyuret/Knet.jl [5]…

comment by ddragon · 2019-06-10 · in Matlab–Python–Julia Cheatsheet

▲ 3

Zygote.jl: 21st Century Automatic Differentiation

story by adamnemecek · 2018-12-17 · 0 comments

…can apply AD to an anonymous function that looks up a function in a hash table from user input. https://github.com/FluxML/Zygote.jl

comment by stabbles · 2018-12-04 · in Building a Language and Compiler for Machine Learning

▲ 3

Zygote: Taking Gradients in Julia's Compiler

story by one-more-minute · 2018-10-26 · 0 comments

…next step was to actually embed AD as part of a language. I work on Julia, so I hope Zygote.jl ( https://github.com/FluxML/Zygote.jl ) gets there first, but it's always good to see others moving in the same direction.

comment by simonbyrne · 2018-10-22 · in First-Class Automatic Differentiation in Swift