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Add an example to the readme? #2067

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merged 7 commits into from
Oct 8, 2022
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Add an example to the readme? #2067

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1b7cf9d
add example to readme
mcabbott Sep 26, 2022
b490002
add installation note, tweak
mcabbott Sep 26, 2022
a22a904
tweak wording, remove tutorials link
mcabbott Sep 27, 2022
37cdcca
try adding comments
mcabbott Sep 27, 2022
6689513
mv slack to text, add downloads badge
mcabbott Oct 2, 2022
1a42167
change to use logitcrossentropy
mcabbott Oct 6, 2022
e1ca78b
mention that loss(x,y) closes over model
mcabbott Oct 7, 2022
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25 changes: 22 additions & 3 deletions README.md
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Expand Up @@ -2,7 +2,13 @@
<img width="400px" src="https://raw.githubusercontent.com/FluxML/fluxml.github.io/master/logo.png"/>
</p>

[![][action-img]][action-url] [![](https://img.shields.io/badge/docs-stable-blue.svg)](https://fluxml.github.io/Flux.jl/stable/) [![](https://img.shields.io/badge/chat-on%20slack-yellow.svg)](https://julialang.org/slack/) [![DOI](https://joss.theoj.org/papers/10.21105/joss.00602/status.svg)](https://doi.org/10.21105/joss.00602) [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac) [![][codecov-img]][codecov-url]
<div align="center">

[![](https://img.shields.io/badge/Documentation-stable-blue.svg)](https://fluxml.github.io/Flux.jl/stable/) [![DOI](https://joss.theoj.org/papers/10.21105/joss.00602/status.svg)](https://doi.org/10.21105/joss.00602) [![Flux Downloads](https://shields.io/endpoint?url=https://pkgs.genieframework.com/api/v1/badge/Flux)](https://pkgs.genieframework.com?packages=Flux)
<br/>
[![][action-img]][action-url] [![][codecov-img]][codecov-url] [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)

</div>

[action-img]: https://github.com/FluxML/Flux.jl/workflows/CI/badge.svg
[action-url]: https://github.com/FluxML/Flux.jl/actions
Expand All @@ -11,10 +17,23 @@

Flux is an elegant approach to machine learning. It's a 100% pure-Julia stack, and provides lightweight abstractions on top of Julia's native GPU and AD support. Flux makes the easy things easy while remaining fully hackable.

Works best with [Julia 1.8](https://julialang.org/downloads/) or later. Here's a simple example to try it out:
```julia
] add Flux
using Flux # should install everything for you, including CUDA

x = hcat(digits.(0:3, base=2, pad=2)...) |> gpu # let's solve the XOR problem!
y = Flux.onehotbatch(xor.(eachrow(x)...), 0:1) |> gpu
data = ((Float32.(x), y) for _ in 1:100) # an iterator making Tuples

model = Chain(Dense(2 => 3, sigmoid), BatchNorm(3), Dense(3 => 2)) |> gpu
optim = Adam(0.1, (0.7, 0.95))
mloss(x, y) = Flux.logitcrossentropy(model(x), y) # closes over model

Flux.train!(mloss, Flux.params(model), data, optim) # updates model & optim
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@mcabbott mcabbott Oct 7, 2022 •
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BTW, this business of defining a loss which, unlike what Flux.Losses calls a loss, closes over the model, was pretty confusing to me when I first tried Flux.

train! needs two different objects with implicit references to the model (and optim ends up with them), but does not seem to see the model itself? That's pretty weird.

IMO we should define crossentropy(m, x, y) = crossentropy(m(x), y) globally, and make Flux 0.14 do this, which is much less confusing:

model = Chain(Dense(2 => 3, sigmoid), BatchNorm(3), Dense(3 => 2)) |> gpu
optim = Flux.setup(model, Adam(0.1, (0.7, 0.95)))  # stores Adam's momenta

Flux.train!(Flux.logitcrossentropy, model, data, optim)  # updates model & optim

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This seems the way forward to move train! away from Params.


all((softmax(model(x)) .> 0.5) .== y) # usually 100% accuracy.
```

See the [documentation](https://fluxml.github.io/Flux.jl/) or the [model zoo](https://github.com/FluxML/model-zoo/) for examples.
See the [documentation](https://fluxml.github.io/Flux.jl/) for details, or the [model zoo](https://github.com/FluxML/model-zoo/) for examples. Ask questions on the [Julia discourse](https://discourse.julialang.org/) or [slack](https://discourse.julialang.org/t/announcing-a-julia-slack/4866).

If you use Flux in your research, please [cite](CITATION.bib) our work.