0287abbf66
1166: Fix crossentropy when some probabilities are zero r=dhairyagandhi96 a=cossio Use a function `xlogy(x,y) = x * log(y)` that has the correct limit at `x=0`. Before this PR: ```julia julia> Flux.crossentropy([0.1,0.0,0.9], [0.1,0.0,0.9]) NaN ``` After this PR: ```julia julia> Flux.crossentropy([0.1,0.0,0.9], [0.1,0.0,0.9]) 0.3250829733914482 ``` Co-authored-by: cossio <j.cossio.diaz@gmail.com> |
||
|---|---|---|
| .github | ||
| docs | ||
| paper | ||
| src | ||
| test | ||
| .gitattributes | ||
| .gitignore | ||
| .gitlab-ci.yml | ||
| .travis.yml | ||
| CITATION.bib | ||
| LICENSE.md | ||
| Manifest.toml | ||
| NEWS.md | ||
| Project.toml | ||
| README.md | ||
| bors.toml | ||
README.md
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.
] add Flux
See the documentation or the model zoo for examples.
If you use Flux in your research, please cite our work.