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@ -38,7 +38,7 @@ b = param(randn(2))
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y(x) = σ.(W * x .+ b)
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```
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If that's *still* not enough, you can go as deep as you want, even writing your own CUDA kernels! All this can be freely mixed-and-matched in a single model or script, and it all runs interactively via Jupyter or Juno.
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If that's *still* not enough, you can go as deep as you want, even writing your own CUDA kernels with [CUDAnative](https://github.com/JuliaGPU/CUDAnative.jl)! All this can be freely mixed-and-matched in a single model or script, and it all runs interactively via Jupyter or Juno.
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```julia
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function gpu_add(a, b, c)
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