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Hi!
Arch/Manjaro user with a RX 6950 XT. I was trying to run the `TwoD_Julia` tutorial with an AMD GPU backend. I can successfully do `using AMDGPU` (I should say that some tests fail though) with an…
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Hello! First of all, thank you to the software writer for making this package. There are many examples with lovely pictures.
The documentation site says the package supports differentiating through…
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```
julia> which(Core.Compiler.is_pure_intrinsic_infer, (Core.IntrinsicFunction,)).sig
Tuple{typeof(Core.Compiler.is_pure_intrinsic_infer), Core.IntrinsicFunction} # good
julia> which(Core.Compil…
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There are many things to be said about how to grow and scale repositories. However, I think it's clear that OrdinaryDiffEq.jl is a repo that is currently hitting the scaling limits of Julia and thus a…
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Here is a MWE
```julia
using Enzyme
using FFTW
Enzyme.EnzymeRules.inactive(::typeof(FFTW.assert_applicable), args...) = nothing
function test(p, x)
p*x
return sum(abs2, x)
end
…
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This code causes an error exiting Julia during `Zygote.gradient `. Any ideas why? Without `additional` layer works fine.
```julia
try
deeponet = NeuralOperators.DeepONet(
…
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I am able to go up to second order derivatives with Enzyme. However, when I use the same approach to go for the third derivative, I get an error. Here is a minimal working example to show that. The la…
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**Describe the bug**
Hello, I want to use DynamicalSystems.jl to calculate the gradient, but the following problem occurs, which may be related to mutate array
**Minimal Working Example**
```
us…
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Hi @gdalle
I'm having problems trying to do nested jacobian calculations. This might be related to https://github.com/gdalle/DifferentiationInterface.jl/issues/345
MWE:
```julia
using Differe…
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Not sure why but it can be seen in https://github.com/FluxML/Flux.jl/pull/2464
e.g.
https://github.com/FluxML/Flux.jl/actions/runs/10435007814/job/28898510960?pr=2464#step:6:530