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MWE:
```julia
using Turing: Turing
using Enzyme: Enzyme
Enzyme.API.runtimeActivity!(true)
Turing.@model function demo()
x ~ Turing.Normal()
y ~ Turing.Normal()
end
model = demo(…
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MWE:
```julia
using Random: randn
using Enzyme: Enzyme
using Turing: Turing
Enzyme.API.runtimeActivity!(true)
Turing.@model function MvDirichletWithManualAccumulation(w, doc)
β ~ Turing…
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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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```julia
using Zygote: Zygote
struct VNV{TVal}
vals::TVal
bv::BitVector
end
f(x) = VNV(x, BitVector(undef, 1)).vals
Zygote.pullback(f, [1.0])
```
The above fails with
```
ERRO…
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MWE (PR: https://github.com/JuliaGPU/AMDGPU.jl/pull/668):
```julia
using AMDGPU
using EnzymeCore, Enzyme
function square_kernel!(x)
i = workitemIdx().x
x[i] *= x[i]
return
end
…
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## Describe the bug
The following code produces an error:
```julia
ᶜgradᵥ = Operators.GradientF2C()
level_field = Fields.level(Fields.Field(Float64, center_space), 1)
ᶠscalar_field = Fields.Fie…
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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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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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Logical indexing of a matrix using .== doesn't work for oneAPI:
```
using oneAPI
A = oneArray(rand(Float32, (1000, 1000)))
A[A .== 0] .= 1.0f0
```
```
ERROR: LoadError: GPU compilation of M…
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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…