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Hi. I think that this is something that I could tackle, initially for structured data. Is that o.k @wdeconinck @ytremolet ? Please tell me either way. I won't be offended if you say no. If the ans…
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I am trying to implement custom adjoints for Fast Fourier Transform (FFT) functions.
As the derivative of a DFT (discrete fourier transform) output is the inverse DFT of the derivative of the inputs,…
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Based on our schedule the next release is set to happen on the 19th of October, which means that the feature freeze will begin on the 12th of October (next Monday).
Release notes will be generated …
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The transpose (adjoint) of a sparse object is considered non-sparse. Steps to reproduce:
```
using SparseArrays
x = sparse(rand(10))
issparse(x) # true
issparse(x') # false, should be true
typ…
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I am having trouble using DynamicHMC + Zygote on a simple example using a constrained variable. This will work with ForwardDiff, but I am interested in Zygote because of the reverse mode autodiff and …
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```julia
using Flux, CuArrays
CuArrays.allowscalar(false)
dudt = Chain(Dense(2,50,tanh),Dense(50,2)) |> gpu
p,re = Flux.destructure(dudt)
Zygote.gradient(x->sum(re(p)(x)),cu(rand(2)))
```
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When running:
```
importer = pypesto.PetabImporter(petab_problem)
obj = importer.create_objective()
obj.amici_solver.setSensitivityMethod(2)
obj(petab_problem.x_nominal, sensi_orders=(0,1))
```
…
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It would be nice to have a `backsolve` function which is like `solve` but has the adjoints already setup with Zygote.jl, where it runs a choice gradient calculation when Zygote is used. We can set it …
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#### Summary:
Able to install `rstan`, but not `rstanarm`.
Reviewed and tried suggestions fron #293, #408 and #394, but no luck.
Tried installing a few ways, and all give the same error message…
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https://github.com/JuliaDiffEq/DiffEqFlux.jl/pull/96 got master to Zygote compatible, but there are still some feature regressions that need to be worked out before we can release:
- [ ] `diffeq_ad…