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When the VJP is not an abstract array, things get weird
```julia
julia> import AbstractDifferentiation as AD
julia> import Zygote
julia> ad_backend = AD.ReverseRuleConfigBackend(Zygote.Zygot…
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```julia
using ChainRulesCore, Zygote
f(x) = 2x
ChainRulesCore.rrule(::typeof(f), x) = 2x, d -> (NoTangent(), @not_implemented(""), )
Zygote.gradient(f, 1)
```
The last line returns `(noth…
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### Is there an existing issue for this?
- [X] I have searched the existing issues
### Problem description
During plugin development, when using `addonmanager_utilities.restart_freecad()` for…
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对于isolated process(隔离进程,或者叫孤立进程),不被允许访问现在替换的clipboard service,所以无法与在system server运行的管理服务进行交互,可能需要改替换目标;而且它每次运行的uid都是随机的,很难判断它属于哪个app;
至于app zygote,它是一个child zygote,根本不被允许进行binder transaction,需要想办法绕开;…
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MWE
```julia
using Zygote, LinearAlgebra
N = 4
u0 = rand(N)
ps = rand(N)
mats = (rand(N,N), rand(N,N),) # (A, B,)
nums = (rand(), rand(),) # (α, β,)
loss_m = function(p)
v = D…
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I would like to compute the gradient of a function that contains a `ForwardDiff.gradient`/`ForwardDiff.derivative`.
Computing that higher order gradient with ForwardDiff works, but will be slow for m…
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I found Zygote's recent advancement in AD and tried to benchmark it and found the following:
```
julia> @time ForwardDiff.gradient(rosenbrock,x);
0.074665 seconds (9 allocations: 1.070 MiB)
…
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MWE:
```julia
using Turing, Distributions, Random, KernelDensity
x1 = rand(Normal(10, 1), 200)
x2 = rand(Normal(8, 1), 200)
struct KDEDist f(x), rand(a)) # Vector{Float64}:
Zygote.gra…
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Hi,
I've stumbled upon this really weird bug where I was getting invalid types in my code, but only if the piece of code in question was executed with Zygote...
I've simplified the example to this…
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Doing the following outputs a reasonable error? Any hints? Doing a similar function without AxisKeys works, however the advantage of using the `time` dimension is lost, which I would like to keep.
…