Comments (4)
MikeInnes
commented on July 23, 2024
3
Indeed there is.
julia> function foo(x)
z = zero(x)
for i in eachindex(x)
z[i] = x[i]
end
return z
end
foo (generic function with 1 method)
julia> gradient(x -> sum(foo(x)), [1, 2, 3])
([1, 1, 1],)This is on Zygote#mutate, and you'll also need julia master to avoid the control flow issue.
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antoine-levitt
commented on July 23, 2024
1
There seems to be ongoing work on that: https://discourse.julialang.org/t/chainrules-replacing-diffrules-in-the-julia-ad-world/17608/42, https://github.com/FluxML/Zygote.jl/branches
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Roger-luo
commented on July 23, 2024
I see....
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MikeInnes
commented on July 23, 2024
Closing in favour of #61
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Related Issues (20)
- Method ambiguities reported by Aqua
- slow/high allocation gradient with mapreduce and iterators HOT 11
- error in summation of product iterator HOT 2
- `sort(x; rev=true)` is not supported HOT 1
- Incorrect gradients for `plan_rfft(x) * x` HOT 2
- Gradient of scalar function of gradient giving mutating array error HOT 4
- `sum` with CUDA and view on array errors HOT 3
- Cannot take gradient of sort on 2D CuArray HOT 1
- `Ref` and broadcasting issue HOT 1
- Strip zygote frames from mutation error stack trace HOT 1
- Zygote in Julia 1.10+ not reading rrules for default constructors HOT 7
- Few issues in the Zygote Home Page documentation HOT 1
- OOM when computing the gradient in an embarrassingly parallel problem HOT 1
- Pullback over jacobian HOT 6
- `withjacobian` flattens the output when it is a matrix HOT 1
- Gradient wrt to a sparse matrix is mathematically wrong HOT 6
- Increasing memory usage in each call of gradient HOT 1
- Precompilation error in Julia nightly HOT 1
- Gradient involving `LinearAlgebra.tr` errors HOT 1
- Device-to-host copies with GPU code HOT 11
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