Comments (2)
Hi,
It seems that the problem is not with ForwardDiff, but with Adapt.jl https://github.com/JuliaGPU/Adapt.jl. Can you tell us your Julia version?
from forwarddiff.jl.
from forwarddiff.jl.
Related Issues (20)
- Correctly forming nested dual numbers. HOT 8
- Derivative of a function of derivatives HOT 7
- Symbolics.jl compatibility HOT 1
- Support derivative(f, ::Complex) HOT 1
- `ForwardDiff` fails to compute correct derivative HOT 3
- Incorrect Hessian by `exp` function HOT 1
- Method ambiguities reported by Aqua HOT 3
- Document internals? HOT 1
- Bug (NaNs) when differentiating eigenvectors of Symmetric matrices HOT 1
- Error requiring `Symbolics` from `Optimization` HOT 1
- promote_rule ambiguity with AbstractIrrational and ForwardDiff.Dual HOT 2
- Allocation tests broken since Julia 1.9
- Working with anonymous functions HOT 2
- DiffResults objects are not re-aliased properly HOT 2
- `gradient!` allocates for matrices but not for vectors
- ERROR: Package ForwardDiff errored during testing HOT 1
- Reinterpret discards information and returns incorrect result HOT 4
- NaN gradient occurring in `SpecialFunctions.gamma`, when using float arguments. HOT 2
- Cannot compute gradient with `ArrayPartition` that holds containers of different types HOT 3
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from forwarddiff.jl.