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We could have possibly the following examples:
- [x] A simple U-Net (pulled from fastMRI dataset possibly), trained? @Lenoush can you handle this in your free time? #199 #209
- [ ] A network built …
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I have the following minimized code (has no logic implemented) and when I run with loose types I get a bug report
This generates an error, without the LooseTypes there's no error
```
$ RUSTBACKTRACE=…
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It would be awesome if the backing array implementation supported auto differentiation, that we could access some `grad` method from Cubed.
It looks like a bunch of stakeholder libraries have this…
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Here is the example:
```julia
using TensorKit, Zygote
g(x)=real(scalar(x'*x))
V=Z3Space(0=>2,1=>2,2=>2);
A=randn(ComplexF64,V*V*V',one(V));
gradient(g,A)
```
Output:
```
ERROR: MethodError…
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| Metadata | |
| -------- | --- |
| Owner(s) | @ZuseZ4 |
| Team(s) | [compiler](http://github.com/rust-lang/compiler-team), [lang](http://github.com/rust-lang/lang-team) |
| Goal…
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I am on Enzyme main (b63f36f6) and Julia 1.10.6. The following used to work.
```julia
using Enzyme
f_nest(x) = 2 * x^4
deriv(f, x) = first(first(autodiff(Reverse, f, Active(x))))
f′(x) = deriv(f_nest,…
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I am on Enzyme main (30b6b2d93d8ef1bdfb9f628e8c111d123cc4595e), CUDA master (7ff012) and Julia 1.10.6.
```julia
using Enzyme, CUDA
function f(a, b)
c = a .+ b
Array(c)[1]
end
a = CuArray(rand(…
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Lots of boxes! Gotta check them all!
### Forward mode
- [ ] libxc interfacing
- [ ] upstream FFT stuff
- [ ] figure out the T = promote_type pattern and use it consistently
- [ ] make sure ever…
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The following script fails:
```julia
using Gridap
using Gridap.CellData
model = CartesianDiscreteModel((0,1,0,1),(2,2))
Ω_space = Triangulation(model,[1,2])
reffe = ReferenceFE(lagrangi…
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### Issue type
Bug
### Have you reproduced the bug with TensorFlow Nightly?
No
### Source
binary
### TensorFlow version
2.17.0
### Custom code
No
### OS platform and distribution
Linux ubun…