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minimal working example:
```cpp
#include "clad/Differentiator/Differentiator.h"
#include "clad/Differentiator/STLBuiltins.h"
#include
#include
double fnTuple(double x, double y) {
doub…
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Currently the **Docker (Advanced)** section of the [Hosting](https://www.rplumber.io/articles/hosting.html) vignette has two subsections:
- [Multiple Applications on One Port](https://www.rplumber.…
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### Preflight Checklist
* [x] I agree to follow the [Code of Conduct](https://github.com/jgraph/drawio/blob/master/CODE_OF_CONDUCT.md) that this project adheres to.
* [x] I have searched the iss…
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Test:
```cpp
#include "clad/Differentiator/Differentiator.h"
class SimpleFunctions1 {
public:
SimpleFunctions1() noexcept : x(0), y(0) {}
SimpleFunctions1(double p_x, double p_y) noexcept …
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Larger PDE solves may benefit from a reverse mode AD and also helps with adding support for neural networks as surrogates or part of training the PDEs themselves, therefore I was wondering what it wou…
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I tried running the last example in the README with an HMC sampler substituted for the MALA one:
```
using Klara
plogtarget(z) = -dot(z, z)
p = BasicContMuvParameter(:p, logtarget=plogtarget…
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The following minimal function results in a segfault (run on Enzyme's main as of 2023-11-26, Julia v1.10.0-rc1). If removing the `@turbo` annotation, the autodiff works fine.
```julia
using LoopV…
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Hello. I am reverse-engineering the binary protocol that the Gree app uses to talk to the Wifi unit, and I am seeing a similar packet structure. The status packet used for my unit has a length field o…
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I'm trying to differentiate the MJX step function via the autograd function `jax.grad()` in JAX, like:
```
def step(vel, pos):
mjx_data = mjx.make_data(mjx_model)
mjx_data = mjx_data.replace(q…
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Has this already been considered?
This request would add a mode to flip the "confirmation" from having the requestor click back to confirm to having the calendar owner confirm the slot within some …