Hessian and Jacobian #117
Hessian and Jacobian #117
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Since fwd_adj is theoretically the fastest higher order mode for computing Hessians, I'm unsure if I should implement overloads for other modes or enforce fwd_adj with Hessian. |
Edited: I think |
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Also we would like to eventually move the implementations of Hessian and Jacobian into source files, explicitly instantiating them for the possible types T where it makes sense. This gives us a chance to potentially optimise / parallelise the code in future directly with XAD compilation and keep the user code compatible.
You will also need to add some reference doc for these, but it's ok to do this at the end.
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Also feel free to merge or rebase |
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Please disregard this for now. The templated iterator approach will not allow to move this to a source file. We can worry at this later if it's needed. |
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Microsoft has made a jump in the toolset version recently - latest Visual Studio 2022 is now toolset 14.4. That makes the Windows builds fail. I'd say we make the toolsets tested 14.0, 14.1, 14.2, 14.4 now. |
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Also a note regarding the documentation you added. The files under docs/ref go verbatim onto the documentation reference section on the website. They need to be written in the style of a reference manual - showing the functions provided, listing/explaining their parameters, along with a short description what the function or header does. Similar to the other files there. I believe headers.md will also need to be adapted for the 2 new headers that aren't included by default. We will have to extend the docs in this part of the website (not part of this repository), and we will take part of what you have written so far for that with the next release. |
- Added sample programs for Hessian and Jacobian - Added doc for Hessian and Jacobian - Tweaked TypeTraits tests to be easier to understand - Changed order of some checks for iterators Upcoming: - More efficient fwd Jacobian computation - Possibly less evaluations of foo for Jacobian
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auto-differentiation-dev
merged commit 26d2385
into
auto-differentiation:main
Description
Implementation of Hessian and Jacobian class methods as per #37.
Features:
Unrelated changes: