I haven't heard of tangent before.

Can you clarify more what the project would do? Wouldn't it be enough
to just run sympy.python() on an expression, then pass that to
tangent?

Aaron Meurer

On Thu, Mar 1, 2018 at 12:46 PM, Navjot Kukreja <[email protected]> wrote:
> Hello everyone
>
> I am Navjot Kukreja, a PhD student at Imperial College London. I would like
> to propose a GSoC project to enable automatic differentiation of Sympy
> constructs using tangent (https://github.com/google/tangent). Tangent does
> source-to-source automatic differentiation directly on python code. The
> ability to perform automatic differentiation on python code that contains
> sympy constructs would enable/simplify the use of sympy in defining various
> optimization problems, which is a very broad class of problems in
> HPC/Science/Engineering. It also makes it easier to use sympy in the
> construction of DSL compilers.
>
>
> Has this been considered before? Is there someone in the community that has
> tried this or needs this?
>
>
> Thank you
>
> Navjot Kukreja
>
> https://github.com/navjotk
>
>
> PS: I am one of the developers of Devito (https://github.com/opesci/devito),
> a sympy-based DSL for the rapid development of high-performance
> finite-difference simulations. The primary use of devito is as part of
> PDE-constrained optimization problems where the problem definition,
> including the objective function, governing PDE, interpolators etc. are
> provided as a combination of sympy expressions and pure python.
>
>
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