SymPy integration - #502
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Hi Christian, thank you for the PR, this looks like a very useful feature. My suggestion would be to do another crunching pass over the code. 1.5K is .. a lot! I feel like this code has some of the fluffiness of partly AI-generated and could do with some simplification passes to reduce it to a more minimal form (matching also the documented API surface). Thanks, |
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I realize I never submitted my comments from the original PR :-(
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This PR adds integration to sympy using the
dr.wrapdecorator.SymPy is a symbolic expressions engine. This PR adds it as a target for
dr.wrap, allowing us to compute higher order derivatives (hessians) etc in Dr.Jit. In contrast to other targets for this decorator the SymPy target does not exchange data between the libraries at runtime, but rather traces the symbolic expressions generated by the wrapped function, and compiles it to Dr.Jit. The wrapped function therefore acts like an ordinary Dr.Jit function, while we can use the complicated symbolic operations supported by SymPy. The wrapped functions are restricted to per-lane operations. Inverting aMatrix4finside of this wrapper will generate the necessary code for Dr.Jit to invert the matrix. Calling the function with a Matrix array in Dr.Jit will therefore invert each matrix per SIMD lane.