Add custom jax jvp for solve_sylvester#2116
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| # We're manually overriding the jax jvp for this Op, so we test the gradients too | ||
| A_bar, B_bar, C_bar = pt.grad(out.sum(), [A, B, C]) | ||
| compare_jax_and_py([A, B, C], [A_bar, B_bar, C_bar], [A_val, B_val, C_val]) |
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this doesn't test the jax jvp though?
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Jax added support for
solve_sylvesterbut they didn't add a VJP. There is a bunch of discussion about corner cases in this thread. I don't think we care -- these are about schur/eigenproblems. This is implicated in the autograd graph of solve_sylvester, but we can directly use adjoints. This is already what we do in python/c/numba. Kind of niche, but it comes up in statespace models using nutpie with gradient_backend='jax'.