lax.custom_linear_solve primitive #1402
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The primitive's implementation and JVP rules are now 100% pytree free.
dougalm
approved these changes
Oct 3, 2019
jekbradbury
reviewed
Oct 4, 2019
|
Please take another look. I rewrote everything so |
gehring
reviewed
Oct 10, 2019
gehring
reviewed
Oct 10, 2019
|
This is ready for a final (?) review. |
This was referenced Oct 20, 2019
dougalm
approved these changes
Oct 21, 2019
| """Transpose a linear function.""" | ||
| # TODO(shoyer): can we use something more direct than the vjp machinery? | ||
| # It's particularly awkward that we need the second argument to give | ||
| # particular values of the primals, which are entirely arbitrary. |
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Good idea. It might be a new transformation, but one that shares a lot of machinery with the existing jvp/transpose.
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A follow-on to
lax.rootfrom #1339. See the tests for a simple example of defining gradients for an iterative linear solver.Eventually, I expect to use this for implementing iterative solvers (e.g., GMRES, CG) from
scipy.sparse.linalg, which in turn we will use for the linear solves needed for gradients inscipy.optimize.root.