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Implementcupy.linalg.eig /cupy.linalg.eigvals#8854
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| cupy.linalg._util._check_cusolver_dev_info_if_synchronization_allowed( | ||
| cusolver.xgeev, dev_info) | ||
| if all(w.imag == 0.0): |
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I don't like theNumPy behavior but it looks like we have to follow... 🙁
Q: can we find a way to not create an intermediate array of bools for later reduction? Perhaps this can be replaced by a simpleReductionKernel?
| work = [_geev(a[ind, :, :], True) for ind in numpy.ndindex(a.shape[:-2])] | ||
| w = cupy.stack([x[0] for x in work]) | ||
| v = cupy.stack([x[1] for x in work]) |
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This uses a Python loop to call geev. I suggest:
- either we create an issue to track this overhead before merging, or
- we just move this loop to C++ in this PR (seecusolver.pyx for batched SVD/QR examples)
| @@ -88,7 +97,56 @@ def _syevd(a, UPLO, with_eigen_vector, overwrite_a=False): | |||
| return w.astype(w_dtype, copy=False), v.astype(v_dtype, copy=False) | |||
| # TODO(okuta): Implement eig | |||
| def _geev(a, with_eigen_vector, overwrite_a=False): | |||
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Q: it seems we never seeoverwrite_a being set toTrue?
@EarlMilktea any chance we can push this across the finish line? Do you need any help? Or should I find someone to take over? |
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sorry, confused myself... /test mini |
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Thiscloses#3255 and alsocloses#6359 .
This PR uses
cusolverDnXgeevto solve non-hermitian eigenvalue problems on GPU.