Comments (3)
yaozhewei
commented on September 24, 2024
Hi Xinyue,
Yes, it is expected. The top50 eigenvalues will be very cost using hessian.eigenvalues(). Since your problem is only about 100, I would suggest you use hessian.density(), set the niter to be exactly like your problem dimension, that should be finished very fast and give you the distribution of the full eigenvalues.
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xinyueshen
commented on September 24, 2024
Thanks for the response! But does hessian.density() compute and return the eigenvectors at the same time?
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xinyueshen
commented on September 24, 2024
I see that hessian.density() computes the eigenvalues, not the eigenvectors, but it is much faster. Thanks!
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Related Issues (18)
- How do we compute eigenvalues of Hessian matrices for each weight matrices or for each module in a model rather than calculating the eigenvalue for the whole model?? HOT 10
- Hi, a question of inconsistency of the dymamics of tr(FIM) and tr(H).
- RuntimeError: element 0 of variables does not require grad and does not have a grad_fn HOT 2
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