Comments (2)
ybdai7
commented on September 24, 2024
2
I think more proper modification would be:
a_, b_ = torch.linalg.eig(T)
eigen_list = a_.real
weight_list = b_.real[0,:]**2
according to the source code. It would be nice if the author can fix this. But i think this repo is no longer maintained.
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amkmpro
commented on September 24, 2024
Hello, you must change these codes in 'hessian.py'
line 275:
a_, b_ = torch.linalg.eig(T)
eigen_list = a_.real
weight_list = b_.real**2
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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
- Where is the hessian trace calculation w.r.t activations? HOT 1
- Computing sum of square of diagonal entries of Hessian
- edits for PINN/custom loss functions
- How to calculate average Hessian trace?
- Potential bugs
- No module named 'pyhessian.client'
- deprecation of torch.eig method
- Question about backward() with create_graph=True warning
- A question on the computation of Hessian-vector product HOT 2
- Large variance of results HOT 1
- computational (time) cost HOT 3
- RuntimeError: derivative for grid_sampler_2d_backward is not implemented HOT 1
- Unexpected `shape` issue in Hessian-Vector computation HOT 4
- Hi! Can Pyhessian Perform stage-wise Hessian trace?
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