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Getting NaNs

Hi,
When running inside network training, after a while with some probability i'm getting nan for one instance in the batch. All the eigen values and the eigen vecotrs are nan.
The matrix batch in this case is 1024X64X64 and it is real and symmetric. I'm using ed_plus.
It seems to have a relation to the batch size, as the same matrix that caused the nan, doesn't nan when taken alone or with a smaller batch.
Ant idea of where I should investigate this?
Thanks!

Doesn't work for matrix sizes which are not powers of 2

BatchED.utils_ed_plus.Batched_ED_Plus.apply just gives an error... Generally, its quite hard to find a use for such a code.

[utils_ed_plus.py:217](https://file+.vscode-resource.vscode-cdn.net/mnt/hd1/Dropbox/tmp/projects/SNIPPETS/torch_eigs/BatchED/utils_ed_plus.py:217), in DivideStep(x_orig)
    [215](file:///mnt/hd1/Dropbox/tmp/projects/SNIPPETS/torch_eigs/BatchED/utils_ed_plus.py?line=214) t1 = x[:, :half_size, :half_size]
    [216](file:///mnt/hd1/Dropbox/tmp/projects/SNIPPETS/torch_eigs/BatchED/utils_ed_plus.py?line=215) t2 = x[:, half_size:, half_size:]
--> [217](file:///mnt/hd1/Dropbox/tmp/projects/SNIPPETS/torch_eigs/BatchED/utils_ed_plus.py?line=216) return torch.cat([t1,t2],dim=0), xnorm, beta

RuntimeError: Sizes of tensors must match except in dimension 0. Expected size 4 but got size 5 for tensor number 1 in the list.

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