cwlkr / torchvahadane Goto Github PK

I'm sorry to bother you, but is it possible to provide a graphics card for parallel processing of multiple slices at the same time? I use the for loop and it takes too long. An unknown error occurred when I used the from multiprocessing import Pool module. So I don't have any other options. thank you!

Attempt fix in #1
In the update_dict method in https://github.com/cwlkr/torchvahadane/blob/main/torchvahadane/dict_learning.py#L100, when the atomic norm is too small, the corresponding atom is re-initialized with tensor.normal_.
However, if all numbers drawn are negative, the following in-place clamp will yield a zero vector, and in the in-place normalization
of dictionary[:, k] /= dictionary[:, k].norm() a nan vector will be generated and this will invalidate the whole computation procedure.