You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Unless I'm doing something wrong, there is a corner case inside def __wct_core, when one of the matrices is basically a vector.
When calculating: contentConv = torch.mm(cont_feat, cont_feat.t()).div(cFSize[1] - 1) + iden
cFSize[1] is 1 so there is a division by 0=> and we get a matrix full of NAN which is causing the SVD to fail.
For now, as a w/a inside def __feature_wct
I've changed the condtion if cont_mask[0].size <= 0 or styl_mask[0].size <= 0:
continue
to
if cont_mask[0].size <= 1 or styl_mask[0].size <= 1:
continue
to ignore labels that causing this issue.
Any idea why it happens and what is the best approach to fix it?
The text was updated successfully, but these errors were encountered:
Unless I'm doing something wrong, there is a corner case inside def __wct_core, when one of the matrices is basically a vector.
When calculating:
contentConv = torch.mm(cont_feat, cont_feat.t()).div(cFSize[1] - 1) + iden
cFSize[1] is 1 so there is a division by 0=> and we get a matrix full of NAN which is causing the SVD to fail.
For now, as a w/a inside
def __feature_wct
I've changed the condtion
if cont_mask[0].size <= 0 or styl_mask[0].size <= 0:
continue
to
if cont_mask[0].size <= 1 or styl_mask[0].size <= 1:
continue
to ignore labels that causing this issue.
Any idea why it happens and what is the best approach to fix it?
The text was updated successfully, but these errors were encountered: