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
Hi , Thanks a lot for your great work,I mitigated SSW and SCF to my own Project with similar backbone. But the SSW loss is a NAN, so I debuged it and found it's 'num_sensitive_sum' being zero after ‘mask_matrix’ multiplied by self.reversal_eye.
Even if I set 'num_sensitive_sum' to 0.0001 , the SWW loss becomes zero too.
Is there a bug here or am I understanding it wrong?
mask_matrix = mask_matrix.view(B, -1)
for midx in range(B):
mask_matrix[midx][indices] = 1
mask_matrix = mask_matrix.view(B, self.dim, self.dim)
mask_matrix = mask_matrix * self.reversal_eye
num_sensitive_sum = torch.sum(mask_matrix)
if num_sensitive_sum==0:
num_sensitive_sum=0.0001
The text was updated successfully, but these errors were encountered:
Sorry to reply late. num_sensitive_sum sums the number of pixels that are sensitive to viewpoint changes. In our experiments, we did not observe cases in that num_sensitive_sum equals zero. And it is not proper to set num_sensitive_sum to 0.0001 as it is an integer.
Hi , Thanks a lot for your great work,I mitigated SSW and SCF to my own Project with similar backbone. But the SSW loss is a NAN, so I debuged it and found it's 'num_sensitive_sum' being zero after ‘mask_matrix’ multiplied by self.reversal_eye.
Even if I set 'num_sensitive_sum' to 0.0001 , the SWW loss becomes zero too.
Is there a bug here or am I understanding it wrong?
The text was updated successfully, but these errors were encountered: