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
x = self.gud_up_proj_layer4(x, skip4) # 64 channels features
x= self.gud_up_proj_layer5(x) # blur depth
guidance = self.gud_up_proj_layer6(x) # affinity matrix
x = self.post_process_layer(guidance, x, sparse_depth)
`
I think the first x is 64 channels features, which are used to generate blur depth and affinity matrix, and the second x is blur depth. Therefore, the input of self.gud_up_proj_layer6 is the first x. I modify the code as follows:
`
x = self.gud_up_proj_layer4(x, skip4)
blur_depth = self.gud_up_proj_layer5(x)
guidance = self.gud_up_proj_layer6(x)
x = self.post_process_layer(guidance, blur_depth, sparse_depth)
`
And I find the cspn.py have the following errors.
IndexError: only integers, slices (:), ellipsis (...), None and long or byte Variables are valid indices (got float)
So, I suggest replace '/'(div operation) using '//' when you want to get 'int' rather than 'float'.
The text was updated successfully, but these errors were encountered:
This is independent of the version of pytorch. I guess you used python3, In python3 the default types output from div is float. My configuration is python2 + pytorch0.3. So If you use python3, you could add int() to convert the type from float to int.
x = self.gud_up_proj_layer4(x, skip4) # 64 channels features
x= self.gud_up_proj_layer5(x) # blur depth
guidance = self.gud_up_proj_layer6(x) # affinity matrix
x = self.post_process_layer(guidance, x, sparse_depth)
`
I think the first x is 64 channels features, which are used to generate blur depth and affinity matrix, and the second x is blur depth. Therefore, the input of self.gud_up_proj_layer6 is the first x. I modify the code as follows:
`
x = self.gud_up_proj_layer4(x, skip4)
blur_depth = self.gud_up_proj_layer5(x)
guidance = self.gud_up_proj_layer6(x)
x = self.post_process_layer(guidance, blur_depth, sparse_depth)
I also find this bug. Can you double-check it? @XinJCheng Thanks!
`
`
I think the first x is 64 channels features, which are used to generate blur depth and affinity matrix, and the second x is blur depth. Therefore, the input of self.gud_up_proj_layer6 is the first x. I modify the code as follows:
`
`
And I find the cspn.py have the following errors.
So, I suggest replace '/'(div operation) using '//' when you want to get 'int' rather than 'float'.
The text was updated successfully, but these errors were encountered: