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
{{ message }}
This repository has been archived by the owner on May 9, 2024. It is now read-only.
when i traing segmentation i meet a problem:
when i set batch_size=8 and iter_size=1,program case a problem "isinstance(x, (list,tuple)) and len(x)<=2, 'incorrect input'".
"isinstance(x, (list,tuple)) and len(x)<=2, 'incorrect input" is found in the file "/modules/pytorch_jacinto_ai/xvision/models/pixel2pixel/deeplabv3lite.py",local in line 106.
when i set batch_size=1 and iter_size=1 the model can be trained. Is the segmantation model must be trained one image by one?
can you tell me how can set batch size bigger than one or why i must set batch size to be one?
As i konow the model with "batchnorm" need a better result,usually need input images number bigger than one.
(other set if need ,model name is deeplabv3lite_mobilenetv2_tv i only have one gpu card)
The text was updated successfully, but these errors were encountered:
Sign up for freeto subscribe to this conversation on GitHub.
Already have an account?
Sign in.
when i traing segmentation i meet a problem:
when i set batch_size=8 and iter_size=1,program case a problem "isinstance(x, (list,tuple)) and len(x)<=2, 'incorrect input'".
"isinstance(x, (list,tuple)) and len(x)<=2, 'incorrect input" is found in the file "/modules/pytorch_jacinto_ai/xvision/models/pixel2pixel/deeplabv3lite.py",local in line 106.
when i set batch_size=1 and iter_size=1 the model can be trained. Is the segmantation model must be trained one image by one?
can you tell me how can set batch size bigger than one or why i must set batch size to be one?
As i konow the model with "batchnorm" need a better result,usually need input images number bigger than one.
(other set if need ,model name is deeplabv3lite_mobilenetv2_tv i only have one gpu card)
The text was updated successfully, but these errors were encountered: