help! RuntimeError: result type Float can't be cast to the desired output type Long

[asdjklfgh]

File "D:\AP\Anaconda\ANaconda\lib\site-packages\torch\nn\modules\module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "D:\AP\Anaconda\ANaconda\lib\site-packages\torch\nn\modules\loss.py", line 713, in forward return F.binary_cross_entropy_with_logits(input, target, File "D:\AP\Anaconda\ANaconda\lib\site-packages\torch\nn\functional.py", line 3132, in binary_cross_entropy_with_logits return torch.binary_cross_entropy_with_logits(input, target, weight, pos_weight, reduction_enum) RuntimeError: result type Float can't be cast to the desired output type Long

[newkinf]

Do you know how to solve this problem now？

[Z1176893827]

Do you know how to solve this problem now？

Do you know how to solve this problem now？...i have the same problem

[newkinf]

Do you know how to solve this problem now？

Do you know how to solve this problem now？...i have the same problem

d_target_label_cover = d_target_label_cover.float() I solve this problem like this, by adding .float() behind the "d_target_label_cover "

[Z1176893827]

Do you know how to solve this problem now？

Do you know how to solve this problem now？...i have the same problem

d_target_label_cover = d_target_label_cover.float() I solve this problem like this, by adding .float() behind the "d_target_label_cover "

I had a problem when I was testing，If I want to adjust different attack intensity, for example, crop 0.5 to 0.8, do I need to retrain the model? If not, how do I adjust the attack intensity parameters