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Recently，I upgraded my Ubuntu from 22.04 to 24.04 and found the performence of my trained deep network written by torch degrade. After debug, I found the problem is copying data from one gpu to another. The test code:

a=np.ones([2,64,1500,800]).astype('float32')
a=torch.from_numpy(a)
b=a.to('cuda:0').to('cuda:1')
c=a.to('cuda:0').cpu().to('cuda:1')
print(torch.min(b))  ### 0
print(torch.min(c))  ### 1

The value of b is very strange. Some values of entries in b are 0 and the others are 1. Can someone give the reasons?

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  • Your code runs correctly on my device; have you tried testing it on two different docker images (i.e., ubuntu 22.04 and ubuntu 24.04)? Commented Jul 4 at 0:12
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