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Hello @li-js ,

I've been troubleshooting this error for a while now, but I'm unsure what is causing it. The Error occurs after iterating through a dozen or so images. Eventually, one of the tensors is only off by 1, and the program crashes. At first, I thought it was a rounding error caused by the outS function in the model_solver file. But, experimenting with it didn't fix the error. Recently, I noticed the tensors are different sizes on line 267 and 271 in the train.py file. But, I still don't know what is causing the problem. Also, I'm running on a cpu, so testing takes a while, but I'll have access to a gpu within the next week so.

Training Epoch 0/18 (3199.0 batches) ..:   0%| | 11/600Traceback (most recent call last):
  File "train.py", line 272, in <module>
    loss_tag_grp = myInstanceLoss.myInstanceLoss_group(tag, tag_target, ignore_index=None)
  File "libs/myInstanceLoss.py", line 118, in myInstanceLoss_group
    inst = pred[mask.expand_as(pred)].view(C,-1,1) #c x -1 x 1
RuntimeError: The expanded size of the tensor (76) must match the existing size (77) at non-singleton dimension 1.  Target sizes: [8, 76, 76].  Tensor sizes: [1, 77, 76]