Thank you … It solved the error
But can you explain for me what does this flag/option does ? like why in the beginning I had a mismatch in dimensions, and how this is solved ?
Another thing, I got now a different error

Traceback (most recent call last):
  File "main.py", line 506, in <module>
    main(parser.parse_args())
  File "main.py", line 460, in main
    model = train(args, model, True) #Train encoder
  File "main.py", line 232, in train
    loss = criterion(outputs, targets[:, 0])
  File "/home/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 491, in __call__
    result = self.forward(*input, **kwargs)
  File "main.py", line 82, in forward
    return self.loss(torch.nn.functional.log_softmax(outputs, dim=1), targets)
  File "/home/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 491, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/.local/lib/python2.7/site-packages/torch/nn/modules/loss.py", line 193, in forward
    self.ignore_index, self.reduce)
  File "/home/.local/lib/python2.7/site-packages/torch/nn/functional.py", line 1334, in nll_loss
    return torch._C._nn.nll_loss2d(input, target, weight, size_average, ignore_index, reduce)
RuntimeError: input and target batch or spatial sizes don't match: target [5 x 64 x 85], input [5 x 13 x 64 x 86] at /pytorch/aten/src/THCUNN/generic/SpatialClassNLLCriterion.cu:24