hello @ptrblck, i am working on a project related to person re-identification. I am trying to re-implement that code of one of the CVPR paper entitled “ABD-Net: Attentive but Diverse Person Re-Identification”. I trained the ABD-Net architecture with resnet and densenet but when i am trying to train the architecture using shufflenet backbone I face this error. Could you please help me…
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File “train.py”, line 147, in main
train(epoch, model, criterion, regularizer, optimizer, trainloader, use_gpu, fixbase=True)
File “train.py”, line 246, in train
loss = criterion(outputs, pids)
File “C:\Users\Hayat\AppData\Local\Continuum\anaconda3\lib\site-packages\torch\nn\modules\module.py”, line 493, in  call
result = self.forward(*input, **kwargs)
File “F:\hayat ullah work\Attention Code\paper 2_new code\torchreid\losses\cross_entropy_loss.py”, line 56, in forward
return self._forward(inputs[1], targets)
File “F:\hayatullah work\Attention Code\paper 2_new code\torchreid\losses\cross_entropy_loss.py”, line 52, in _forward
return sum([self.apply_loss(x, targets) for x in inputs_tuple]) / len(inputs_tuple)
File “F:\hayat ullah work\Attention Code\paper 2_new code\torchreid\losses\cross_entropy_loss.py”, line 52, in
return sum([self.apply_loss(x, targets) for x in inputs_tuple]) / len(inputs_tuple)
File “F:\hayat ullah work\Attention Code\paper 2_new code\torchreid\losses\cross_entropy_loss.py”, line 32, in apply_loss
log_probs = self.logsoftmax(inputs)
File “C:\Users\Hayat\AppData\Local\Continuum\anaconda3\lib\site-packages\torch\nn\modules\module.py”, line 493, in  call
result = self.forward(*input, **kwargs)
File “C:\Users\Hayat\AppData\Local\Continuum\anaconda3\lib\site-packages\torch\nn\modules\activation.py”, line 1179, in forward
return F.log_softmax(input, self.dim, _stacklevel=5)
File “C:\Users\Hayat\AppData\Local\Continuum\anaconda3\lib\site-packages\torch\nn\functional.py”, line 1350, in log_softmax
ret = input.log_softmax(dim)
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)