utkuozbulak / pytorch-cnn-adversarial-attacks Goto Github PK

Iteration: 0

RuntimeError Traceback (most recent call last)
in ()
----> 1 FGS_untargeted.generate(original_image, org_class, target_class)

in generate(self, original_image, org_class, target_class)
48 out = self.model(processed_image)
49 # Calculate CE loss
---> 50 pred_loss = ce_loss(out, im_label_as_var)
51 # Do backward pass
52 pred_loss.backward()

~\anaconda3\lib\site-packages\torch\nn\modules\module.py in call(self, *input, **kwargs)
475 result = self._slow_forward(*input, **kwargs)
476 else:
--> 477 result = self.forward(*input, **kwargs)
478 for hook in self._forward_hooks.values():
479 hook_result = hook(self, input, result)

~\anaconda3\lib\site-packages\torch\nn\modules\loss.py in forward(self, input, target)
860 def forward(self, input, target):
861 return F.cross_entropy(input, target, weight=self.weight,
--> 862 ignore_index=self.ignore_index, reduction=self.reduction)
863
864

~\anaconda3\lib\site-packages\torch\nn\functional.py in cross_entropy(input, target, weight, size_average, ignore_index, reduce, reduction)
1548 if size_average is not None or reduce is not None:
1549 reduction = _Reduction.legacy_get_string(size_average, reduce)
-> 1550 return nll_loss(log_softmax(input, 1), target, weight, None, ignore_index, None, reduction)
1551
1552

~\anaconda3\lib\site-packages\torch\nn\functional.py in nll_loss(input, target, weight, size_average, ignore_index, reduce, reduction)
1405 .format(input.size(0), target.size(0)))
1406 if dim == 2:
-> 1407 return torch._C._nn.nll_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index)
1408 elif dim == 4:
1409 return torch._C._nn.nll_loss2d(input, target, weight, _Reduction.get_enum(reduction), ignore_index)

RuntimeError: Expected object of type torch.LongTensor but found type torch.IntTensor for argument #2 'target'