AttributeError                            Traceback (most recent call last)
 in 
44
45         with torch.no_grad():
—> 46             output = model(image)
47             test_image_output = output.data.cpu().numpy()
48             for i in test_image_output:
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in call(self, *input, **kwargs)
545             result = self._slow_forward(*input, **kwargs)
546         else:
–> 547             result = self.forward(*input, **kwargs)
548         for hook in self._forward_hooks.values():
549             hook_result = hook(self, input, result)
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\container.py in forward(self, input)
90     def forward(self, input):
91         for module in self._modules.values():
—> 92             input = module(input)
93         return input
94
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in call(self, *input, **kwargs)
545             result = self._slow_forward(*input, **kwargs)
546         else:
–> 547             result = self.forward(*input, **kwargs)
548         for hook in self._forward_hooks.values():
549             hook_result = hook(self, input, result)
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\container.py in forward(self, input)
90     def forward(self, input):
91         for module in self._modules.values():
—> 92             input = module(input)
93         return input
94
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in call(self, *input, **kwargs)
545             result = self._slow_forward(*input, **kwargs)
546         else:
–> 547             result = self.forward(*input, **kwargs)
548         for hook in self._forward_hooks.values():
549             hook_result = hook(self, input, result)
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\linear.py in forward(self, input)
85
86     def forward(self, input):
—> 87         return F.linear(input, self.weight, self.bias)
88
89     def extra_repr(self):
C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\functional.py in linear(input, weight, bias)
1365         - Output: :math:(N, *, out\_features)
1366     “”"
-> 1367     if input.dim() == 2 and bias is not None:
1368         # fused op is marginally faster
1369         ret = torch.addmm(bias, input, weight.t())