title: pytorch scoring set of images and evaluating results
body: <p>In Pytorch by using GPU (cuda) need to score a set of images given trained NN.
  The following code is meant to score a set of transformed images one by one.</p>
  
  <pre><code>model.to('cuda')
  model.eval()
  
  for ii, (inputs, classes) in enumerate(dataloaders['test']):
       inputs, classes = inputs, classes
       results = model.forward(inputs)
       ps = torch.exp(results)
  </code></pre>
  
  <p>Error Stack:</p>
  
  <pre><code>RuntimeError                              Traceback (most recent call last)
  &lt;ipython-input-24-948390e2b25a&gt; in &lt;module&gt;()
        5 for ii, (inputs, classes) in enumerate(dataloaders['test']):
        6      inputs, classes = inputs, classes
  ----&gt; 7      results = model(inputs)
        8      ps = torch.exp(results)
  
  /opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
      489             result = self._slow_forward(*input, **kwargs)
      490         else:
  --&gt; 491             result = self.forward(*input, **kwargs)
      492         for hook in self._forward_hooks.values():
      493             hook_result = hook(self, input, result)
  
  /opt/conda/lib/python3.6/site-packages/torchvision-0.2.1-py3.6.egg/torchvision/models/vgg.py in forward(self, x)
       40 
       41     def forward(self, x):
  ---&gt; 42         x = self.features(x)
       43         x = x.view(x.size(0), -1)
       44         x = self.classifier(x)
  
  /opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
      489             result = self._slow_forward(*input, **kwargs)
      490         else:
  --&gt; 491             result = self.forward(*input, **kwargs)
      492         for hook in self._forward_hooks.values():
      493             hook_result = hook(self, input, result)
  
  /opt/conda/lib/python3.6/site-packages/torch/nn/modules/container.py in forward(self, input)
       89     def forward(self, input):
       90         for module in self._modules.values():
  ---&gt; 91             input = module(input)
       92         return input
       93 
  
  /opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
      489             result = self._slow_forward(*input, **kwargs)
      490         else:
  --&gt; 491             result = self.forward(*input, **kwargs)
      492         for hook in self._forward_hooks.values():
      493             hook_result = hook(self, input, result)
  
  /opt/conda/lib/python3.6/site-packages/torch/nn/modules/conv.py in forward(self, input)
      299     def forward(self, input):
      300         return F.conv2d(input, self.weight, self.bias, self.stride,
  --&gt; 301                         self.padding, self.dilation, self.groups)
      302 
      303 
  </code></pre>
  
  <p>RuntimeError: Expected object of type torch.FloatTensor but found type torch.cuda.FloatTensor for argument #2 'weight'</p>
  
  <p>Model made on a GPU (cuda).</p>