RuntimeError                              Traceback (most recent call last)
 in 
21         optimizer.zero_grad()
22         # forward pass: compute predicted outputs by passing inputs to the model
—> 23         output = model(data)
24         # calculate the batch loss
25         loss = criterion(output, target)
c:\users\ahmedsedik\anaconda2\envs\maskrcnn\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)
 in forward(self, x)
23     def forward(self, x):
24         # add sequence of convolutional and max pooling layers
—> 25         x = self.pool(F.relu(self.conv1(x)))
26         x = self.pool(F.relu(self.conv2(x)))
27         x = self.pool(F.relu(self.conv3(x)))
c:\users\ahmedsedik\anaconda2\envs\maskrcnn\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)
c:\users\ahmedsedik\anaconda2\envs\maskrcnn\lib\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,
–> 301                         self.padding, self.dilation, self.groups)
302
303
RuntimeError: CuDNN error: CUDNN_STATUS_ARCH_MISMATCH