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