RuntimeError                              Traceback (most recent call last)
 in ()
----> 1 model = cycle(model = “resnet” ,  path = “Classify.pth” , epochs = 6 , depth = 0 , lr = 1e-3 , freeze = True)
 in cycle(model, path, epochs, depth, lr, freeze)
42     criterion = nn.CrossEntropyLoss()
43
—> 44     model.to(device)
45     print(" Error here ? ")
46
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in to(self, *args, **kwargs)
379             return t.to(device, dtype if t.is_floating_point() else None, non_blocking)
380
–> 381         return self._apply(convert)
382
383     def register_backward_hook(self, hook):
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in _apply(self, fn)
185     def _apply(self, fn):
186         for module in self.children():
–> 187             module._apply(fn)
188
189         for param in self._parameters.values():
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in _apply(self, fn)
191                 # Tensors stored in modules are graph leaves, and we don’t
192                 # want to create copy nodes, so we have to unpack the data.
–> 193                 param.data = fn(param.data)
194                 if param._grad is not None:
195                     param._grad.data = fn(param._grad.data)
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in convert(t)
377
378         def convert(t):
–> 379             return t.to(device, dtype if t.is_floating_point() else None, non_blocking)
380
381         return self._apply(convert)
RuntimeError: CUDA error: device-side assert triggered