loss = nn.CrossEntropyLoss()
input = torch.randn(3, 5, requires_grad=True)
target = torch.empty(3, dtype=torch.long).random_(5)
output = loss(input, target)
print(output)
output.backward()

tensor(1.6685)
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-5-835ec6ff9004> in <module>()
      4 output = loss(input, target)
      5 print(output)
----> 6 output.backward()

1 frames
/usr/local/lib/python3.6/dist-packages/torch/autograd/__init__.py in backward(tensors, grad_tensors, retain_graph, create_graph, grad_variables)
     98     Variable._execution_engine.run_backward(
     99         tensors, grad_tensors, retain_graph, create_graph,
--> 100         allow_unreachable=True)  # allow_unreachable flag
    101 
    102 

RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn