Here an example:
aa = torch.nn.functional.log_softmax(torch.autograd.Variable(torch.randn(4, 3), requires_grad=1), 1)                                   
b = torch.diag(aa, 1)
c = torch.sum(b)
c.backward()


> RuntimeError                              Traceback (most recent call last)
> <ipython-input-30-4857ca7423f9> in <module>()
> ----> 1 c.backward()
> 
> /usr/local/lib/python2.7/dist-packages/torch/autograd/variable.pyc in backward(self, gradient, retain_graph, create_graph, retain_variables)
>     165                 Variable.
>     166         """
> --> 167         torch.autograd.backward(self, gradient, retain_graph, create_graph, retain_variables)
>     168 
>     169     def register_hook(self, hook):
> 
> /usr/local/lib/python2.7/dist-packages/torch/autograd/__init__.pyc in backward(variables, grad_variables, retain_graph, create_graph, retain_variables)
>      97 
>      98     Variable._execution_engine.run_backward(
> ---> 99         variables, grad_variables, retain_graph)
>     100 
>     101 
> 
> RuntimeError: output and gradOutput shapes do not match: output [4 x 3], gradOutput [3 x 3] at /data/packages/pytorch/torch/lib/THNN/generic/LogSoftMax.c:73


however, when the matrix a is square I dont get the error.