问pytorch错误：“预期的isFloatingType(grad.scalar_type()) x (input_is_complex == grad_is_complex)为真，但为假”

EN

def forward(self, x):
    #Encoder Process
    out = self.feature(x)
    out = self.encoder(out)
    out = self.last(out)

    #### Start of error point ######
    batch_size, y = out.size()
    out_real = x[:, 0:int(y / 2)]
    out_comp = x[:, int(y / 2) : y + 1]
    out_comp = out_comp * 1j
    symbols = out_real + out_comp

    n = torch.randn(symbols.shape. dtype=torch.cfloat).to(device) 
    out = symbols + n 
    out_real = out.real 
    out_imag = out.imag 
    out = torch.cat((out_real, out_imag),1)
    #### End of error point ######

    #Decoder process
    out0 = self.decoder0(out)

    out1 = self.decoder1(out0)
    out1 += self.shortcut(out0)

    out2 = self.decoder2(out1)
    out2 += self.shortcut(out1)

    ---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-8-a131419c404b> in <module>
      6 for epoch in range(start_epoch, start_epoch+total_epoch):
      7     start = time.time()
----> 8     train(epoch, scheduler)
      9     end = time.time()
     10     total_time += (end-start)

<ipython-input-4-d3b479d83256> in train(epoch, scheduler)
     48         top5 = accuracy(outputs, targets, topk=(1, 5))
     49 
---> 50         loss.backward()
     51         optimizer.step()
     52         scheduler.step(epoch +batch_idx/iters)

~\Anaconda3\envs\1DCNN\lib\site-packages\torch\tensor.py in backward(self, gradient, retain_graph, create_graph)
    219                 retain_graph=retain_graph,
    220                 create_graph=create_graph)
--> 221         torch.autograd.backward(self, gradient, retain_graph, create_graph)
    222 
    223     def register_hook(self, hook):

~\Anaconda3\envs\1DCNN\lib\site-packages\torch\autograd\__init__.py in backward(tensors, grad_tensors, retain_graph, create_graph, grad_variables)
    130     Variable._execution_engine.run_backward(
    131         tensors, grad_tensors_, retain_graph, create_graph,
--> 132         allow_unreachable=True)  # allow_unreachable flag
    133 
    134 

RuntimeError: Expected isFloatingType(grad.scalar_type()) || (input_is_complex == grad_is_complex) to be true, but got false.  (Could this error message be improved?  If so, please report an enhancement request to PyTorch.)