I am researching RaLSGAN and encounter this RuntimeError “one of the variables needed for gradient computation has been modified by an inplace operation” when running on Colab.
Perhaps, this error relates to backward function but I can’t solve it. Please help me with this problem.
for epoch in range(epochs):
    
    for ii, real_images in tqdm(enumerate(train_loader), total=len(train_loader)):
        ############################
        # (1) Update D network
        ###########################
        netD.zero_grad()
        real_images = real_images.to(device)
        batch_size = real_images.size(0)
        labels = torch.full((batch_size, 1), real_label, device=device)
        outputR = netD(real_images)
        noise = torch.randn(batch_size, nz, 1, 1, device=device)
        fake = netG(noise)
        outputF = netD(fake.detach())
        errD = (torch.mean((outputR - torch.mean(outputF) - labels) ** 2) + 
                torch.mean((outputF - torch.mean(outputR) + labels) ** 2))/2
        errD.backward(retain_graph=True)
        optimizerD.step()
        ############################
        # (2) Update G network
        ###########################
        netG.zero_grad()
        outputF = netD(fake)   
        errG = (torch.mean((outputR - torch.mean(outputF) + labels) ** 2) +
                torch.mean((outputF - torch.mean(outputR) - labels) ** 2))/2
        errG.backward()
        optimizerG.step()
        
        if (ii+1) % (len(train_loader)//2) == 0:
            print('[%d/%d][%d/%d] Loss_D: %.4f Loss_G: %.4f'
                  % (epoch + 1, epochs, ii+1, len(train_loader),
                     errD.item(), errG.item()))

/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0
Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`
  This is separate from the ipykernel package so we can avoid doing imports until
0%
0/644 [00:00<?, ?it/s]
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-27-d298a2f96c50> in <module>()
     24         errG = (torch.mean((outputR - torch.mean(outputF) + labels) ** 2) +
     25                 torch.mean((outputF - torch.mean(outputR) - labels) ** 2))/2
---> 26         errG.backward()
     27         optimizerG.step()
     28 

1 frames
/usr/local/lib/python3.6/dist-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):

/usr/local/lib/python3.6/dist-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: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [1, 256, 4, 4]] is at version 2; expected version 1 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).