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Thanks for providing this repository. It appears there is an issue with the model that is being caught by a version of PyTorch that is newer. I am happy to downgrade if that will fix it, but since the requirements doesn't list versions I do not know which version would work.
I've included the entire traceback here, including the torch.autograd.set_detect_anomaly(True) output, which points to line 60 in "models.py":
[W python_anomaly_mode.cpp:104] Warning: Error detected in CudnnConvolutionBackward. Traceback of forward call that caused the error:
File "main_train.py", line 29, in <module>
train(opt, Gs, Zs, reals, NoiseAmp)
File "./SinGAN/training.py", line 39, in train
z_curr,in_s,G_curr = train_single_scale(D_curr,G_curr,reals,Gs,Zs,in_s,NoiseAmp,opt)
File "./SinGAN/training.py", line 156, in train_single_scale
fake = netG(noise.detach(),prev)
File "python3.6/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "./SinGAN/models.py", line 60, in forward
x = self.tail(x)
File "python3.6/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "python3.6/site-packages/torch/nn/modules/container.py", line 119, in forward
input = module(input)
File "python3.6/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "python3.6/site-packages/torch/nn/modules/conv.py", line 399, in forward
return self._conv_forward(input, self.weight, self.bias)
File "python3.6/site-packages/torch/nn/modules/conv.py", line 396, in _conv_forward
self.padding, self.dilation, self.groups)
(function _print_stack)
Traceback (most recent call last):
File "main_train.py", line 29, in <module>
train(opt, Gs, Zs, reals, NoiseAmp)
File "./SinGAN/training.py", line 39, in train
z_curr,in_s,G_curr = train_single_scale(D_curr,G_curr,reals,Gs,Zs,in_s,NoiseAmp,opt)
File "./SinGAN/training.py", line 179, in train_single_scale
errG.backward(retain_graph=True)
File "python3.6/site-packages/torch/tensor.py", line 245, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "python3.6/site-packages/torch/autograd/__init__.py", line 147, in backward
allow_unreachable=True, accumulate_grad=True) # allow_unreachable flag
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [3, 32, 3, 3]] is at version 2; expected version 1 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!
The text was updated successfully, but these errors were encountered:
I had the same issue. Installing pytorch 1.4 solved it, but I would reccomend installing 0.5.0 torchvision at the same time, overwise it still won't work. conda install pytorch==1.4.0 torchvision==0.5.0 -c pytorch
Hello,
Thanks for providing this repository. It appears there is an issue with the model that is being caught by a version of PyTorch that is newer. I am happy to downgrade if that will fix it, but since the requirements doesn't list versions I do not know which version would work.
I've included the entire traceback here, including the
torch.autograd.set_detect_anomaly(True)
output, which points to line 60 in "models.py":The text was updated successfully, but these errors were encountered: