Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Possible to run on a 1080 with 8GB? (memory error) #7

Open
powerspowers opened this issue Aug 25, 2019 · 1 comment
Open

Possible to run on a 1080 with 8GB? (memory error) #7

powerspowers opened this issue Aug 25, 2019 · 1 comment

Comments

@powerspowers
Copy link

I have a DELL XPS with an nVidia 1080 w 8GB. My hope was to run StyleGAN on this rather than needing to jump to the cloud. Possible?

I disable blur2d by commenting out the lines including it

Getting this error:

:\Users\Powerpop\Anaconda3\lib\site-packages\skimage\transform\_warps.py:110: UserWarning: Anti-aliasing will be enabled by default in skimage 0.15 to avoid aliasing artifacts when down-sampling images.
  warn("Anti-aliasing will be enabled by default in skimage 0.15 to "
Traceback (most recent call last):
  File "train_stylegan.py", line 164, in <module>
    main(opts)
  File "train_stylegan.py", line 98, in main
    real_logit = D(real_img)
  File "C:\Users\Powerpop\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 493, in __call__
    result = self.forward(*input, **kwargs)
  File "C:\Users\Powerpop\Desktop\StyleGAN\networks_stylegan.py", line 651, in forward
    x = F.leaky_relu(self.conv6(x), 0.2, inplace=True)
  File "C:\Users\Powerpop\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 493, in __call__
    result = self.forward(*input, **kwargs)
  File "C:\Users\Powerpop\Anaconda3\lib\site-packages\torch\nn\modules\conv.py", line 338, in forward
    self.padding, self.dilation, self.groups)
RuntimeError: CUDA out of memory. Tried to allocate 4.00 GiB (GPU 0; 8.00 GiB total capacity; 4.19 GiB already allocated; 2.06 GiB free; 8.04 MiB cached)
@XiaoqiangZhou
Copy link

@powerspowers I think you can reduce the batch size or remove some modules to lower the generated image resolution from 1024x1024 to 512 or 256.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants