2d.py with SDXL

[ThibaultGROUEIX]

Hi !

I am interested in your implementation of SDS with SDXL, and i would like to see the results on pixel optimization.
I was trying to run 2d.py but I ran into this error :

   scaler.scale(loss).backward()
  File "xxx/lib/python3.8/site-packages/torch/_tensor.py", line 522, in backward
    torch.autograd.backward(
  File xxx/lib/python3.8/site-packages/torch/autograd/__init__.py", line 266, in backward
    Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
RuntimeError: Trying to create tensor with negative dimension -17146298352: [-17146298352]

Does this experiment run on your side with SDXL or SDXL-turbo?
Thank you very much,
Thibault

[mdarhdarz]

Thank you for your attention.
Yes, 'assets/pgc.png' and 'assets/nopgc.png' are obtained through running 2d.py with SDXL-0.9. In this released version, some new arguments should be added to 'opt' in 2d.py but it seems you have fixed this.
For the negative dimension error, I have not met this. Could you provide more information for reproducing this error?
Here is my environment:
One 48G NVIDIA RTX A6000, 32G used to run 2d.py
Ubuntu 20, CUDA 11.7

[ivanpuhachov]

Hi, I can confirm that this issue is version related.
2d.py with SDXL raises RuntimeError: Trying to create tensor with negative dimension -17146298352: [-17146298352] with CUDA 12.2 and PyTorch 2.1
Runs OK if I use CUDA 11.7 and PyTorch 1.13 as recommended. I also fixed some arguments-related errors, can do a pull request.

256x256 image optimizations take 24GB of gpu memory (fits into 3090).

@mdarhdarz could you share arguments for 2d.py to reproduce assets/pgc.py?
upd: 1000 iterations with SDXL takes approx 15 minutes, is it expected?