Open vibrantrida opened 2 years ago
Note that PyTorch's seed depend on:
Note that PyTorch's seed depend on:
- PyTorch version
- CUDA/CuDNN version
- Whether it's CPU or GPU
Thank you for this information, I made sure to use the exact same PyTorch and CUDA version this time and my local installation of stable diffusion produced an output that is close enough but not exactly the same output as the google colab.
PyTorch: 1.12.1+cu113
CUDA: 11.3
Prompt: kyoto animation beautiful detailed portrait cell shaded 4 k concept art by wlop ilya kuv kuvshinov greg rutkowski pixiv cinematic dramatic atmosphere sharp focus volumetric lighting cinematic lighting studio quality
Sampler: k_lms
Scale: 7
Steps: 30
Seed: 2494989938
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.32.03 Driver Version: 460.32.03 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 516.59 Driver Version: 516.59 CUDA Version: 11.7 |
|-------------------------------+----------------------+----------------------+
try keggle
try anyone of these https://datasciencenotebook.org/
try anyone of these https://datasciencenotebook.org/
I don't know what this have to do with the issue.
Hello, I have an old graphics card (see below) and I am using the exact same 1,4 model from huggingface but for some reason I am getting a different results for the same configuration.
Google Colab (same output on dreamstudio beta)
Jupyter Lab
I reported this issue to the author of the notebook I'm using and they said it is a known issue that seed is non-reproducible/not universal because of the way it is currently being generated. https://github.com/FuouM/HidamariDiffusionColab/issues/1
I am hoping that you have any idea how to deal with this as it stands right now any changes to this is guaranteed to make AND break everyone's seed.