Closed
Description
Describe the bug
diffusers DDIM gives worst results than Deforum DDIM when using small inference steps of size 8.
My understanding is that ddim is a very fast sampler, and
should yield a decent result even at a low step size like 8 or 16.
it's possible that I didn't set up the scheduler correctly. So, I've included the code below.
as for the deforum code you could try it on colab: https://colab.research.google.com/github/deforum/stable-diffusion/blob/main/Deforum_Stable_Diffusion.ipynb
Also, I've tried it with both CPU and GPU. it yields the same results.
Reproduction
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
# make sure you're logged in with `huggingface-cli login`
from torch import autocast
from diffusers import StableDiffusionPipeline
from diffusers import DDIMScheduler
steps = 8
ddim = DDIMScheduler()
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=True)
pipe = pipe.to("cpu")
prompt = "a photograph of an astronaut riding a horse"
# with autocast("cuda"):
# image = pipe(prompt).images[0]
image = pipe(prompt,num_inference_steps=steps,scheduler=ddim).images[0]
image.save("output/output_{0}.png".format(1))
diffusers image outputs with scheduler set to ddim and steps = 8 :
Deforum with DDIM scheduler with steps = 8 :
Logs
No response
System Info
diffusers
version: 0.4.0.dev0- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.8.3
- PyTorch version (GPU?): 1.12.1 (False)
- Huggingface_hub version: 0.9.1
- Transformers version: 4.21.2
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No