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Implement Euler Ancestral Discrete scheduler #34
Implement Euler Ancestral Discrete scheduler #34
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implement euler ancestral discrete scheduler following HF implementation: https://github.com/huggingface/diffusers/blob/main/src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py
Hi @sssemil, |
Did you change the scheduler and the number of inference steps (some of those snippets have 1000)? I tried several times with that same snippet and the appropriate scheduler. Here are other examples I just produced I leave the exact snippet hereby, to make sure we're using the same one import torch
from diffusers import StableDiffusionPipeline, EulerAncestralDiscreteScheduler
pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
pipe.scheduler = EulerAncestralDiscreteScheduler()
pipe = pipe.to("cuda")
prompt = "A very rusty robot holding a fire torch."
image = pipe(prompt, num_inference_steps=21).images[0]
image |
Happy to help 👍 |
Merged, thanks for all the scheduler hard work! |
Thanks for merging! (maybe forgot to push after git merge?) |
Oh right sorry about that! |
Hi @LaurentMazare,
this PR aims at integrating the Euler Ancestral Discrete Scheduler into this repository, solving the second task mentioned in #23 .
It includes all the features implemented in HF's Python version.
All the considerations made in my last PR, regarding the need to generalize the examples, still apply here.