Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

diffusers: upgrade to diffusers 0.10, add Heun scheduler

Browse Source
This commit is contained in:
Kevin Turner 2022-12-08 13:02:47 -08:00
parent 30a8d4c2b3
commit 9199d698f8
3 changed files with 10 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
binary_installer/requirements.in
View File

@ -4,7 +4,7 @@
--trusted-host https://download.pytorch.org --trusted-host https://download.pytorch.org
accelerate~=0.14 accelerate~=0.14
albumentations albumentations
diffusers[torch]~=0.9 diffusers[torch]~=0.10
einops einops
eventlet eventlet
flask_cors flask_cors

8
ldm/generate.py
View File

@ -17,6 +17,7 @@ import skimage
import torch import torch
import transformers import transformers
from PIL import Image, ImageOps from PIL import Image, ImageOps
from diffusers import HeunDiscreteScheduler
from diffusers.pipeline_utils import DiffusionPipeline from diffusers.pipeline_utils import DiffusionPipeline
from diffusers.schedulers.scheduling_ddim import DDIMScheduler from diffusers.schedulers.scheduling_ddim import DDIMScheduler
from diffusers.schedulers.scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler from diffusers.schedulers.scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
@ -1008,12 +1009,17 @@ class Generate:
scheduler_map = dict( scheduler_map = dict(
ddim=DDIMScheduler, ddim=DDIMScheduler,
dpmpp_2=DPMSolverMultistepScheduler,
ipndm=IPNDMScheduler, ipndm=IPNDMScheduler,
# DPMSolverMultistepScheduler is technically not `k_` anything, as it is neither
# the k-diffusers implementation nor included in EDM (Karras 2022), but we can
# provide an alias for compatibility.
k_dpmpp_2=DPMSolverMultistepScheduler,
k_euler=EulerDiscreteScheduler, k_euler=EulerDiscreteScheduler,
k_euler_a=EulerAncestralDiscreteScheduler, k_euler_a=EulerAncestralDiscreteScheduler,
k_heun=HeunDiscreteScheduler,
k_lms=LMSDiscreteScheduler, k_lms=LMSDiscreteScheduler,
plms=PNDMScheduler, plms=PNDMScheduler,
k_dpmpp_2=DPMSolverMultistepScheduler,
) )
if self.sampler_name in scheduler_map: if self.sampler_name in scheduler_map:

4
ldm/invoke/generator/diffusers_pipeline.py
View File

@ -407,7 +407,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
batch_size = initial_latents.size(0) batch_size = initial_latents.size(0)
img2img_pipeline = StableDiffusionImg2ImgPipeline(**self.components) img2img_pipeline = StableDiffusionImg2ImgPipeline(**self.components)
img2img_pipeline.scheduler.set_timesteps(num_inference_steps, device=device) img2img_pipeline.scheduler.set_timesteps(num_inference_steps, device=device)
timesteps = img2img_pipeline.get_timesteps(num_inference_steps, strength, device=device) timesteps, _ = img2img_pipeline.get_timesteps(num_inference_steps, strength, device=device)
latent_timestep = timesteps[:1].repeat(batch_size) latent_timestep = timesteps[:1].repeat(batch_size)
latents = self.noise_latents_for_time(initial_latents, latent_timestep, noise_func=noise_func) latents = self.noise_latents_for_time(initial_latents, latent_timestep, noise_func=noise_func)
@ -454,7 +454,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
img2img_pipeline = StableDiffusionImg2ImgPipeline(**self.components) img2img_pipeline = StableDiffusionImg2ImgPipeline(**self.components)
img2img_pipeline.scheduler.set_timesteps(num_inference_steps, device=device) img2img_pipeline.scheduler.set_timesteps(num_inference_steps, device=device)
timesteps = img2img_pipeline.get_timesteps(num_inference_steps, strength, device=device) timesteps, _ = img2img_pipeline.get_timesteps(num_inference_steps, strength, device=device)
assert img2img_pipeline.scheduler is self.scheduler assert img2img_pipeline.scheduler is self.scheduler