Public/automatic
1
0
Fork 0
mirror of https://github.com/vladmandic/automatic synced 2026-09-18 16:54:33 +02:00
Code Issues Packages Projects Releases Wiki Activity

fix stable cascade

Browse Source
This commit is contained in:
Vladimir Mandic
2024-05-14 14:20:13 -04:00
parent 1ad27d4b25
commit f7fa2794df
2 changed files with 30 additions and 30 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/sd_models.py
+28 -24
View File
@@ -943,30 +943,34 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
diffusers_load_config['variant'] = 'fp16'
if model_type in ['Stable Cascade']: # forced pipeline
try: # this is horrible special-case handling for stable-cascade multi-stage pipeline with variants and non-standard revision
shared.opts.data['diffusers_model_cpu_offload'] = True # override
diffusers_load_config.pop("vae", None)
if 'stabilityai' in checkpoint_info.name:
diffusers_load_config["variant"] = 'bf16'
if 'stabilityai' in checkpoint_info.name and ('lite' in checkpoint_info.name or (checkpoint_info.hash is not None and 'abc818bb0d' in checkpoint_info.hash)):
decoder_unet = diffusers.models.StableCascadeUNet.from_pretrained("stabilityai/stable-cascade", subfolder="decoder_lite", cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
decoder = diffusers.StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", cache_dir=shared.opts.diffusers_dir, decoder=decoder_unet, **diffusers_load_config)
shared.log.debug(f'StableCascade lite decoder: scale={decoder.latent_dim_scale}')
prior_unet = diffusers.models.StableCascadeUNet.from_pretrained("stabilityai/stable-cascade-prior", subfolder="prior_lite", cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
prior = diffusers.StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", cache_dir=shared.opts.diffusers_dir, prior=prior_unet, **diffusers_load_config)
shared.log.debug(f'StableCascade lite prior: scale={prior.resolution_multiple}')
sd_model = diffusers.StableCascadeCombinedPipeline(
tokenizer=decoder.tokenizer,
text_encoder=decoder.text_encoder,
decoder=decoder.decoder,
scheduler=decoder.scheduler,
vqgan=decoder.vqgan,
prior_prior=prior.prior,
prior_text_encoder=prior.text_encoder,
prior_tokenizer=prior.tokenizer,
prior_scheduler=prior.scheduler,
prior_feature_extractor=prior.feature_extractor,
prior_image_encoder=prior.image_encoder)
decoder_folder = 'decoder_lite'
prior_folder = 'prior_lite'
else:
sd_model = diffusers.StableCascadeCombinedPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
decoder_folder = 'decoder'
prior_folder = 'prior'
decoder_unet = diffusers.models.StableCascadeUNet.from_pretrained("stabilityai/stable-cascade", subfolder=decoder_folder, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
decoder = diffusers.StableCascadeDecoderPipeline.from_pretrained("stabilityai/stable-cascade", cache_dir=shared.opts.diffusers_dir, decoder=decoder_unet, **diffusers_load_config)
shared.log.debug(f'StableCascade {decoder_folder}: scale={decoder.latent_dim_scale}')
prior_unet = diffusers.models.StableCascadeUNet.from_pretrained("stabilityai/stable-cascade-prior", subfolder=prior_folder, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
prior = diffusers.StableCascadePriorPipeline.from_pretrained("stabilityai/stable-cascade-prior", cache_dir=shared.opts.diffusers_dir, prior=prior_unet, **diffusers_load_config)
shared.log.debug(f'StableCascade {prior_folder}: scale={prior.resolution_multiple}')
sd_model = diffusers.StableCascadeCombinedPipeline(
tokenizer=decoder.tokenizer,
text_encoder=decoder.text_encoder,
decoder=decoder.decoder,
scheduler=decoder.scheduler,
vqgan=decoder.vqgan,
prior_prior=prior.prior,
prior_text_encoder=prior.text_encoder,
prior_tokenizer=prior.tokenizer,
prior_scheduler=prior.scheduler,
prior_feature_extractor=prior.feature_extractor,
prior_image_encoder=prior.image_encoder)
shared.log.debug(f'StableCascade combined: {sd_model.__class__.__name__}')
except Exception as e:
shared.log.error(f'Diffusers Failed loading {op}: {checkpoint_info.path} {e}')
@@ -994,15 +998,15 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
return
elif model_type in ['PixArt-Sigma']: # forced pipeline
try:
from modules.sd_hijack_pixart import PixArtSigmaPipeline, patch_pixart_sigma_transformer
# from modules.sd_hijack_pixart import PixArtSigmaPipeline, patch_pixart_sigma_transformer
shared.opts.data['cuda_dtype'] = 'FP32' # override
shared.opts.data['set_diffuser_options'] = True # override
shared.opts.data['diffusers_model_cpu_offload'] = True # override
devices.set_cuda_params()
sd_model = PixArtSigmaPipeline.from_pretrained(
sd_model = diffusers.PixArtSigmaPipeline.from_pretrained(
checkpoint_info.path,
transformer=patch_pixart_sigma_transformer(),
use_safetensors=True,
cache_dir=shared.opts.diffusers_dir,
# transformer=patch_pixart_sigma_transformer(),
**diffusers_load_config)
except Exception as e:
shared.log.error(f'Diffusers Failed loading {op}: {checkpoint_info.path} {e}')
@@ -1061,7 +1065,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
shared.log.error(f'Failed loading {op}: {checkpoint_info.path} auto={err1} diffusion={err2}')
return
elif os.path.isfile(checkpoint_info.path) and checkpoint_info.path.lower().endswith('.safetensors'):
diffusers_load_config["local_files_only"] = False # TODO avoid online check on model load
diffusers_load_config["local_files_only"] = diffusers_version < 28 # TODO avoid online check on model load
diffusers_load_config["extract_ema"] = shared.opts.diffusers_extract_ema
if pipeline is None:
shared.log.error(f'Diffusers {op} pipeline not initialized: {shared.opts.diffusers_pipeline}')
modules/shared_items.py
+2 -6
View File
@@ -62,8 +62,10 @@ def get_pipelines():
'Stable Diffusion XL Img2Img': getattr(diffusers, 'StableDiffusionXLImg2ImgPipeline', None),
'Stable Diffusion XL Inpaint': getattr(diffusers, 'StableDiffusionXLInpaintPipeline', None),
'Stable Diffusion XL Instruct': getattr(diffusers, 'StableDiffusionXLInstructPix2PixPipeline', None),
'Stable Cascade': getattr(diffusers, 'StableCascadeCombinedPipeline', None),
'Latent Consistency Model': getattr(diffusers, 'LatentConsistencyModelPipeline', None),
'PixArt-Alpha': getattr(diffusers, 'PixArtAlphaPipeline', None),
'PixArt-Sigma': getattr(diffusers, 'PixArtSigmaPipeline', None),
'UniDiffuser': getattr(diffusers, 'UniDiffuserPipeline', None),
'Wuerstchen': getattr(diffusers, 'WuerstchenCombinedPipeline', None),
'Kandinsky 2.1': getattr(diffusers, 'KandinskyPipeline', None),
@@ -85,12 +87,6 @@ def get_pipelines():
}
pipelines.update(onnx_pipelines)
if hasattr(diffusers, 'StableCascadeCombinedPipeline'):
pipelines['Stable Cascade'] = getattr(diffusers, 'StableCascadeCombinedPipeline', None)
from modules.sd_hijack_pixart import PixArtSigmaPipeline
pipelines['PixArt-Sigma'] = PixArtSigmaPipeline
for k, v in pipelines.items():
if k != 'Autodetect' and v is None:
log.error(f'Not available: pipeline={k} diffusers={diffusers.__version__} path={diffusers.__file__}')