Files
automatic/pipelines/model_ultraflux.py
T
Vladimir Mandic 3859530214 refactor for consistent folders usage for all models
Signed-off-by: Vladimir Mandic <mandic00@live.com>
2026-06-08 08:24:21 +02:00

60 lines
2.4 KiB
Python

import diffusers
import transformers
from modules import shared, devices, sd_models, model_quant, sd_hijack_te, sd_hijack_vae
from modules.logger import log
from pipelines import generic
def load_ultraflux(checkpoint_info, diffusers_load_config=None):
if diffusers_load_config is None:
diffusers_load_config = {}
repo_id = sd_models.path_to_repo(checkpoint_info)
sd_models.hf_auth_check(checkpoint_info)
load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, allow_quant=False)
load_args.pop('cache_dir', None)
log.debug(f'Load model: type=UltraFlux repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
from pipelines.ultraflux.pipeline_flux import UltraFluxPipeline
from pipelines.ultraflux.transformer_flux import FluxTransformer2DModel
from pipelines.ultraflux.autoencoder_kl import AutoencoderUltraFluxKL
diffusers.pipelines.auto_pipeline.AUTO_TEXT2IMAGE_PIPELINES_MAPPING['ultraflux'] = UltraFluxPipeline
generic.set_pipeline('UltraFlux', UltraFluxPipeline)
transformer = generic.load_transformer(repo_id, cls_name=FluxTransformer2DModel, load_config=diffusers_load_config)
text_encoder_2 = generic.load_text_encoder(repo_id, cls_name=transformers.T5EncoderModel, load_config=diffusers_load_config, subfolder='text_encoder_2')
if repo_id is None or repo_id.lower() == 'none':
return None
vae = AutoencoderUltraFluxKL.from_pretrained(
repo_id,
subfolder='vae',
cache_dir=shared.opts.hfcache_dir,
torch_dtype=devices.dtype,
)
pipe = UltraFluxPipeline.from_pretrained(
repo_id,
transformer=transformer,
text_encoder_2=text_encoder_2,
vae=vae,
cache_dir=shared.opts.diffusers_dir,
**load_args,
)
pipe.task_args = {
'output_type': 'np',
}
if hasattr(pipe, 'scheduler') and hasattr(pipe.scheduler, 'config'):
if hasattr(pipe.scheduler.config, 'use_dynamic_shifting'):
pipe.scheduler.config.use_dynamic_shifting = False
if hasattr(pipe.scheduler.config, 'time_shift'):
pipe.scheduler.config.time_shift = 4
del text_encoder_2
del transformer
del vae
sd_hijack_te.init_hijack(pipe)
sd_hijack_vae.init_hijack(pipe)
devices.torch_gc(force=True, reason='load')
return pipe