mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
Vladimir Mandic
67 lines
2.8 KiB
Python
67 lines
2.8 KiB
Python
import sys
|
|
import transformers
|
|
import diffusers
|
|
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_boogu(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, _ = model_quant.get_dit_args(diffusers_load_config, allow_quant=False)
|
|
log.debug(f'Load model: type=Boogu repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={load_args}')
|
|
|
|
from pipelines.boogu.pipeline_boogu import BooguImagePipeline
|
|
from pipelines.boogu.pipeline_boogu_turbo import BooguImageTurboPipeline
|
|
from pipelines.boogu.transformer_boogu import BooguImageTransformer2DModel
|
|
from pipelines.boogu import transformer_boogu, scheduling_flow_match_euler_discrete_time_shifting
|
|
sys.modules['transformer_boogu'] = transformer_boogu # for loading custom code from HF repo
|
|
sys.modules['scheduling_flow_match_euler_discrete_time_shifting'] = scheduling_flow_match_euler_discrete_time_shifting # for loading custom code from HF repo
|
|
generic.set_pipeline('Boogu', BooguImagePipeline)
|
|
|
|
if repo_id is None or repo_id.lower() == 'none':
|
|
return None
|
|
|
|
mllm = generic.load_text_encoder(repo_id, cls_name=transformers.Qwen3VLForConditionalGeneration, load_config=diffusers_load_config, subfolder='mllm')
|
|
transformer = generic.load_transformer(repo_id, cls_name=BooguImageTransformer2DModel, load_config=diffusers_load_config)
|
|
scheduler = scheduling_flow_match_euler_discrete_time_shifting.FlowMatchEulerDiscreteScheduler.from_pretrained(repo_id, subfolder='scheduler', cache_dir=shared.opts.diffusers_dir)
|
|
|
|
if 'turbo' in repo_id.lower():
|
|
cls = BooguImageTurboPipeline
|
|
else:
|
|
cls = BooguImagePipeline
|
|
|
|
diffusers.pipelines.auto_pipeline.AUTO_TEXT2IMAGE_PIPELINES_MAPPING['boogu'] = cls
|
|
diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING['boogu'] = cls
|
|
|
|
pipe = cls.from_pretrained(
|
|
repo_id,
|
|
transformer=transformer,
|
|
mllm=mllm,
|
|
scheduler=scheduler,
|
|
cache_dir=shared.opts.diffusers_dir,
|
|
**load_args,
|
|
)
|
|
scheduler.__class__.__name__ = 'BooguFlowMatchEulerScheduler' # its not same as normal euler
|
|
pipe.default_scheduler = scheduler
|
|
pipe.scheduler = scheduler
|
|
|
|
pipe.task_args = {
|
|
'output_type': 'np',
|
|
}
|
|
|
|
generic.load_vae_override(pipe, diffusers_load_config)
|
|
|
|
del transformer
|
|
del mllm
|
|
sd_hijack_te.init_hijack(pipe)
|
|
sd_hijack_vae.init_hijack(pipe)
|
|
|
|
devices.torch_gc(force=True, reason='load')
|
|
return pipe
|