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major refactoring of modules

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-07-03 09:18:38 -04:00
parent 772a5c9ad3
commit c4d9338d2e
214 changed files with 1154 additions and 1153 deletions
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modules/sd_models.py
+21 -21
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@@ -306,7 +306,7 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op='
shared.sd_model = None
try:
if model_type in ['Stable Cascade']: # forced pipeline
from modules.model_stablecascade import load_cascade_combined
from pipelines.model_stablecascade import load_cascade_combined
sd_model = load_cascade_combined(checkpoint_info, diffusers_load_config)
allow_post_quant = True
elif model_type in ['InstaFlow']: # forced pipeline
@@ -315,77 +315,77 @@ def load_diffuser_force(model_type, checkpoint_info, diffusers_load_config, op='
sd_model = pipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
allow_post_quant = True
elif model_type in ['SegMoE']: # forced pipeline
from modules.segmoe.segmoe_model import SegMoEPipeline
from pipelines.segmoe.segmoe_model import SegMoEPipeline
sd_model = SegMoEPipeline(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model = sd_model.pipe # segmoe pipe does its stuff in __init__ and __call__ is the original pipeline
allow_post_quant = True
shared_items.pipelines['SegMoE'] = SegMoEPipeline
elif model_type in ['PixArt Sigma']: # forced pipeline
from modules.model_pixart import load_pixart
from pipelines.model_pixart import load_pixart
sd_model = load_pixart(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Sana']: # forced pipeline
from modules.model_sana import load_sana
from pipelines.model_sana import load_sana
sd_model = load_sana(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Lumina-Next']: # forced pipeline
from modules.model_lumina import load_lumina
from pipelines.model_lumina import load_lumina
sd_model = load_lumina(checkpoint_info, diffusers_load_config)
allow_post_quant = True
elif model_type in ['Kolors']: # forced pipeline
from modules.model_kolors import load_kolors
from pipelines.model_kolors import load_kolors
sd_model = load_kolors(checkpoint_info, diffusers_load_config)
allow_post_quant = True
elif model_type in ['AuraFlow']: # forced pipeline
from modules.model_auraflow import load_auraflow
from pipelines.model_auraflow import load_auraflow
sd_model = load_auraflow(checkpoint_info, diffusers_load_config)
allow_post_quant = True
elif model_type in ['FLUX']:
from modules.model_flux import load_flux
from pipelines.model_flux import load_flux
sd_model = load_flux(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['FLEX']:
from modules.model_flex import load_flex
from pipelines.model_flex import load_flex
sd_model = load_flex(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Chroma']:
from modules.model_chroma import load_chroma
from pipelines.model_chroma import load_chroma
sd_model = load_chroma(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Lumina 2']:
from modules.model_lumina import load_lumina2
from pipelines.model_lumina import load_lumina2
sd_model = load_lumina2(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Stable Diffusion 3']:
from modules.model_sd3 import load_sd3
from pipelines.model_sd3 import load_sd3
sd_model = load_sd3(checkpoint_info, cache_dir=shared.opts.diffusers_dir, config=diffusers_load_config.get('config', None))
allow_post_quant = False
elif model_type in ['CogView 3']: # forced pipeline
from modules.model_cogview import load_cogview3
from pipelines.model_cogview import load_cogview3
sd_model = load_cogview3(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['CogView 4']: # forced pipeline
from modules.model_cogview import load_cogview4
from pipelines.model_cogview import load_cogview4
sd_model = load_cogview4(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Meissonic']: # forced pipeline
from modules.model_meissonic import load_meissonic
from pipelines.model_meissonic import load_meissonic
sd_model = load_meissonic(checkpoint_info, diffusers_load_config)
allow_post_quant = True
elif model_type in ['OmniGen2']: # forced pipeline
from modules.model_omnigen2 import load_omnigen2
from pipelines.model_omnigen2 import load_omnigen2
sd_model = load_omnigen2(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['OmniGen']: # forced pipeline
from modules.model_omnigen import load_omnigen
from pipelines.model_omnigen import load_omnigen
sd_model = load_omnigen(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['HiDream']:
from modules.model_hidream import load_hidream
from pipelines.model_hidream import load_hidream
sd_model = load_hidream(checkpoint_info, diffusers_load_config)
allow_post_quant = False
elif model_type in ['Cosmos']:
from modules.model_cosmos import load_cosmos_t2i
from pipelines.model_cosmos import load_cosmos_t2i
sd_model = load_cosmos_t2i(checkpoint_info, diffusers_load_config)
allow_post_quant = False
except Exception as e:
@@ -480,7 +480,7 @@ def load_diffuser_file(model_type, pipeline, checkpoint_info, diffusers_load_con
shared.log.debug(f'Load {op}: config="{model_config}"')
diffusers_load_config['config'] = model_config
if model_type.startswith('Stable Diffusion 3'):
from modules.model_sd3 import load_sd3
from pipelines.model_sd3 import load_sd3
sd_model = load_sd3(checkpoint_info=checkpoint_info, cache_dir=shared.opts.diffusers_dir, config=diffusers_load_config.get('config', None))
elif hasattr(pipeline, 'from_single_file'):
diffusers.loaders.single_file_utils.CHECKPOINT_KEY_NAMES["clip"] = "cond_stage_model.transformer.text_model.embeddings.position_embedding.weight" # patch for diffusers==0.28.0
@@ -1069,7 +1069,7 @@ def reload_model_weights(sd_model=None, info=None, reuse_dict=False, op='model',
unload_model_weights(op=op)
sd_model = None
timer = Timer()
# TODO model loader: implement model in-memory caching
# TODO model load: implement model in-memory caching
state_dict = get_checkpoint_state_dict(checkpoint_info, timer) if not shared.native else None
checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
timer.record("config")