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https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
controlnet load lock
Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
@@ -1,5 +1,6 @@
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import os
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import time
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import threading
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from typing import Union
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from diffusers import StableDiffusionPipeline, StableDiffusionXLPipeline, FluxPipeline, StableDiffusion3Pipeline, ControlNetModel
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from modules.control.units import detect
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@@ -116,6 +117,7 @@ all_models.update(predefined_sdxl)
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all_models.update(predefined_f1)
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all_models.update(predefined_sd3)
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cache_dir = 'models/control/controlnet'
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load_lock = threading.Lock()
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def find_models():
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@@ -236,73 +238,74 @@ class ControlNet():
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self.model = cls.from_single_file(model_path, config=config, **self.load_config)
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def load(self, model_id: str = None, force: bool = True) -> str:
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try:
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t0 = time.time()
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model_id = model_id or self.model_id
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if model_id is None or model_id == 'None':
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self.reset()
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return
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if model_id not in all_models:
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log.error(f'Control {what} unknown model: id="{model_id}" available={list(all_models)}')
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return
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model_path = all_models[model_id]
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if model_path == '':
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return
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if model_path is None:
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log.error(f'Control {what} model load failed: id="{model_id}" error=unknown model id')
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return
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if 'lora' in model_id.lower():
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self.model = model_path
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return
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if model_id == self.model_id and not force:
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# log.debug(f'Control {what} model: id="{model_id}" path="{model_path}" already loaded')
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return
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log.debug(f'Control {what} model loading: id="{model_id}" path="{model_path}"')
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cls, _config = self.get_class(model_id)
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if model_path.endswith('.safetensors'):
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self.load_safetensors(model_id, model_path)
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else:
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kwargs = {}
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if '/bin' in model_path:
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model_path = model_path.replace('/bin', '')
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self.load_config['use_safetensors'] = False
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if cls is None:
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log.error(f'Control {what} model load failed: id="{model_id}" unknown base model')
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with load_lock:
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try:
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t0 = time.time()
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model_id = model_id or self.model_id
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if model_id is None or model_id == 'None':
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self.reset()
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return
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if variants.get(model_id, None) is not None:
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kwargs['variant'] = variants[model_id]
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self.model = cls.from_pretrained(model_path, **self.load_config, **kwargs)
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if self.model is None:
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return
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if self.dtype is not None:
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self.model.to(self.dtype)
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if "ControlNet" in opts.nncf_compress_weights:
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try:
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log.debug(f'Control {what} model NNCF Compress: id="{model_id}"')
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from installer import install
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install('nncf==2.7.0', quiet=True)
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from modules.sd_models_compile import nncf_compress_model
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self.model = nncf_compress_model(self.model)
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except Exception as e:
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log.error(f'Control {what} model NNCF Compression failed: id="{model_id}" error={e}')
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elif "ControlNet" in opts.optimum_quanto_weights:
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try:
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log.debug(f'Control {what} model Optimum Quanto: id="{model_id}"')
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model_quant.load_quanto('Load model: type=ControlNet')
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from modules.sd_models_compile import optimum_quanto_model
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self.model = optimum_quanto_model(self.model)
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except Exception as e:
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log.error(f'Control {what} model Optimum Quanto failed: id="{model_id}" error={e}')
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if self.device is not None:
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self.model.to(self.device)
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t1 = time.time()
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self.model_id = model_id
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log.debug(f'Control {what} model loaded: id="{model_id}" path="{model_path}" cls={cls.__name__} time={t1-t0:.2f}')
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return f'{what} loaded model: {model_id}'
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except Exception as e:
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log.error(f'Control {what} model load failed: id="{model_id}" error={e}')
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errors.display(e, f'Control {what} load')
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return f'{what} failed to load model: {model_id}'
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if model_id not in all_models:
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log.error(f'Control {what} unknown model: id="{model_id}" available={list(all_models)}')
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return
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model_path = all_models[model_id]
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if model_path == '':
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return
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if model_path is None:
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log.error(f'Control {what} model load failed: id="{model_id}" error=unknown model id')
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return
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if 'lora' in model_id.lower():
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self.model = model_path
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return
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if model_id == self.model_id and not force:
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# log.debug(f'Control {what} model: id="{model_id}" path="{model_path}" already loaded')
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return
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log.debug(f'Control {what} model loading: id="{model_id}" path="{model_path}"')
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cls, _config = self.get_class(model_id)
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if model_path.endswith('.safetensors'):
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self.load_safetensors(model_id, model_path)
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else:
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kwargs = {}
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if '/bin' in model_path:
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model_path = model_path.replace('/bin', '')
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self.load_config['use_safetensors'] = False
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if cls is None:
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log.error(f'Control {what} model load failed: id="{model_id}" unknown base model')
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return
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if variants.get(model_id, None) is not None:
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kwargs['variant'] = variants[model_id]
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self.model = cls.from_pretrained(model_path, **self.load_config, **kwargs)
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if self.model is None:
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return
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if self.dtype is not None:
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self.model.to(self.dtype)
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if "ControlNet" in opts.nncf_compress_weights:
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try:
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log.debug(f'Control {what} model NNCF Compress: id="{model_id}"')
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from installer import install
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install('nncf==2.7.0', quiet=True)
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from modules.sd_models_compile import nncf_compress_model
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self.model = nncf_compress_model(self.model)
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except Exception as e:
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log.error(f'Control {what} model NNCF Compression failed: id="{model_id}" error={e}')
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elif "ControlNet" in opts.optimum_quanto_weights:
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try:
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log.debug(f'Control {what} model Optimum Quanto: id="{model_id}"')
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model_quant.load_quanto('Load model: type=ControlNet')
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from modules.sd_models_compile import optimum_quanto_model
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self.model = optimum_quanto_model(self.model)
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except Exception as e:
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log.error(f'Control {what} model Optimum Quanto failed: id="{model_id}" error={e}')
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if self.device is not None:
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self.model.to(self.device)
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t1 = time.time()
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self.model_id = model_id
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log.info(f'Control {what} model loaded: id="{model_id}" path="{model_path}" cls={cls.__name__} time={t1-t0:.2f}')
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return f'{what} loaded model: {model_id}'
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except Exception as e:
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log.error(f'Control {what} model load failed: id="{model_id}" error={e}')
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errors.display(e, f'Control {what} load')
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return f'{what} failed to load model: {model_id}'
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class ControlNetPipeline():
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