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mirror of https://github.com/vladmandic/automatic synced 2026-09-20 01:31:13 +02:00
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fix prompt parser for sdxl and enable offloading

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Vladimir Mandic
2023-08-10 21:20:56 +00:00
parent 5bcd65d4c2
commit f52249d5a8
9 changed files with 65 additions and 43 deletions
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modules/sd_models.py
+18 -7
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@@ -136,12 +136,9 @@ def list_models():
checkpoints_list.clear()
checkpoint_aliases.clear()
ext_filter=[".safetensors"] if shared.opts.sd_disable_ckpt else [".ckpt", ".safetensors"]
model_list = []
if shared.backend == shared.Backend.ORIGINAL or shared.opts.diffusers_allow_safetensors:
model_list += modelloader.load_models(model_path=model_path, model_url=None, command_path=shared.opts.ckpt_dir, ext_filter=ext_filter, download_name=None, ext_blacklist=[".vae.ckpt", ".vae.safetensors"])
model_list = modelloader.load_models(model_path=model_path, model_url=None, command_path=shared.opts.ckpt_dir, ext_filter=ext_filter, download_name=None, ext_blacklist=[".vae.ckpt", ".vae.safetensors"])
if shared.backend == shared.Backend.DIFFUSERS:
model_list += modelloader.load_diffusers_models(model_path=os.path.join(models_path, 'Diffusers'), command_path=shared.opts.diffusers_dir)
for filename in sorted(model_list, key=str.lower):
checkpoint_info = CheckpointInfo(filename)
if checkpoint_info.name is not None:
@@ -844,7 +841,6 @@ def set_diffuser_pipe(pipe, new_pipe_type):
new_pipe = diffusers.AutoPipelineForImage2Image.from_pipe(pipe)
elif new_pipe_type == DiffusersTaskType.INPAINTING:
new_pipe = diffusers.AutoPipelineForInpainting.from_pipe(pipe)
if pipe.__class__ == new_pipe.__class__:
return
@@ -1030,20 +1026,35 @@ def reload_model_weights(sd_model=None, info=None, reuse_dict=False, op='model')
shared.log.info(f"Weights loaded in {timer.summary()}")
def disable_offload(sd_model):
from accelerate.hooks import remove_hook_from_module
if not sd_model.has_accelerate:
return
for _name, model in sd_model.components.items():
if not isinstance(model, torch.nn.Module):
continue
remove_hook_from_module(model, recurse=True)
def unload_model_weights(op='model'):
from modules import sd_hijack
if op == 'model' or op == 'dict':
if model_data.sd_model:
model_data.sd_model.to(devices.cpu)
if shared.backend == shared.Backend.ORIGINAL:
model_data.sd_model.to(devices.cpu)
sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
else:
disable_offload(model_data.sd_model)
model_data.sd_model.to('meta')
model_data.sd_model = None
shared.log.debug(f'Unload weights {op}: {memory_stats()}')
else:
if model_data.sd_refiner:
model_data.sd_refiner.to(devices.cpu)
model_data.sd_refiner.to('meta')
if shared.backend == shared.Backend.ORIGINAL:
sd_hijack.model_hijack.undo_hijack(model_data.sd_refiner)
else:
disable_offload(model_data.sd_model)
model_data.sd_refiner = None
shared.log.debug(f'Unload weights {op}: {memory_stats()}')
devices.torch_gc(force=True)