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Update sd_models.py

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lllyasviel
2024-01-25 06:29:33 -08:00
parent 1034af36cc
commit 485e5ac1cc
1 changed files with 1 additions and 47 deletions
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48
modules/sd_models.py
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@@ -641,53 +641,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer):
""" pass
Checks if the desired checkpoint from checkpoint_info is not already loaded in model_data.loaded_sd_models.
If it is loaded, returns that (moving it to GPU if necessary, and moving the currently loadded model to CPU if necessary).
If not, returns the model that can be used to load weights from checkpoint_info's file.
If no such model exists, returns None.
Additionaly deletes loaded models that are over the limit set in settings (sd_checkpoints_limit).
"""
already_loaded = None
for i in reversed(range(len(model_data.loaded_sd_models))):
loaded_model = model_data.loaded_sd_models[i]
if loaded_model.sd_checkpoint_info.filename == checkpoint_info.filename:
already_loaded = loaded_model
continue
if len(model_data.loaded_sd_models) > shared.opts.sd_checkpoints_limit > 0:
print(f"Unloading model {len(model_data.loaded_sd_models)} over the limit of {shared.opts.sd_checkpoints_limit}: {loaded_model.sd_checkpoint_info.title}")
model_data.loaded_sd_models.pop()
if already_loaded is not None:
model_data.set_sd_model(already_loaded, already_loaded=True)
if not SkipWritingToConfig.skip:
shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title
shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256
print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}")
sd_vae.reload_vae_weights(already_loaded)
return model_data.sd_model
elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit:
print(f"Loading model {checkpoint_info.title} ({len(model_data.loaded_sd_models) + 1} out of {shared.opts.sd_checkpoints_limit})")
model_data.sd_model = None
load_model(checkpoint_info)
return model_data.sd_model
elif len(model_data.loaded_sd_models) > 0:
sd_model = model_data.loaded_sd_models.pop()
model_data.sd_model = sd_model
sd_vae.base_vae = getattr(sd_model, "base_vae", None)
sd_vae.loaded_vae_file = getattr(sd_model, "loaded_vae_file", None)
sd_vae.checkpoint_info = sd_model.sd_checkpoint_info
print(f"Reusing loaded model {sd_model.sd_checkpoint_info.title} to load {checkpoint_info.title}")
return sd_model
else:
return None
def reload_model_weights(sd_model=None, info=None, forced_reload=False): def reload_model_weights(sd_model=None, info=None, forced_reload=False):