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