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Support SDXL v-pred models

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This commit is contained in:
catboxanon
2024-10-19 06:53:19 -04:00
parent 48239090f1
commit 1ae073c052
3 changed files with 106 additions and 3 deletions
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7
modules/sd_models.py
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@@ -783,7 +783,7 @@ def get_obj_from_str(string, reload=False):
return getattr(importlib.import_module(module, package=None), cls)
def load_model(checkpoint_info=None, already_loaded_state_dict=None):
def load_model(checkpoint_info=None, already_loaded_state_dict=None, checkpoint_config=None):
from modules import sd_hijack
checkpoint_info = checkpoint_info or select_checkpoint()
@@ -801,7 +801,8 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None):
else:
state_dict = get_checkpoint_state_dict(checkpoint_info, timer)
checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
if not checkpoint_config:
checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
clip_is_included_into_sd = any(x for x in [sd1_clip_weight, sd2_clip_weight, sdxl_clip_weight, sdxl_refiner_clip_weight] if x in state_dict)
timer.record("find config")
@@ -974,7 +975,7 @@ def reload_model_weights(sd_model=None, info=None, forced_reload=False):
if sd_model is not None:
send_model_to_trash(sd_model)
load_model(checkpoint_info, already_loaded_state_dict=state_dict)
load_model(checkpoint_info, already_loaded_state_dict=state_dict, checkpoint_config=checkpoint_config)
return model_data.sd_model
try:

4
modules/sd_models_config.py
View File

@@ -14,6 +14,7 @@ config_sd2 = os.path.join(sd_repo_configs_path, "v2-inference.yaml")
config_sd2v = os.path.join(sd_repo_configs_path, "v2-inference-v.yaml")
config_sd2_inpainting = os.path.join(sd_repo_configs_path, "v2-inpainting-inference.yaml")
config_sdxl = os.path.join(sd_xl_repo_configs_path, "sd_xl_base.yaml")
config_sdxlv = os.path.join(sd_configs_path, "sd_xl_v.yaml")
config_sdxl_refiner = os.path.join(sd_xl_repo_configs_path, "sd_xl_refiner.yaml")
config_sdxl_inpainting = os.path.join(sd_configs_path, "sd_xl_inpaint.yaml")
config_depth_model = os.path.join(sd_repo_configs_path, "v2-midas-inference.yaml")
@@ -81,6 +82,9 @@ def guess_model_config_from_state_dict(sd, filename):
if diffusion_model_input.shape[1] == 9:
return config_sdxl_inpainting
else:
if ('v_pred' in sd):
del sd['v_pred']
return config_sdxlv
return config_sdxl
if sd.get('conditioner.embedders.0.model.ln_final.weight', None) is not None: