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rename vae and unet none to default

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2025-03-16 18:46:26 -04:00
parent ed602b173d
commit 942553a504
8 changed files with 19 additions and 19 deletions
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modules/model_flux.py
+6 -6
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@@ -216,7 +216,7 @@ def load_transformer(file_path): # triggered by opts.sd_unet change
transformer = diffusers.FluxTransformer2DModel.from_single_file(file_path, **diffusers_load_config)
if transformer is None:
shared.log.error('Failed to load UNet model')
shared.opts.sd_unet = 'None'
shared.opts.sd_unet = 'Default'
return transformer
@@ -238,20 +238,20 @@ def load_flux(checkpoint_info, diffusers_load_config): # triggered by opts.sd_ch
devices.torch_gc(force=True)
# load overrides if any
if shared.opts.sd_unet != 'None':
if shared.opts.sd_unet != 'Default':
try:
debug(f'Load model: type=FLUX unet="{shared.opts.sd_unet}"')
transformer = load_transformer(sd_unet.unet_dict[shared.opts.sd_unet])
if transformer is None:
shared.opts.sd_unet = 'None'
shared.opts.sd_unet = 'Default'
sd_unet.failed_unet.append(shared.opts.sd_unet)
except Exception as e:
shared.log.error(f"Load model: type=FLUX failed to load UNet: {e}")
shared.opts.sd_unet = 'None'
shared.opts.sd_unet = 'Default'
if debug:
from modules import errors
errors.display(e, 'FLUX UNet:')
if shared.opts.sd_text_encoder != 'None':
if shared.opts.sd_text_encoder != 'Default':
try:
debug(f'Load model: type=FLUX te="{shared.opts.sd_text_encoder}"')
from modules.model_te import load_t5, load_vit_l
@@ -261,7 +261,7 @@ def load_flux(checkpoint_info, diffusers_load_config): # triggered by opts.sd_ch
text_encoder_2 = load_t5(name=shared.opts.sd_text_encoder, cache_dir=shared.opts.diffusers_dir)
except Exception as e:
shared.log.error(f"Load model: type=FLUX failed to load T5: {e}")
shared.opts.sd_text_encoder = 'None'
shared.opts.sd_text_encoder = 'Default'
if debug:
from modules import errors
errors.display(e, 'FLUX T5:')
modules/model_sd3.py
+4 -4
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@@ -5,7 +5,7 @@ from modules import shared, devices, sd_models, sd_unet, model_quant, model_tool
def load_overrides(kwargs, cache_dir):
if shared.opts.sd_unet != 'None':
if shared.opts.sd_unet != 'Default':
try:
fn = sd_unet.unet_dict[shared.opts.sd_unet]
if fn.endswith('.safetensors'):
@@ -20,9 +20,9 @@ def load_overrides(kwargs, cache_dir):
shared.log.debug(f'Load model: type=SD3 unet="{shared.opts.sd_unet}" fmt=gguf')
except Exception as e:
shared.log.error(f"Load model: type=SD3 failed to load UNet: {e}")
shared.opts.sd_unet = 'None'
shared.opts.sd_unet = 'Default'
sd_unet.failed_unet.append(shared.opts.sd_unet)
if shared.opts.sd_text_encoder != 'None':
if shared.opts.sd_text_encoder != 'Default':
try:
from modules.model_te import load_t5, load_vit_l, load_vit_g
if 'vit-l' in shared.opts.sd_text_encoder.lower():
@@ -36,7 +36,7 @@ def load_overrides(kwargs, cache_dir):
shared.log.debug(f'Load model: type=SD3 variant="t5" te="{shared.opts.sd_text_encoder}"')
except Exception as e:
shared.log.error(f"Load model: type=SD3 failed to load T5: {e}")
shared.opts.sd_text_encoder = 'None'
shared.opts.sd_text_encoder = 'Default'
if shared.opts.sd_vae != 'Default' and shared.opts.sd_vae != 'Automatic':
try:
from modules import sd_vae
modules/model_stablecascade.py
+2 -2
View File
@@ -93,7 +93,7 @@ def load_cascade_combined(checkpoint_info, diffusers_load_config):
if 'cascade' in checkpoint_info.name.lower():
diffusers_load_config["variant"] = 'bf16'
if shared.opts.sd_unet != "None" or 'stabilityai' in checkpoint_info.name.lower():
if shared.opts.sd_unet != "Default" or 'stabilityai' in checkpoint_info.name.lower():
if 'cascade' in checkpoint_info.name and ('lite' in checkpoint_info.name or (checkpoint_info.hash is not None and 'abc818bb0d' in checkpoint_info.hash)):
decoder_folder = 'decoder_lite'
prior_folder = 'prior_lite'
@@ -107,7 +107,7 @@ def load_cascade_combined(checkpoint_info, diffusers_load_config):
decoder = StableCascadeDecoderPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, text_encoder=None, **diffusers_load_config)
# shared.log.debug(f'StableCascade {decoder_folder}: scale={decoder.latent_dim_scale}')
prior_text_encoder = None
if shared.opts.sd_unet != "None":
if shared.opts.sd_unet != "Default":
prior_unet, prior_text_encoder = load_prior(unet_dict[shared.opts.sd_unet])
else:
prior_unet = StableCascadeUNet.from_pretrained("stabilityai/stable-cascade-prior", subfolder=prior_folder, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
modules/processing_info.py
+2 -2
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@@ -87,8 +87,8 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
args['Grid'] = grid
if shared.native:
args['Pipeline'] = shared.sd_model.__class__.__name__
args['TE'] = None if (not shared.opts.add_model_name_to_info or shared.opts.sd_text_encoder is None or shared.opts.sd_text_encoder == 'None') else shared.opts.sd_text_encoder
args['UNet'] = None if (not shared.opts.add_model_name_to_info or shared.opts.sd_unet is None or shared.opts.sd_unet == 'None') else shared.opts.sd_unet
args['TE'] = None if (not shared.opts.add_model_name_to_info or shared.opts.sd_text_encoder is None or shared.opts.sd_text_encoder == 'Default') else shared.opts.sd_text_encoder
args['UNet'] = None if (not shared.opts.add_model_name_to_info or shared.opts.sd_unet is None or shared.opts.sd_unet == 'Default') else shared.opts.sd_unet
if 'txt2img' in p.ops:
args["Variation seed"] = all_subseeds[index] if p.subseed_strength > 0 else None
args["Variation strength"] = p.subseed_strength if p.subseed_strength > 0 else None
modules/sd_models.py
+1 -1
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@@ -948,7 +948,7 @@ def get_native(pipe: diffusers.DiffusionPipeline):
def reload_text_encoder(initial=False):
if initial and (shared.opts.sd_text_encoder is None or shared.opts.sd_text_encoder == 'None'):
if initial and (shared.opts.sd_text_encoder is None or shared.opts.sd_text_encoder == 'Default'):
return # dont unload
signature = get_signature(shared.sd_model)
t5 = [k for k, v in signature.items() if 'T5EncoderModel' in str(v)]
modules/sd_unet.py
+1 -1
View File
@@ -10,7 +10,7 @@ debug = os.environ.get('SD_LOAD_DEBUG', None) is not None
def load_unet(model):
global loaded_unet # pylint: disable=global-statement
if shared.opts.sd_unet == 'None':
if shared.opts.sd_unet == 'Default':
return
if shared.opts.sd_unet not in list(unet_dict):
shared.log.error(f'UNet model not found: {shared.opts.sd_unet}')
modules/shared.py
+2 -2
View File
@@ -389,7 +389,7 @@ options_templates.update(options_section(('sd', "Models & Loading"), {
"diffusers_pipeline": OptionInfo('Autodetect', 'Model pipeline', gr.Dropdown, lambda: {"choices": list(shared_items.get_pipelines()), "visible": native}),
"sd_model_checkpoint": OptionInfo(default_checkpoint, "Base model", DropdownEditable, lambda: {"choices": list_checkpoint_titles()}, refresh=refresh_checkpoints),
"sd_model_refiner": OptionInfo('None', "Refiner model", gr.Dropdown, lambda: {"choices": ['None'] + list_checkpoint_titles()}, refresh=refresh_checkpoints),
"sd_unet": OptionInfo("None", "UNET model", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list),
"sd_unet": OptionInfo("Default", "UNET model", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list),
"latent_history": OptionInfo(16, "Latent history size", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
"offload_sep": OptionInfo("<h2>Model Offloading</h2>", "", gr.HTML),
@@ -429,7 +429,7 @@ options_templates.update(options_section(('vae_encoder', "Variable Auto Encoder"
}))
options_templates.update(options_section(('text_encoder', "Text Encoder"), {
"sd_text_encoder": OptionInfo('None', "Text encoder model", gr.Dropdown, lambda: {"choices": shared_items.sd_te_items()}, refresh=shared_items.refresh_te_list),
"sd_text_encoder": OptionInfo('Default', "Text encoder model", gr.Dropdown, lambda: {"choices": shared_items.sd_te_items()}, refresh=shared_items.refresh_te_list),
"prompt_attention": OptionInfo("native", "Prompt attention parser", gr.Radio, {"choices": ["native", "compel", "xhinker", "a1111", "fixed"] }),
"prompt_mean_norm": OptionInfo(False, "Prompt attention normalization", gr.Checkbox),
"sd_textencoder_cache": OptionInfo(True, "Cache text encoder results", gr.Checkbox, {"visible": False}),