From 942553a504981be23caefbdde7d730cd2d9721b5 Mon Sep 17 00:00:00 2001 From: Vladimir Mandic Date: Sun, 16 Mar 2025 18:46:26 -0400 Subject: [PATCH] rename vae and unet none to default Signed-off-by: Vladimir Mandic --- CHANGELOG.md | 2 +- modules/model_flux.py | 12 ++++++------ modules/model_sd3.py | 8 ++++---- modules/model_stablecascade.py | 4 ++-- modules/processing_info.py | 4 ++-- modules/sd_models.py | 2 +- modules/sd_unet.py | 2 +- modules/shared.py | 4 ++-- 8 files changed, 19 insertions(+), 19 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 3f8557e8d..c659343df 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -37,7 +37,7 @@ - add quantization support to **CogView-3Plus** - update `diffusers` and other requirements - remote vae use `scaling_factor` and `shift_factor` - - rename vae *None* to *Default* to avoid confusion + - rename vae, unet and text-encoder settings *None* to *Default* to avoid confusion - **Fixes** - fix installer not starting when older version of `rich` is installed - fix circular imports when debug flags are enabled diff --git a/modules/model_flux.py b/modules/model_flux.py index 8e102afeb..79d81d031 100644 --- a/modules/model_flux.py +++ b/modules/model_flux.py @@ -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:') diff --git a/modules/model_sd3.py b/modules/model_sd3.py index 962a6d6db..baf936c1a 100644 --- a/modules/model_sd3.py +++ b/modules/model_sd3.py @@ -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 diff --git a/modules/model_stablecascade.py b/modules/model_stablecascade.py index 3c3339dca..0c767d33b 100644 --- a/modules/model_stablecascade.py +++ b/modules/model_stablecascade.py @@ -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) diff --git a/modules/processing_info.py b/modules/processing_info.py index fa084a2fb..5677a538c 100644 --- a/modules/processing_info.py +++ b/modules/processing_info.py @@ -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 diff --git a/modules/sd_models.py b/modules/sd_models.py index 0d662f9df..8c4356793 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -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)] diff --git a/modules/sd_unet.py b/modules/sd_unet.py index deb0b24b0..cfba470a1 100644 --- a/modules/sd_unet.py +++ b/modules/sd_unet.py @@ -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}') diff --git a/modules/shared.py b/modules/shared.py index ed3ef031d..4328eb787 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -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("

Model Offloading

", "", 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}),