From 0a89cd1a584b1584a0609c0ba27fb35c434b0b68 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 24 Jul 2023 22:08:08 +0300 Subject: Use less RAM when creating models --- modules/sd_models.py | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index fb31a793..acb1e817 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -460,7 +460,6 @@ def get_empty_cond(sd_model): return sd_model.cond_stage_model([""]) - def load_model(checkpoint_info=None, already_loaded_state_dict=None): from modules import lowvram, sd_hijack checkpoint_info = checkpoint_info or select_checkpoint() @@ -495,19 +494,24 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): sd_model = None try: with sd_disable_initialization.DisableInitialization(disable_clip=clip_is_included_into_sd or shared.cmd_opts.do_not_download_clip): - sd_model = instantiate_from_config(sd_config.model) - except Exception: - pass + with sd_disable_initialization.InitializeOnMeta(): + sd_model = instantiate_from_config(sd_config.model) + + except Exception as e: + errors.display(e, "creating model quickly", full_traceback=True) if sd_model is None: print('Failed to create model quickly; will retry using slow method.', file=sys.stderr) - sd_model = instantiate_from_config(sd_config.model) + + with sd_disable_initialization.InitializeOnMeta(): + sd_model = instantiate_from_config(sd_config.model) sd_model.used_config = checkpoint_config timer.record("create model") - load_model_weights(sd_model, checkpoint_info, state_dict, timer) + with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): + load_model_weights(sd_model, checkpoint_info, state_dict, timer) if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram) -- cgit v1.2.3 From 3bca90b249d749ed5429f76e380d2ffa52fc0d41 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 30 Jul 2023 13:48:27 +0300 Subject: hires fix checkpoint selection --- modules/generation_parameters_copypaste.py | 3 ++ modules/processing.py | 47 +++++++++++++++++++----------- modules/sd_models.py | 22 ++++++++------ modules/shared.py | 19 ++++++++---- modules/txt2img.py | 3 +- modules/ui.py | 8 ++++- 6 files changed, 68 insertions(+), 34 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a3448be9..4e286558 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -280,6 +280,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "Hires sampler" not in res: res["Hires sampler"] = "Use same sampler" + if "Hires checkpoint" not in res: + res["Hires checkpoint"] = "Use same checkpoint" + if "Hires prompt" not in res: res["Hires prompt"] = "" diff --git a/modules/processing.py b/modules/processing.py index b0992ee1..7026487a 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -935,7 +935,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): cached_hr_uc = [None, None] cached_hr_c = [None, None] - def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs): + def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_checkpoint_name: str = None, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs): super().__init__(**kwargs) self.enable_hr = enable_hr self.denoising_strength = denoising_strength @@ -946,11 +946,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_resize_y = hr_resize_y self.hr_upscale_to_x = hr_resize_x self.hr_upscale_to_y = hr_resize_y + self.hr_checkpoint_name = hr_checkpoint_name + self.hr_checkpoint_info = None self.hr_sampler_name = hr_sampler_name self.hr_prompt = hr_prompt self.hr_negative_prompt = hr_negative_prompt self.all_hr_prompts = None self.all_hr_negative_prompts = None + self.latent_scale_mode = None if firstphase_width != 0 or firstphase_height != 0: self.hr_upscale_to_x = self.width @@ -973,6 +976,14 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def init(self, all_prompts, all_seeds, all_subseeds): if self.enable_hr: + if self.hr_checkpoint_name: + self.hr_checkpoint_info = sd_models.get_closet_checkpoint_match(self.hr_checkpoint_name) + + if self.hr_checkpoint_info is None: + raise Exception(f'Could not find checkpoint with name {self.hr_checkpoint_name}') + + self.extra_generation_params["Hires checkpoint"] = self.hr_checkpoint_info.short_title + if self.hr_sampler_name is not None and self.hr_sampler_name != self.sampler_name: self.extra_generation_params["Hires sampler"] = self.hr_sampler_name @@ -982,6 +993,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): if tuple(self.hr_negative_prompt) != tuple(self.negative_prompt): self.extra_generation_params["Hires negative prompt"] = self.hr_negative_prompt + self.latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") + if self.enable_hr and self.latent_scale_mode is None: + if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers): + raise Exception(f"could not find upscaler named {self.hr_upscaler}") + if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height): self.hr_resize_x = self.width self.hr_resize_y = self.height @@ -1020,14 +1036,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.truncate_x = (self.hr_upscale_to_x - target_w) // opt_f self.truncate_y = (self.hr_upscale_to_y - target_h) // opt_f - # special case: the user has chosen to do nothing - if self.hr_upscale_to_x == self.width and self.hr_upscale_to_y == self.height: - self.enable_hr = False - self.denoising_strength = None - self.extra_generation_params.pop("Hires upscale", None) - self.extra_generation_params.pop("Hires resize", None) - return - if not state.processing_has_refined_job_count: if state.job_count == -1: state.job_count = self.n_iter @@ -1045,17 +1053,22 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): def sample(self, conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts): self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model) - latent_scale_mode = shared.latent_upscale_modes.get(self.hr_upscaler, None) if self.hr_upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") - if self.enable_hr and latent_scale_mode is None: - if not any(x.name == self.hr_upscaler for x in shared.sd_upscalers): - raise Exception(f"could not find upscaler named {self.hr_upscaler}") - x = create_random_tensors([opt_C, self.height // opt_f, self.width // opt_f], seeds=seeds, subseeds=subseeds, subseed_strength=self.subseed_strength, seed_resize_from_h=self.seed_resize_from_h, seed_resize_from_w=self.seed_resize_from_w, p=self) samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) if not self.enable_hr: return samples + current = shared.sd_model.sd_checkpoint_info + try: + if self.hr_checkpoint_info is not None: + sd_models.reload_model_weights(info=self.hr_checkpoint_info) + + return self.sample_hr_pass(samples, seeds, subseeds, subseed_strength, prompts) + finally: + sd_models.reload_model_weights(info=current) + + def sample_hr_pass(self, samples, seeds, subseeds, subseed_strength, prompts): self.is_hr_pass = True target_width = self.hr_upscale_to_x @@ -1073,11 +1086,11 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): info = create_infotext(self, self.all_prompts, self.all_seeds, self.all_subseeds, [], iteration=self.iteration, position_in_batch=index) images.save_image(image, self.outpath_samples, "", seeds[index], prompts[index], opts.samples_format, info=info, p=self, suffix="-before-highres-fix") - if latent_scale_mode is not None: + if self.latent_scale_mode is not None: for i in range(samples.shape[0]): save_intermediate(samples, i) - samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=latent_scale_mode["mode"], antialias=latent_scale_mode["antialias"]) + samples = torch.nn.functional.interpolate(samples, size=(target_height // opt_f, target_width // opt_f), mode=self.latent_scale_mode["mode"], antialias=self.latent_scale_mode["antialias"]) # Avoid making the inpainting conditioning unless necessary as # this does need some extra compute to decode / encode the image again. @@ -1193,7 +1206,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): self.hr_uc = None self.hr_c = None - if self.enable_hr: + if self.enable_hr and self.hr_checkpoint_info is None: if shared.opts.hires_fix_use_firstpass_conds: self.calculate_hr_conds() diff --git a/modules/sd_models.py b/modules/sd_models.py index acb1e817..cb67e425 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -52,6 +52,7 @@ class CheckpointInfo: self.shorthash = self.sha256[0:10] if self.sha256 else None self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]' + self.short_title = self.name_for_extra if self.shorthash is None else f'{self.name_for_extra} [{self.shorthash}]' self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) @@ -81,6 +82,7 @@ class CheckpointInfo: checkpoints_list.pop(self.title) self.title = f'{self.name} [{self.shorthash}]' + self.short_title = f'{self.name_for_extra} [{self.shorthash}]' self.register() return self.shorthash @@ -101,14 +103,8 @@ def setup_model(): enable_midas_autodownload() -def checkpoint_tiles(): - def convert(name): - return int(name) if name.isdigit() else name.lower() - - def alphanumeric_key(key): - return [convert(c) for c in re.split('([0-9]+)', key)] - - return sorted([x.title for x in checkpoints_list.values()], key=alphanumeric_key) +def checkpoint_tiles(use_short=False): + return [x.short_title if use_short else x.title for x in checkpoints_list.values()] def list_models(): @@ -131,11 +127,14 @@ def list_models(): elif cmd_ckpt is not None and cmd_ckpt != shared.default_sd_model_file: print(f"Checkpoint in --ckpt argument not found (Possible it was moved to {model_path}: {cmd_ckpt}", file=sys.stderr) - for filename in sorted(model_list, key=str.lower): + for filename in model_list: checkpoint_info = CheckpointInfo(filename) checkpoint_info.register() +re_strip_checksum = re.compile(r"\s*\[[^]]+]\s*$") + + def get_closet_checkpoint_match(search_string): checkpoint_info = checkpoint_aliases.get(search_string, None) if checkpoint_info is not None: @@ -145,6 +144,11 @@ def get_closet_checkpoint_match(search_string): if found: return found[0] + search_string_without_checksum = re.sub(re_strip_checksum, '', search_string) + found = sorted([info for info in checkpoints_list.values() if search_string_without_checksum in info.title], key=lambda x: len(x.title)) + if found: + return found[0] + return None diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..807fb9e3 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -220,12 +220,19 @@ class State: return import modules.sd_samplers - if opts.show_progress_grid: - self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) - else: - self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) - self.current_image_sampling_step = self.sampling_step + try: + if opts.show_progress_grid: + self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) + else: + self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) + + self.current_image_sampling_step = self.sampling_step + + except Exception: + # when switching models during genration, VAE would be on CPU, so creating an image will fail. + # we silently ignore this error + errors.record_exception() def assign_current_image(self, image): self.current_image = image @@ -512,7 +519,7 @@ options_templates.update(options_section(('ui', "User interface"), { "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_restart(), "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_restart(), - "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires sampler selection").needs_restart(), + "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_restart(), "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_restart(), "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_restart(), })) diff --git a/modules/txt2img.py b/modules/txt2img.py index 29d94e8c..935ed418 100644 --- a/modules/txt2img.py +++ b/modules/txt2img.py @@ -9,7 +9,7 @@ from modules.ui import plaintext_to_html import gradio as gr -def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args): +def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_checkpoint_name: str, hr_sampler_index: int, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args): override_settings = create_override_settings_dict(override_settings_texts) p = processing.StableDiffusionProcessingTxt2Img( @@ -41,6 +41,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step hr_second_pass_steps=hr_second_pass_steps, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y, + hr_checkpoint_name=None if hr_checkpoint_name == 'Use same checkpoint' else hr_checkpoint_name, hr_sampler_name=sd_samplers.samplers_for_img2img[hr_sampler_index - 1].name if hr_sampler_index != 0 else None, hr_prompt=hr_prompt, hr_negative_prompt=hr_negative_prompt, diff --git a/modules/ui.py b/modules/ui.py index 07ecee7b..6d8265f2 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -476,6 +476,10 @@ def create_ui(): hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y") with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container: + checkpoint_choices = lambda: ["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True) + hr_checkpoint_name = gr.Dropdown(label='Hires checkpoint', elem_id="hr_checkpoint", choices=checkpoint_choices(), value="Use same checkpoint") + create_refresh_button(hr_checkpoint_name, modules.sd_models.list_models, lambda: {"choices": checkpoint_choices()}, "hr_checkpoint_refresh") + hr_sampler_index = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + [x.name for x in samplers_for_img2img], value="Use same sampler", type="index") with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container: @@ -553,6 +557,7 @@ def create_ui(): hr_second_pass_steps, hr_resize_x, hr_resize_y, + hr_checkpoint_name, hr_sampler_index, hr_prompt, hr_negative_prompt, @@ -630,8 +635,9 @@ def create_ui(): (hr_second_pass_steps, "Hires steps"), (hr_resize_x, "Hires resize-1"), (hr_resize_y, "Hires resize-2"), + (hr_checkpoint_name, "Hires checkpoint"), (hr_sampler_index, "Hires sampler"), - (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" else gr.update()), + (hr_sampler_container, lambda d: gr.update(visible=True) if d.get("Hires sampler", "Use same sampler") != "Use same sampler" or d.get("Hires checkpoint", "Use same checkpoint") != "Use same checkpoint" else gr.update()), (hr_prompt, "Hires prompt"), (hr_negative_prompt, "Hires negative prompt"), (hr_prompts_container, lambda d: gr.update(visible=True) if d.get("Hires prompt", "") != "" or d.get("Hires negative prompt", "") != "" else gr.update()), -- cgit v1.2.3 From 4d9b096663288e2aa738723fa63950f3d41f6170 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 31 Jul 2023 10:43:31 +0300 Subject: additional memory improvements when switching between models of different types --- modules/sd_models.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index cb67e425..4855037a 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -582,7 +582,10 @@ def reload_model_weights(sd_model=None, info=None): timer.record("find config") if sd_model is None or checkpoint_config != sd_model.used_config: - del sd_model + if sd_model is not None: + sd_model.to(device="meta") + + devices.torch_gc() load_model(checkpoint_info, already_loaded_state_dict=state_dict) return model_data.sd_model -- cgit v1.2.3 From b235022c615a7384f73c05fe240d8f4a28d103d4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 1 Aug 2023 00:24:48 +0300 Subject: option to keep multiple models in memory --- modules/lowvram.py | 3 + modules/sd_hijack.py | 6 +- modules/sd_hijack_inpainting.py | 5 +- modules/sd_models.py | 136 +++++++++++++++++++++++++++++++++------- modules/sd_models_xl.py | 8 +-- modules/shared.py | 12 +++- 6 files changed, 135 insertions(+), 35 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/lowvram.py b/modules/lowvram.py index 3f830664..96f52b7b 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -15,6 +15,9 @@ def send_everything_to_cpu(): def setup_for_low_vram(sd_model, use_medvram): + if getattr(sd_model, 'lowvram', False): + return + sd_model.lowvram = True parents = {} diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index cfa5f0eb..7d692e3c 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -30,8 +30,10 @@ ldm.modules.attention.MemoryEfficientCrossAttention = ldm.modules.attention.Cros ldm.modules.attention.BasicTransformerBlock.ATTENTION_MODES["softmax-xformers"] = ldm.modules.attention.CrossAttention # silence new console spam from SD2 -ldm.modules.attention.print = lambda *args: None -ldm.modules.diffusionmodules.model.print = lambda *args: None +ldm.modules.attention.print = shared.ldm_print +ldm.modules.diffusionmodules.model.print = shared.ldm_print +ldm.util.print = shared.ldm_print +ldm.models.diffusion.ddpm.print = shared.ldm_print optimizers = [] current_optimizer: sd_hijack_optimizations.SdOptimization = None diff --git a/modules/sd_hijack_inpainting.py b/modules/sd_hijack_inpainting.py index c1977b19..97350f4f 100644 --- a/modules/sd_hijack_inpainting.py +++ b/modules/sd_hijack_inpainting.py @@ -91,7 +91,4 @@ def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=F return x_prev, pred_x0, e_t -def do_inpainting_hijack(): - # p_sample_plms is needed because PLMS can't work with dicts as conditionings - - ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms +ldm.models.diffusion.plms.PLMSSampler.p_sample_plms = p_sample_plms diff --git a/modules/sd_models.py b/modules/sd_models.py index acb1e817..77195f2f 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -15,7 +15,6 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl -from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer import tomesd @@ -423,6 +422,7 @@ sdxl_refiner_clip_weight = 'conditioner.embedders.0.model.ln_final.weight' class SdModelData: def __init__(self): self.sd_model = None + self.loaded_sd_models = [] self.was_loaded_at_least_once = False self.lock = threading.Lock() @@ -437,6 +437,7 @@ class SdModelData: try: load_model() + except Exception as e: errors.display(e, "loading stable diffusion model", full_traceback=True) print("", file=sys.stderr) @@ -448,11 +449,24 @@ class SdModelData: def set_sd_model(self, v): self.sd_model = v + try: + self.loaded_sd_models.remove(v) + except ValueError: + pass + + if v is not None: + self.loaded_sd_models.insert(0, v) + model_data = SdModelData() def get_empty_cond(sd_model): + from modules import extra_networks, processing + + p = processing.StableDiffusionProcessingTxt2Img() + extra_networks.activate(p, {}) + if hasattr(sd_model, 'conditioner'): d = sd_model.get_learned_conditioning([""]) return d['crossattn'] @@ -460,19 +474,43 @@ def get_empty_cond(sd_model): return sd_model.cond_stage_model([""]) +def send_model_to_cpu(m): + from modules import lowvram + + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + lowvram.send_everything_to_cpu() + else: + m.to(devices.cpu) + + devices.torch_gc() + + +def send_model_to_device(m): + from modules import lowvram + + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) + else: + m.to(shared.device) + + +def send_model_to_trash(m): + m.to(device="meta") + devices.torch_gc() + + def load_model(checkpoint_info=None, already_loaded_state_dict=None): - from modules import lowvram, sd_hijack + from modules import sd_hijack checkpoint_info = checkpoint_info or select_checkpoint() + timer = Timer() + if model_data.sd_model: - sd_hijack.model_hijack.undo_hijack(model_data.sd_model) + send_model_to_trash(model_data.sd_model) model_data.sd_model = None - gc.collect() devices.torch_gc() - do_inpainting_hijack() - - timer = Timer() + timer.record("unload existing model") if already_loaded_state_dict is not None: state_dict = already_loaded_state_dict @@ -512,12 +550,9 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): load_model_weights(sd_model, checkpoint_info, state_dict, timer) + timer.record("load weights from state dict") - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.setup_for_low_vram(sd_model, shared.cmd_opts.medvram) - else: - sd_model.to(shared.device) - + send_model_to_device(sd_model) timer.record("move model to device") sd_hijack.model_hijack.hijack(sd_model) @@ -525,7 +560,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): timer.record("hijack") sd_model.eval() - model_data.sd_model = sd_model + model_data.set_sd_model(sd_model) model_data.was_loaded_at_least_once = True sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True) # Reload embeddings after model load as they may or may not fit the model @@ -546,10 +581,61 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): return sd_model +def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): + """ + 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() + send_model_to_trash(loaded_model) + timer.record("send model to trash") + + if shared.opts.sd_checkpoints_keep_in_cpu: + send_model_to_cpu(sd_model) + timer.record("send model to cpu") + + if already_loaded is not None: + send_model_to_device(already_loaded) + timer.record("send model to device") + + model_data.set_sd_model(already_loaded) + print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}") + 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 + + 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): - from modules import lowvram, devices, sd_hijack + from modules import devices, sd_hijack checkpoint_info = info or select_checkpoint() + timer = Timer() + if not sd_model: sd_model = model_data.sd_model @@ -558,19 +644,17 @@ def reload_model_weights(sd_model=None, info=None): else: current_checkpoint_info = sd_model.sd_checkpoint_info if sd_model.sd_model_checkpoint == checkpoint_info.filename: - return - - sd_unet.apply_unet("None") + return sd_model - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.send_everything_to_cpu() - else: - sd_model.to(devices.cpu) + sd_model = reuse_model_from_already_loaded(sd_model, checkpoint_info, timer) + if sd_model is not None and sd_model.sd_checkpoint_info.filename == checkpoint_info.filename: + return sd_model + if sd_model is not None: + sd_unet.apply_unet("None") + send_model_to_cpu(sd_model) sd_hijack.model_hijack.undo_hijack(sd_model) - timer = Timer() - state_dict = get_checkpoint_state_dict(checkpoint_info, timer) checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info) @@ -578,7 +662,9 @@ def reload_model_weights(sd_model=None, info=None): timer.record("find config") if sd_model is None or checkpoint_config != sd_model.used_config: - del sd_model + if sd_model is not None: + send_model_to_trash(sd_model) + load_model(checkpoint_info, already_loaded_state_dict=state_dict) return model_data.sd_model @@ -601,6 +687,8 @@ def reload_model_weights(sd_model=None, info=None): print(f"Weights loaded in {timer.summary()}.") + model_data.set_sd_model(sd_model) + return sd_model diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py index bc219508..01123321 100644 --- a/modules/sd_models_xl.py +++ b/modules/sd_models_xl.py @@ -98,10 +98,10 @@ def extend_sdxl(model): model.conditioner.wrapped = torch.nn.Module() -sgm.modules.attention.print = lambda *args: None -sgm.modules.diffusionmodules.model.print = lambda *args: None -sgm.modules.diffusionmodules.openaimodel.print = lambda *args: None -sgm.modules.encoders.modules.print = lambda *args: None +sgm.modules.attention.print = shared.ldm_print +sgm.modules.diffusionmodules.model.print = shared.ldm_print +sgm.modules.diffusionmodules.openaimodel.print = shared.ldm_print +sgm.modules.encoders.modules.print = shared.ldm_print # this gets the code to load the vanilla attention that we override sgm.modules.attention.SDP_IS_AVAILABLE = True diff --git a/modules/shared.py b/modules/shared.py index aa72c9c8..0184fcd0 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -392,6 +392,7 @@ options_templates.update(options_section(('system', "System"), { "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."), "list_hidden_files": OptionInfo(True, "Load models/files in hidden directories").info("directory is hidden if its name starts with \".\""), "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"), + "hide_ldm_prints": OptionInfo(True, "Prevent Stability-AI's ldm/sgm modules from printing noise to console."), })) options_templates.update(options_section(('training', "Training"), { @@ -411,7 +412,9 @@ options_templates.update(options_section(('training', "Training"), { options_templates.update(options_section(('sd', "Stable Diffusion"), { "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), - "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), + "sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}), + "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"), + "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"), "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), @@ -889,3 +892,10 @@ def walk_files(path, allowed_extensions=None): continue yield os.path.join(root, filename) + + +def ldm_print(*args, **kwargs): + if opts.hide_ldm_prints: + return + + print(*args, **kwargs) -- cgit v1.2.3 From 4b43480fe8b65a3bd24dc9bc03a7e910c9b0314f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 1 Aug 2023 07:08:11 +0300 Subject: show metadata for SD checkpoints in the extra networks UI --- modules/sd_models.py | 26 ++++++++++++++++---------- modules/ui_extra_networks_checkpoints.py | 1 + 2 files changed, 17 insertions(+), 10 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index acb1e817..1af7fd78 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -14,7 +14,7 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config -from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl +from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer import tomesd @@ -33,6 +33,8 @@ class CheckpointInfo: self.filename = filename abspath = os.path.abspath(filename) + self.is_safetensors = os.path.splitext(filename)[1].lower() == ".safetensors" + if shared.cmd_opts.ckpt_dir is not None and abspath.startswith(shared.cmd_opts.ckpt_dir): name = abspath.replace(shared.cmd_opts.ckpt_dir, '') elif abspath.startswith(model_path): @@ -43,6 +45,19 @@ class CheckpointInfo: if name.startswith("\\") or name.startswith("/"): name = name[1:] + def read_metadata(): + metadata = read_metadata_from_safetensors(filename) + self.modelspec_thumbnail = metadata.pop('modelspec.thumbnail', None) + + return metadata + + self.metadata = {} + if self.is_safetensors: + try: + self.metadata = cache.cached_data_for_file('safetensors-metadata', "checkpoint/" + name, filename, read_metadata) + except Exception as e: + errors.display(e, f"reading metadata for {filename}") + self.name = name self.name_for_extra = os.path.splitext(os.path.basename(filename))[0] self.model_name = os.path.splitext(name.replace("/", "_").replace("\\", "_"))[0] @@ -55,15 +70,6 @@ class CheckpointInfo: self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) - self.metadata = {} - - _, ext = os.path.splitext(self.filename) - if ext.lower() == ".safetensors": - try: - self.metadata = read_metadata_from_safetensors(filename) - except Exception as e: - errors.display(e, f"reading checkpoint metadata: {filename}") - def register(self): checkpoints_list[self.title] = self for id in self.ids: diff --git a/modules/ui_extra_networks_checkpoints.py b/modules/ui_extra_networks_checkpoints.py index 76780cfd..2bb0a222 100644 --- a/modules/ui_extra_networks_checkpoints.py +++ b/modules/ui_extra_networks_checkpoints.py @@ -23,6 +23,7 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage): "search_term": self.search_terms_from_path(checkpoint.filename) + " " + (checkpoint.sha256 or ""), "onclick": '"' + html.escape(f"""return selectCheckpoint({quote_js(name)})""") + '"', "local_preview": f"{path}.{shared.opts.samples_format}", + "metadata": checkpoint.metadata, "sort_keys": {'default': index, **self.get_sort_keys(checkpoint.filename)}, } -- cgit v1.2.3 From 07be13caa357b14f6afa247566d53339522b8e66 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 1 Aug 2023 08:27:54 +0300 Subject: add metadata to checkpoint merger --- modules/extras.py | 39 +++++++++++++++++++++++++++++++++------ modules/sd_models.py | 2 +- modules/ui_checkpoint_merger.py | 20 ++++++++++++++++++-- 3 files changed, 52 insertions(+), 9 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/extras.py b/modules/extras.py index e9c0263e..2a310ae3 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -7,7 +7,7 @@ import json import torch import tqdm -from modules import shared, images, sd_models, sd_vae, sd_models_config +from modules import shared, images, sd_models, sd_vae, sd_models_config, errors from modules.ui_common import plaintext_to_html import gradio as gr import safetensors.torch @@ -72,7 +72,20 @@ def to_half(tensor, enable): return tensor -def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights, save_metadata): +def read_metadata(primary_model_name, secondary_model_name, tertiary_model_name): + metadata = {} + + for checkpoint_name in [primary_model_name, secondary_model_name, tertiary_model_name]: + checkpoint_info = sd_models.checkpoints_list.get(checkpoint_name, None) + if checkpoint_info is None: + continue + + metadata.update(checkpoint_info.metadata) + + return json.dumps(metadata, indent=4, ensure_ascii=False) + + +def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source, bake_in_vae, discard_weights, save_metadata, add_merge_recipe, copy_metadata_fields, metadata_json): shared.state.begin(job="model-merge") def fail(message): @@ -241,11 +254,25 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ shared.state.textinfo = "Saving" print(f"Saving to {output_modelname}...") - metadata = None + metadata = {} + + if save_metadata and copy_metadata_fields: + if primary_model_info: + metadata.update(primary_model_info.metadata) + if secondary_model_info: + metadata.update(secondary_model_info.metadata) + if tertiary_model_info: + metadata.update(tertiary_model_info.metadata) if save_metadata: - metadata = {"format": "pt"} + try: + metadata.update(json.loads(metadata_json)) + except Exception as e: + errors.display(e, "readin metadata from json") + + metadata["format"] = "pt" + if save_metadata and add_merge_recipe: merge_recipe = { "type": "webui", # indicate this model was merged with webui's built-in merger "primary_model_hash": primary_model_info.sha256, @@ -261,7 +288,6 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ "is_inpainting": result_is_inpainting_model, "is_instruct_pix2pix": result_is_instruct_pix2pix_model } - metadata["sd_merge_recipe"] = json.dumps(merge_recipe) sd_merge_models = {} @@ -281,11 +307,12 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_ if tertiary_model_info: add_model_metadata(tertiary_model_info) + metadata["sd_merge_recipe"] = json.dumps(merge_recipe) metadata["sd_merge_models"] = json.dumps(sd_merge_models) _, extension = os.path.splitext(output_modelname) if extension.lower() == ".safetensors": - safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata) + safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata if len(metadata)>0 else None) else: torch.save(theta_0, output_modelname) diff --git a/modules/sd_models.py b/modules/sd_models.py index 1af7fd78..8f72f21d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -85,7 +85,7 @@ class CheckpointInfo: if self.shorthash not in self.ids: self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] - checkpoints_list.pop(self.title) + checkpoints_list.pop(self.title, None) self.title = f'{self.name} [{self.shorthash}]' self.register() diff --git a/modules/ui_checkpoint_merger.py b/modules/ui_checkpoint_merger.py index 8e72258a..4863d861 100644 --- a/modules/ui_checkpoint_merger.py +++ b/modules/ui_checkpoint_merger.py @@ -51,7 +51,6 @@ class UiCheckpointMerger: with FormRow(): self.checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="safetensors", label="Checkpoint format", elem_id="modelmerger_checkpoint_format") self.save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half") - self.save_metadata = gr.Checkbox(value=True, label="Save metadata (.safetensors only)", elem_id="modelmerger_save_metadata") with FormRow(): with gr.Column(): @@ -65,16 +64,30 @@ class UiCheckpointMerger: with FormRow(): self.discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights") - with gr.Row(): + with gr.Accordion("Metadata", open=False) as metadata_editor: + with FormRow(): + self.save_metadata = gr.Checkbox(value=True, label="Save metadata", elem_id="modelmerger_save_metadata") + self.add_merge_recipe = gr.Checkbox(value=True, label="Add merge recipe metadata", elem_id="modelmerger_add_recipe") + self.copy_metadata_fields = gr.Checkbox(value=True, label="Copy metadata from merged models", elem_id="modelmerger_copy_metadata") + + self.metadata_json = gr.TextArea('{}', label="Metadata in JSON format") + self.read_metadata = gr.Button("Read metadata from selected checkpoints") + + with FormRow(): self.modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary') with gr.Column(variant='compact', elem_id="modelmerger_results_container"): with gr.Group(elem_id="modelmerger_results_panel"): self.modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False) + self.metadata_editor = metadata_editor self.blocks = modelmerger_interface def setup_ui(self, dummy_component, sd_model_checkpoint_component): + self.checkpoint_format.change(lambda fmt: gr.update(visible=fmt == 'safetensors'), inputs=[self.checkpoint_format], outputs=[self.metadata_editor], show_progress=False) + + self.read_metadata.click(extras.read_metadata, inputs=[self.primary_model_name, self.secondary_model_name, self.tertiary_model_name], outputs=[self.metadata_json]) + self.modelmerger_merge.click(fn=lambda: '', inputs=[], outputs=[self.modelmerger_result]) self.modelmerger_merge.click( fn=call_queue.wrap_gradio_gpu_call(modelmerger, extra_outputs=lambda: [gr.update() for _ in range(4)]), @@ -93,6 +106,9 @@ class UiCheckpointMerger: self.bake_in_vae, self.discard_weights, self.save_metadata, + self.add_merge_recipe, + self.copy_metadata_fields, + self.metadata_json, ], outputs=[ self.primary_model_name, -- cgit v1.2.3 From 390bffa81b747a7eb38ac7a0cd6dfb9fcc388151 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 1 Aug 2023 17:13:15 +0300 Subject: repair merge error --- modules/sd_models.py | 1 - 1 file changed, 1 deletion(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 40a450df..3c451a4b 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -15,7 +15,6 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache -from modules.sd_hijack_inpainting import do_inpainting_hijack from modules.timer import Timer import tomesd -- cgit v1.2.3 From 20549a50cb3c41868ce561c6658bfaa0d20ac7ba Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 3 Aug 2023 22:46:57 +0300 Subject: add style editor dialog rework toprow for img2img and txt2img to use a class with fields fix the console error when editing checkpoint user metadata --- modules/sd_models.py | 2 +- modules/styles.py | 5 +- modules/ui.py | 230 ++++++++++--------------- modules/ui_common.py | 32 +++- modules/ui_extra_networks_checkpoints.py | 2 +- modules/ui_extra_networks_hypernets.py | 2 +- modules/ui_extra_networks_textual_inversion.py | 2 +- modules/ui_prompt_styles.py | 110 ++++++++++++ style.css | 13 ++ 9 files changed, 248 insertions(+), 150 deletions(-) create mode 100644 modules/ui_prompt_styles.py (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 8f72f21d..1d93d893 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -68,7 +68,7 @@ class CheckpointInfo: self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]' - self.ids = [self.hash, self.model_name, self.title, name, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) + self.ids = [self.hash, self.model_name, self.title, name, self.name_for_extra, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) def register(self): checkpoints_list[self.title] = self diff --git a/modules/styles.py b/modules/styles.py index ec0e1bc5..0740fe1b 100644 --- a/modules/styles.py +++ b/modules/styles.py @@ -106,10 +106,7 @@ class StyleDatabase: if os.path.exists(path): shutil.copy(path, f"{path}.bak") - fd = os.open(path, os.O_RDWR | os.O_CREAT) - with os.fdopen(fd, "w", encoding="utf-8-sig", newline='') as file: - # _fields is actually part of the public API: typing.NamedTuple is a replacement for collections.NamedTuple, - # and collections.NamedTuple has explicit documentation for accessing _fields. Same goes for _asdict() + with open(path, "w", encoding="utf-8-sig", newline='') as file: writer = csv.DictWriter(file, fieldnames=PromptStyle._fields) writer.writeheader() writer.writerows(style._asdict() for k, style in self.styles.items()) diff --git a/modules/ui.py b/modules/ui.py index ac2787eb..c059dcec 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -12,7 +12,7 @@ import numpy as np from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call -from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger +from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, ui_prompt_styles from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path from modules.ui_common import create_refresh_button @@ -92,19 +92,6 @@ def send_gradio_gallery_to_image(x): return image_from_url_text(x[0]) -def add_style(name: str, prompt: str, negative_prompt: str): - if name is None: - return [gr_show() for x in range(4)] - - style = modules.styles.PromptStyle(name, prompt, negative_prompt) - shared.prompt_styles.styles[style.name] = style - # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we - # reserialize all styles every time we save them - shared.prompt_styles.save_styles(shared.styles_filename) - - return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(2)] - - def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y): from modules import processing, devices @@ -129,13 +116,6 @@ def resize_from_to_html(width, height, scale_by): return f"resize: from {width}x{height} to {target_width}x{target_height}" -def apply_styles(prompt, prompt_neg, styles): - prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles) - prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles) - - return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value=[])] - - def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_dir, *ii_singles): if mode in {0, 1, 3, 4}: return [interrogation_function(ii_singles[mode]), None] @@ -267,71 +247,67 @@ def update_token_counter(text, steps): return f"{token_count}/{max_length}" -def create_toprow(is_img2img): - id_part = "img2img" if is_img2img else "txt2img" +class Toprow: + def __init__(self, is_img2img): + id_part = "img2img" if is_img2img else "txt2img" + self.id_part = id_part - with gr.Row(elem_id=f"{id_part}_toprow", variant="compact"): - with gr.Column(elem_id=f"{id_part}_prompt_container", scale=6): - with gr.Row(): - with gr.Column(scale=80): - with gr.Row(): - prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)", elem_classes=["prompt"]) - - with gr.Row(): - with gr.Column(scale=80): - with gr.Row(): - negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)", elem_classes=["prompt"]) - - button_interrogate = None - button_deepbooru = None - if is_img2img: - with gr.Column(scale=1, elem_classes="interrogate-col"): - button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") - button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") - - with gr.Column(scale=1, elem_id=f"{id_part}_actions_column"): - with gr.Row(elem_id=f"{id_part}_generate_box", elem_classes="generate-box"): - interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt", elem_classes="generate-box-interrupt") - skip = gr.Button('Skip', elem_id=f"{id_part}_skip", elem_classes="generate-box-skip") - submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary') - - skip.click( - fn=lambda: shared.state.skip(), - inputs=[], - outputs=[], - ) + with gr.Row(elem_id=f"{id_part}_toprow", variant="compact"): + with gr.Column(elem_id=f"{id_part}_prompt_container", scale=6): + with gr.Row(): + with gr.Column(scale=80): + with gr.Row(): + self.prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)", elem_classes=["prompt"]) - interrupt.click( - fn=lambda: shared.state.interrupt(), - inputs=[], - outputs=[], - ) + with gr.Row(): + with gr.Column(scale=80): + with gr.Row(): + self.negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)", elem_classes=["prompt"]) + + self.button_interrogate = None + self.button_deepbooru = None + if is_img2img: + with gr.Column(scale=1, elem_classes="interrogate-col"): + self.button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate") + self.button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru") + + with gr.Column(scale=1, elem_id=f"{id_part}_actions_column"): + with gr.Row(elem_id=f"{id_part}_generate_box", elem_classes="generate-box"): + self.interrupt = gr.Button('Interrupt', elem_id=f"{id_part}_interrupt", elem_classes="generate-box-interrupt") + self.skip = gr.Button('Skip', elem_id=f"{id_part}_skip", elem_classes="generate-box-skip") + self.submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary') + + self.skip.click( + fn=lambda: shared.state.skip(), + inputs=[], + outputs=[], + ) - with gr.Row(elem_id=f"{id_part}_tools"): - paste = ToolButton(value=paste_symbol, elem_id="paste") - clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt") - extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks") - prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id=f"{id_part}_style_apply") - save_style = ToolButton(value=save_style_symbol, elem_id=f"{id_part}_style_create") - restore_progress_button = ToolButton(value=restore_progress_symbol, elem_id=f"{id_part}_restore_progress", visible=False) - - token_counter = gr.HTML(value="0/75", elem_id=f"{id_part}_token_counter", elem_classes=["token-counter"]) - token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") - negative_token_counter = gr.HTML(value="0/75", elem_id=f"{id_part}_negative_token_counter", elem_classes=["token-counter"]) - negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button") - - clear_prompt_button.click( - fn=lambda *x: x, - _js="confirm_clear_prompt", - inputs=[prompt, negative_prompt], - outputs=[prompt, negative_prompt], - ) + self.interrupt.click( + fn=lambda: shared.state.interrupt(), + inputs=[], + outputs=[], + ) - with gr.Row(elem_id=f"{id_part}_styles_row"): - prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True) - create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles") + with gr.Row(elem_id=f"{id_part}_tools"): + self.paste = ToolButton(value=paste_symbol, elem_id="paste") + self.clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt") + self.extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks") + self.restore_progress_button = ToolButton(value=restore_progress_symbol, elem_id=f"{id_part}_restore_progress", visible=False) + + self.token_counter = gr.HTML(value="0/75", elem_id=f"{id_part}_token_counter", elem_classes=["token-counter"]) + self.token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button") + self.negative_token_counter = gr.HTML(value="0/75", elem_id=f"{id_part}_negative_token_counter", elem_classes=["token-counter"]) + self.negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button") + + self.clear_prompt_button.click( + fn=lambda *x: x, + _js="confirm_clear_prompt", + inputs=[self.prompt, self.negative_prompt], + outputs=[self.prompt, self.negative_prompt], + ) - return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button, restore_progress_button + self.ui_styles = ui_prompt_styles.UiPromptStyles(id_part, self.prompt, self.negative_prompt) def setup_progressbar(*args, **kwargs): @@ -419,14 +395,14 @@ def create_ui(): modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False) with gr.Blocks(analytics_enabled=False) as txt2img_interface: - txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button, restore_progress_button = create_toprow(is_img2img=False) + toprow = txt2img_toprow = Toprow(is_img2img=False) dummy_component = gr.Label(visible=False) txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False) with FormRow(variant='compact', elem_id="txt2img_extra_networks", visible=False) as extra_networks: from modules import ui_extra_networks - extra_networks_ui = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'txt2img') + extra_networks_ui = ui_extra_networks.create_ui(extra_networks, toprow.extra_networks_button, 'txt2img') with gr.Row().style(equal_height=False): with gr.Column(variant='compact', elem_id="txt2img_settings"): @@ -532,9 +508,9 @@ def create_ui(): _js="submit", inputs=[ dummy_component, - txt2img_prompt, - txt2img_negative_prompt, - txt2img_prompt_styles, + toprow.prompt, + toprow.negative_prompt, + toprow.ui_styles.dropdown, steps, sampler_index, restore_faces, @@ -569,12 +545,12 @@ def create_ui(): show_progress=False, ) - txt2img_prompt.submit(**txt2img_args) - submit.click(**txt2img_args) + toprow.prompt.submit(**txt2img_args) + toprow.submit.click(**txt2img_args) res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('txt2img')}", inputs=None, outputs=None, show_progress=False) - restore_progress_button.click( + toprow.restore_progress_button.click( fn=progress.restore_progress, _js="restoreProgressTxt2img", inputs=[dummy_component], @@ -593,7 +569,7 @@ def create_ui(): txt_prompt_img ], outputs=[ - txt2img_prompt, + toprow.prompt, txt_prompt_img ], show_progress=False, @@ -607,8 +583,8 @@ def create_ui(): ) txt2img_paste_fields = [ - (txt2img_prompt, "Prompt"), - (txt2img_negative_prompt, "Negative prompt"), + (toprow.prompt, "Prompt"), + (toprow.negative_prompt, "Negative prompt"), (steps, "Steps"), (sampler_index, "Sampler"), (restore_faces, "Face restoration"), @@ -621,7 +597,7 @@ def create_ui(): (subseed_strength, "Variation seed strength"), (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), - (txt2img_prompt_styles, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), + (toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), (denoising_strength, "Denoising strength"), (enable_hr, lambda d: "Denoising strength" in d), (hr_options, lambda d: gr.Row.update(visible="Denoising strength" in d)), @@ -639,12 +615,12 @@ def create_ui(): ] parameters_copypaste.add_paste_fields("txt2img", None, txt2img_paste_fields, override_settings) parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding( - paste_button=txt2img_paste, tabname="txt2img", source_text_component=txt2img_prompt, source_image_component=None, + paste_button=toprow.paste, tabname="txt2img", source_text_component=toprow.prompt, source_image_component=None, )) txt2img_preview_params = [ - txt2img_prompt, - txt2img_negative_prompt, + toprow.prompt, + toprow.negative_prompt, steps, sampler_index, cfg_scale, @@ -653,8 +629,8 @@ def create_ui(): height, ] - token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_prompt, steps], outputs=[token_counter]) - negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[txt2img_negative_prompt, steps], outputs=[negative_token_counter]) + toprow.token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps], outputs=[toprow.token_counter]) + toprow.negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_token_counter]) ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery) @@ -662,13 +638,13 @@ def create_ui(): modules.scripts.scripts_img2img.initialize_scripts(is_img2img=True) with gr.Blocks(analytics_enabled=False) as img2img_interface: - img2img_prompt, img2img_prompt_styles, img2img_negative_prompt, submit, img2img_interrogate, img2img_deepbooru, img2img_prompt_style_apply, img2img_save_style, img2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button, restore_progress_button = create_toprow(is_img2img=True) + toprow = img2img_toprow = Toprow(is_img2img=True) img2img_prompt_img = gr.File(label="", elem_id="img2img_prompt_image", file_count="single", type="binary", visible=False) with FormRow(variant='compact', elem_id="img2img_extra_networks", visible=False) as extra_networks: from modules import ui_extra_networks - extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, extra_networks_button, 'img2img') + extra_networks_ui_img2img = ui_extra_networks.create_ui(extra_networks, toprow.extra_networks_button, 'img2img') with FormRow().style(equal_height=False): with gr.Column(variant='compact', elem_id="img2img_settings"): @@ -889,7 +865,7 @@ def create_ui(): img2img_prompt_img ], outputs=[ - img2img_prompt, + toprow.prompt, img2img_prompt_img ], show_progress=False, @@ -901,9 +877,9 @@ def create_ui(): inputs=[ dummy_component, dummy_component, - img2img_prompt, - img2img_negative_prompt, - img2img_prompt_styles, + toprow.prompt, + toprow.negative_prompt, + toprow.ui_styles.dropdown, init_img, sketch, init_img_with_mask, @@ -962,11 +938,11 @@ def create_ui(): inpaint_color_sketch, init_img_inpaint, ], - outputs=[img2img_prompt, dummy_component], + outputs=[toprow.prompt, dummy_component], ) - img2img_prompt.submit(**img2img_args) - submit.click(**img2img_args) + toprow.prompt.submit(**img2img_args) + toprow.submit.click(**img2img_args) res_switch_btn.click(fn=None, _js="function(){switchWidthHeight('img2img')}", inputs=None, outputs=None, show_progress=False) @@ -978,7 +954,7 @@ def create_ui(): show_progress=False, ) - restore_progress_button.click( + toprow.restore_progress_button.click( fn=progress.restore_progress, _js="restoreProgressImg2img", inputs=[dummy_component], @@ -991,46 +967,24 @@ def create_ui(): show_progress=False, ) - img2img_interrogate.click( + toprow.button_interrogate.click( fn=lambda *args: process_interrogate(interrogate, *args), **interrogate_args, ) - img2img_deepbooru.click( + toprow.button_deepbooru.click( fn=lambda *args: process_interrogate(interrogate_deepbooru, *args), **interrogate_args, ) - prompts = [(txt2img_prompt, txt2img_negative_prompt), (img2img_prompt, img2img_negative_prompt)] - style_dropdowns = [txt2img_prompt_styles, img2img_prompt_styles] - style_js_funcs = ["update_txt2img_tokens", "update_img2img_tokens"] - - for button, (prompt, negative_prompt) in zip([txt2img_save_style, img2img_save_style], prompts): - button.click( - fn=add_style, - _js="ask_for_style_name", - # Have to pass empty dummy component here, because the JavaScript and Python function have to accept - # the same number of parameters, but we only know the style-name after the JavaScript prompt - inputs=[dummy_component, prompt, negative_prompt], - outputs=[txt2img_prompt_styles, img2img_prompt_styles], - ) - - for button, (prompt, negative_prompt), styles, js_func in zip([txt2img_prompt_style_apply, img2img_prompt_style_apply], prompts, style_dropdowns, style_js_funcs): - button.click( - fn=apply_styles, - _js=js_func, - inputs=[prompt, negative_prompt, styles], - outputs=[prompt, negative_prompt, styles], - ) - - token_button.click(fn=update_token_counter, inputs=[img2img_prompt, steps], outputs=[token_counter]) - negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[img2img_negative_prompt, steps], outputs=[negative_token_counter]) + toprow.token_button.click(fn=update_token_counter, inputs=[toprow.prompt, steps], outputs=[toprow.token_counter]) + toprow.negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_token_counter]) ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery) img2img_paste_fields = [ - (img2img_prompt, "Prompt"), - (img2img_negative_prompt, "Negative prompt"), + (toprow.prompt, "Prompt"), + (toprow.negative_prompt, "Negative prompt"), (steps, "Steps"), (sampler_index, "Sampler"), (restore_faces, "Face restoration"), @@ -1044,7 +998,7 @@ def create_ui(): (subseed_strength, "Variation seed strength"), (seed_resize_from_w, "Seed resize from-1"), (seed_resize_from_h, "Seed resize from-2"), - (img2img_prompt_styles, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), + (toprow.ui_styles.dropdown, lambda d: d["Styles array"] if isinstance(d.get("Styles array"), list) else gr.update()), (denoising_strength, "Denoising strength"), (mask_blur, "Mask blur"), *modules.scripts.scripts_img2img.infotext_fields @@ -1052,7 +1006,7 @@ def create_ui(): parameters_copypaste.add_paste_fields("img2img", init_img, img2img_paste_fields, override_settings) parameters_copypaste.add_paste_fields("inpaint", init_img_with_mask, img2img_paste_fields, override_settings) parameters_copypaste.register_paste_params_button(parameters_copypaste.ParamBinding( - paste_button=img2img_paste, tabname="img2img", source_text_component=img2img_prompt, source_image_component=None, + paste_button=toprow.paste, tabname="img2img", source_text_component=toprow.prompt, source_image_component=None, )) modules.scripts.scripts_current = None diff --git a/modules/ui_common.py b/modules/ui_common.py index 11eb2a4b..ba75fa73 100644 --- a/modules/ui_common.py +++ b/modules/ui_common.py @@ -223,20 +223,44 @@ Requested path was: {f} def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id): + refresh_components = refresh_component if isinstance(refresh_component, list) else [refresh_component] + + label = None + for comp in refresh_components: + label = getattr(comp, 'label', None) + if label is not None: + break + def refresh(): refresh_method() args = refreshed_args() if callable(refreshed_args) else refreshed_args for k, v in args.items(): - setattr(refresh_component, k, v) + for comp in refresh_components: + setattr(comp, k, v) - return gr.update(**(args or {})) + return [gr.update(**(args or {})) for _ in refresh_components] - refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id) + refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id, tooltip=f"{label}: refresh" if label else "Refresh") refresh_button.click( fn=refresh, inputs=[], - outputs=[refresh_component] + outputs=[*refresh_components] ) return refresh_button + +def setup_dialog(button_show, dialog, *, button_close=None): + """Sets up the UI so that the dialog (gr.Box) is invisible, and is only shown when buttons_show is clicked, in a fullscreen modal window.""" + + dialog.visible = False + + button_show.click( + fn=lambda: gr.update(visible=True), + inputs=[], + outputs=[dialog], + ).then(fn=None, _js="function(){ popup(gradioApp().getElementById('" + dialog.elem_id + "')); }") + + if button_close: + button_close.click(fn=None, _js="closePopup") + diff --git a/modules/ui_extra_networks_checkpoints.py b/modules/ui_extra_networks_checkpoints.py index 2bb0a222..891d8f2c 100644 --- a/modules/ui_extra_networks_checkpoints.py +++ b/modules/ui_extra_networks_checkpoints.py @@ -12,7 +12,7 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage): def refresh(self): shared.refresh_checkpoints() - def create_item(self, name, index=None): + def create_item(self, name, index=None, enable_filter=True): checkpoint: sd_models.CheckpointInfo = sd_models.checkpoint_aliases.get(name) path, ext = os.path.splitext(checkpoint.filename) return { diff --git a/modules/ui_extra_networks_hypernets.py b/modules/ui_extra_networks_hypernets.py index e53ccb42..514a4562 100644 --- a/modules/ui_extra_networks_hypernets.py +++ b/modules/ui_extra_networks_hypernets.py @@ -11,7 +11,7 @@ class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage): def refresh(self): shared.reload_hypernetworks() - def create_item(self, name, index=None): + def create_item(self, name, index=None, enable_filter=True): full_path = shared.hypernetworks[name] path, ext = os.path.splitext(full_path) diff --git a/modules/ui_extra_networks_textual_inversion.py b/modules/ui_extra_networks_textual_inversion.py index d1794e50..73134698 100644 --- a/modules/ui_extra_networks_textual_inversion.py +++ b/modules/ui_extra_networks_textual_inversion.py @@ -12,7 +12,7 @@ class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage): def refresh(self): sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings(force_reload=True) - def create_item(self, name, index=None): + def create_item(self, name, index=None, enable_filter=True): embedding = sd_hijack.model_hijack.embedding_db.word_embeddings.get(name) path, ext = os.path.splitext(embedding.filename) diff --git a/modules/ui_prompt_styles.py b/modules/ui_prompt_styles.py new file mode 100644 index 00000000..85eb3a64 --- /dev/null +++ b/modules/ui_prompt_styles.py @@ -0,0 +1,110 @@ +import gradio as gr + +from modules import shared, ui_common, ui_components, styles + +styles_edit_symbol = '\U0001f58c\uFE0F' # 🖌️ +styles_materialize_symbol = '\U0001f4cb' # 📋 + + +def select_style(name): + style = shared.prompt_styles.styles.get(name) + existing = style is not None + empty = not name + + prompt = style.prompt if style else gr.update() + negative_prompt = style.negative_prompt if style else gr.update() + + return prompt, negative_prompt, gr.update(visible=existing), gr.update(visible=not empty) + + +def save_style(name, prompt, negative_prompt): + if not name: + return gr.update(visible=False) + + style = styles.PromptStyle(name, prompt, negative_prompt) + shared.prompt_styles.styles[style.name] = style + shared.prompt_styles.save_styles(shared.styles_filename) + + return gr.update(visible=True) + + +def delete_style(name): + if name == "": + return + + shared.prompt_styles.styles.pop(name, None) + shared.prompt_styles.save_styles(shared.styles_filename) + + return '', '', '' + + +def materialize_styles(prompt, negative_prompt, styles): + prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles) + negative_prompt = shared.prompt_styles.apply_negative_styles_to_prompt(negative_prompt, styles) + + return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=negative_prompt), gr.Dropdown.update(value=[])] + + +def refresh_styles(): + return gr.update(choices=list(shared.prompt_styles.styles)), gr.update(choices=list(shared.prompt_styles.styles)) + + +class UiPromptStyles: + def __init__(self, tabname, main_ui_prompt, main_ui_negative_prompt): + self.tabname = tabname + + with gr.Row(elem_id=f"{tabname}_styles_row"): + self.dropdown = gr.Dropdown(label="Styles", show_label=False, elem_id=f"{tabname}_styles", choices=list(shared.prompt_styles.styles), value=[], multiselect=True, tooltip="Styles") + edit_button = ui_components.ToolButton(value=styles_edit_symbol, elem_id=f"{tabname}_styles_edit_button", tooltip="Edit styles") + + with gr.Box(elem_id=f"{tabname}_styles_dialog", elem_classes="popup-dialog") as styles_dialog: + with gr.Row(): + self.selection = gr.Dropdown(label="Styles", elem_id=f"{tabname}_styles_edit_select", choices=list(shared.prompt_styles.styles), value=[], allow_custom_value=True, info="Styles allow you to add custom text to prompt. Use the {prompt} token in style text, and it will be replaced with user's prompt when applying style. Otherwise, style's text will be added to the end of the prompt.") + ui_common.create_refresh_button([self.dropdown, self.selection], shared.prompt_styles.reload, lambda: {"choices": list(shared.prompt_styles.styles)}, f"refresh_{tabname}_styles") + self.materialize = ui_components.ToolButton(value=styles_materialize_symbol, elem_id=f"{tabname}_style_apply", tooltip="Apply all selected styles from the style selction dropdown in main UI to the prompt.") + + with gr.Row(): + self.prompt = gr.Textbox(label="Prompt", show_label=True, elem_id=f"{tabname}_edit_style_prompt", lines=3) + + with gr.Row(): + self.neg_prompt = gr.Textbox(label="Negative prompt", show_label=True, elem_id=f"{tabname}_edit_style_neg_prompt", lines=3) + + with gr.Row(): + self.save = gr.Button('Save', variant='primary', elem_id=f'{tabname}_edit_style_save', visible=False) + self.delete = gr.Button('Delete', variant='primary', elem_id=f'{tabname}_edit_style_delete', visible=False) + self.close = gr.Button('Close', variant='secondary', elem_id=f'{tabname}_edit_style_close') + + self.selection.change( + fn=select_style, + inputs=[self.selection], + outputs=[self.prompt, self.neg_prompt, self.delete, self.save], + show_progress=False, + ) + + self.save.click( + fn=save_style, + inputs=[self.selection, self.prompt, self.neg_prompt], + outputs=[self.delete], + show_progress=False, + ).then(refresh_styles, outputs=[self.dropdown, self.selection], show_progress=False) + + self.delete.click( + fn=delete_style, + _js='function(name){ if(name == "") return ""; return confirm("Delete style " + name + "?") ? name : ""; }', + inputs=[self.selection], + outputs=[self.selection, self.prompt, self.neg_prompt], + show_progress=False, + ).then(refresh_styles, outputs=[self.dropdown, self.selection], show_progress=False) + + self.materialize.click( + fn=materialize_styles, + inputs=[main_ui_prompt, main_ui_negative_prompt, self.dropdown], + outputs=[main_ui_prompt, main_ui_negative_prompt, self.dropdown], + show_progress=False, + ).then(fn=None, _js="function(){update_"+tabname+"_tokens(); closePopup();}", show_progress=False) + + ui_common.setup_dialog(button_show=edit_button, dialog=styles_dialog, button_close=self.close) + + + + diff --git a/style.css b/style.css index 6c92d6e7..cf8470e4 100644 --- a/style.css +++ b/style.css @@ -972,3 +972,16 @@ div.block.gradio-box.edit-user-metadata { .edit-user-metadata-buttons{ margin-top: 1.5em; } + + + + +div.block.gradio-box.popup-dialog, .popup-dialog { + width: 56em; + background: var(--body-background-fill); + padding: 2em !important; +} + +div.block.gradio-box.popup-dialog > div:last-child, .popup-dialog > div:last-child{ + margin-top: 1em; +} -- cgit v1.2.3 From 24f21583cdba2ae6cc51773b956c6ce068d3dfe4 Mon Sep 17 00:00:00 2001 From: AnyISalIn Date: Fri, 4 Aug 2023 11:43:27 +0800 Subject: fix: prevent cache model.state_dict() after model hijack Signed-off-by: AnyISalIn --- modules/sd_models.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 1d93d893..ba15b451 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -303,12 +303,13 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer sd_models_xl.extend_sdxl(model) model.load_state_dict(state_dict, strict=False) - del state_dict timer.record("apply weights to model") if shared.opts.sd_checkpoint_cache > 0: # cache newly loaded model - checkpoints_loaded[checkpoint_info] = model.state_dict().copy() + checkpoints_loaded[checkpoint_info] = state_dict + + del state_dict if shared.cmd_opts.opt_channelslast: model.to(memory_format=torch.channels_last) -- cgit v1.2.3 From f1975b0213f5be400889ec04b3891d1cb571fe20 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 6 Aug 2023 17:01:07 +0300 Subject: initial refiner support --- modules/processing.py | 4 ++++ modules/sd_models.py | 18 +++++++++++++++++- modules/sd_samplers_common.py | 19 ++++++++++++++++++- modules/sd_samplers_compvis.py | 12 +++++++++++- modules/sd_samplers_kdiffusion.py | 30 ++++++++++++++++++++++++------ modules/shared.py | 2 ++ 6 files changed, 76 insertions(+), 9 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/processing.py b/modules/processing.py index 31745006..f4748d6d 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -666,6 +666,10 @@ def process_images(p: StableDiffusionProcessing) -> Processed: stored_opts = {k: opts.data[k] for k in p.override_settings.keys()} try: + # after running refiner, the refiner model is not unloaded - webui swaps back to main model here + if shared.sd_model.sd_checkpoint_info.title != opts.sd_model_checkpoint: + sd_models.reload_model_weights() + # if no checkpoint override or the override checkpoint can't be found, remove override entry and load opts checkpoint if sd_models.checkpoint_aliases.get(p.override_settings.get('sd_model_checkpoint')) is None: p.override_settings.pop('sd_model_checkpoint', None) diff --git a/modules/sd_models.py b/modules/sd_models.py index f6051604..981aa93d 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -289,11 +289,27 @@ def get_checkpoint_state_dict(checkpoint_info: CheckpointInfo, timer): return res +class SkipWritingToConfig: + """This context manager prevents load_model_weights from writing checkpoint name to the config when it loads weight.""" + + skip = False + previous = None + + def __enter__(self): + self.previous = SkipWritingToConfig.skip + SkipWritingToConfig.skip = True + return self + + def __exit__(self, exc_type, exc_value, exc_traceback): + SkipWritingToConfig.skip = self.previous + + def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer): sd_model_hash = checkpoint_info.calculate_shorthash() timer.record("calculate hash") - shared.opts.data["sd_model_checkpoint"] = checkpoint_info.title + if not SkipWritingToConfig.skip: + shared.opts.data["sd_model_checkpoint"] = checkpoint_info.title if state_dict is None: state_dict = get_checkpoint_state_dict(checkpoint_info, timer) diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index 39586b40..3f3e83e3 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -2,7 +2,7 @@ from collections import namedtuple import numpy as np import torch from PIL import Image -from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared +from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models from modules.shared import opts, state SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options']) @@ -127,3 +127,20 @@ def replace_torchsde_browinan(): replace_torchsde_browinan() + + +def apply_refiner(sampler): + completed_ratio = sampler.step / sampler.steps + if completed_ratio > shared.opts.sd_refiner_switch_at and shared.sd_model.sd_checkpoint_info.title != shared.opts.sd_refiner_checkpoint: + refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(shared.opts.sd_refiner_checkpoint) + if refiner_checkpoint_info is None: + raise Exception(f'Could not find checkpoint with name {shared.opts.sd_refiner_checkpoint}') + + with sd_models.SkipWritingToConfig(): + sd_models.reload_model_weights(info=refiner_checkpoint_info) + + devices.torch_gc() + + sampler.update_inner_model() + + sampler.p.setup_conds() diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py index 4a8396f9..5df926d3 100644 --- a/modules/sd_samplers_compvis.py +++ b/modules/sd_samplers_compvis.py @@ -19,7 +19,8 @@ samplers_data_compvis = [ class VanillaStableDiffusionSampler: def __init__(self, constructor, sd_model): - self.sampler = constructor(sd_model) + self.p = None + self.sampler = constructor(shared.sd_model) self.is_ddim = hasattr(self.sampler, 'p_sample_ddim') self.is_plms = hasattr(self.sampler, 'p_sample_plms') self.is_unipc = isinstance(self.sampler, modules.models.diffusion.uni_pc.UniPCSampler) @@ -32,6 +33,7 @@ class VanillaStableDiffusionSampler: self.nmask = None self.init_latent = None self.sampler_noises = None + self.steps = None self.step = 0 self.stop_at = None self.eta = None @@ -44,6 +46,7 @@ class VanillaStableDiffusionSampler: return 0 def launch_sampling(self, steps, func): + self.steps = steps state.sampling_steps = steps state.sampling_step = 0 @@ -61,10 +64,15 @@ class VanillaStableDiffusionSampler: return res + def update_inner_model(self): + self.sampler.model = shared.sd_model + def before_sample(self, x, ts, cond, unconditional_conditioning): if state.interrupted or state.skipped: raise sd_samplers_common.InterruptedException + sd_samplers_common.apply_refiner(self) + if self.stop_at is not None and self.step > self.stop_at: raise sd_samplers_common.InterruptedException @@ -134,6 +142,8 @@ class VanillaStableDiffusionSampler: self.update_step(x) def initialize(self, p): + self.p = p + if self.is_ddim: self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim else: diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index db71a549..be1bd35e 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -2,7 +2,7 @@ from collections import deque import torch import inspect import k_diffusion.sampling -from modules import prompt_parser, devices, sd_samplers_common, sd_samplers_extra +from modules import prompt_parser, devices, sd_samplers_common, sd_samplers_extra, sd_models from modules.processing import StableDiffusionProcessing from modules.shared import opts, state @@ -87,15 +87,25 @@ class CFGDenoiser(torch.nn.Module): negative prompt. """ - def __init__(self, model): + def __init__(self): super().__init__() - self.inner_model = model + self.model_wrap = None self.mask = None self.nmask = None self.init_latent = None + self.steps = None self.step = 0 self.image_cfg_scale = None self.padded_cond_uncond = False + self.p = None + + @property + def inner_model(self): + if self.model_wrap is None: + denoiser = k_diffusion.external.CompVisVDenoiser if shared.sd_model.parameterization == "v" else k_diffusion.external.CompVisDenoiser + self.model_wrap = denoiser(shared.sd_model, quantize=shared.opts.enable_quantization) + + return self.model_wrap def combine_denoised(self, x_out, conds_list, uncond, cond_scale): denoised_uncond = x_out[-uncond.shape[0]:] @@ -113,10 +123,15 @@ class CFGDenoiser(torch.nn.Module): return denoised + def update_inner_model(self): + self.model_wrap = None + def forward(self, x, sigma, uncond, cond, cond_scale, s_min_uncond, image_cond): if state.interrupted or state.skipped: raise sd_samplers_common.InterruptedException + sd_samplers_common.apply_refiner(self) + # at self.image_cfg_scale == 1.0 produced results for edit model are the same as with normal sampling, # so is_edit_model is set to False to support AND composition. is_edit_model = shared.sd_model.cond_stage_key == "edit" and self.image_cfg_scale is not None and self.image_cfg_scale != 1.0 @@ -267,13 +282,13 @@ class TorchHijack: class KDiffusionSampler: def __init__(self, funcname, sd_model): - denoiser = k_diffusion.external.CompVisVDenoiser if sd_model.parameterization == "v" else k_diffusion.external.CompVisDenoiser - self.model_wrap = denoiser(sd_model, quantize=shared.opts.enable_quantization) + self.p = None self.funcname = funcname self.func = funcname if callable(funcname) else getattr(k_diffusion.sampling, self.funcname) self.extra_params = sampler_extra_params.get(funcname, []) - self.model_wrap_cfg = CFGDenoiser(self.model_wrap) + self.model_wrap_cfg = CFGDenoiser() + self.model_wrap = self.model_wrap_cfg.inner_model self.sampler_noises = None self.stop_at = None self.eta = None @@ -305,6 +320,7 @@ class KDiffusionSampler: shared.total_tqdm.update() def launch_sampling(self, steps, func): + self.model_wrap_cfg.steps = steps state.sampling_steps = steps state.sampling_step = 0 @@ -324,6 +340,8 @@ class KDiffusionSampler: return p.steps def initialize(self, p: StableDiffusionProcessing): + self.p = p + self.model_wrap_cfg.p = p self.model_wrap_cfg.mask = p.mask if hasattr(p, 'mask') else None self.model_wrap_cfg.nmask = p.nmask if hasattr(p, 'nmask') else None self.model_wrap_cfg.step = 0 diff --git a/modules/shared.py b/modules/shared.py index 078e8135..ed8395dc 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -461,6 +461,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), + "sd_refiner_checkpoint": OptionInfo(None, "Refiner checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints).info("switch to another model in the middle of generation"), + "sd_refiner_switch_at": OptionInfo(1.0, "Refiner switch at", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}).info("fraction of sampling steps when the swtch to refiner model should happen; 1=never, 0.5=switch in the middle of generation"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { -- cgit v1.2.3 From c96e4750d895a47290dc7f96e030197069c75fa4 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 7 Aug 2023 08:07:09 +0300 Subject: SD VAE rework 2 - the setting for preferring opts.sd_vae has been inverted and reworded - resolve_vae function made easier to read and now returns an object rather than a tuple - if the checkbox for overriding per-model preferences is checked, opts.sd_vae overrides checkpoint user metadata - changing VAE in user metadata for currently loaded model immediately applies the selection --- modules/sd_models.py | 2 +- modules/sd_vae.py | 71 +++++++++++++++++----- modules/shared.py | 6 +- .../ui_extra_networks_checkpoints_user_metadata.py | 8 ++- webui.py | 2 +- 5 files changed, 69 insertions(+), 20 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index f6051604..d65735e3 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -356,7 +356,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer sd_vae.delete_base_vae() sd_vae.clear_loaded_vae() - vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename) + vae_file, vae_source = sd_vae.resolve_vae(checkpoint_info.filename).tuple() sd_vae.load_vae(model, vae_file, vae_source) timer.record("load VAE") diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 0bd5e19b..38bcb840 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -1,5 +1,7 @@ import os import collections +from dataclasses import dataclass + from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks import glob from copy import deepcopy @@ -97,37 +99,74 @@ def find_vae_near_checkpoint(checkpoint_file): return None -def resolve_vae(checkpoint_file): - if shared.cmd_opts.vae_path is not None: - return shared.cmd_opts.vae_path, 'from commandline argument' +@dataclass +class VaeResolution: + vae: str = None + source: str = None + resolved: bool = True + + def tuple(self): + return self.vae, self.source + + +def is_automatic(): + return shared.opts.sd_vae in {"Automatic", "auto"} # "auto" for people with old config + + +def resolve_vae_from_setting() -> VaeResolution: + if shared.opts.sd_vae == "None": + return VaeResolution() + + vae_from_options = vae_dict.get(shared.opts.sd_vae, None) + if vae_from_options is not None: + return VaeResolution(vae_from_options, 'specified in settings') + + if not is_automatic(): + print(f"Couldn't find VAE named {shared.opts.sd_vae}; using None instead") + return VaeResolution(resolved=False) + + +def resolve_vae_from_user_metadata(checkpoint_file) -> VaeResolution: metadata = extra_networks.get_user_metadata(checkpoint_file) vae_metadata = metadata.get("vae", None) if vae_metadata is not None and vae_metadata != "Automatic": if vae_metadata == "None": - return None, None + return VaeResolution() vae_from_metadata = vae_dict.get(vae_metadata, None) if vae_from_metadata is not None: - return vae_from_metadata, "from user metadata" + return VaeResolution(vae_from_metadata, "from user metadata") + + return VaeResolution(resolved=False) - is_automatic = shared.opts.sd_vae in {"Automatic", "auto"} # "auto" for people with old config +def resolve_vae_near_checkpoint(checkpoint_file) -> VaeResolution: vae_near_checkpoint = find_vae_near_checkpoint(checkpoint_file) if vae_near_checkpoint is not None and (shared.opts.sd_vae_as_default or is_automatic): - return vae_near_checkpoint, 'found near the checkpoint' + return VaeResolution(vae_near_checkpoint, 'found near the checkpoint') - if shared.opts.sd_vae == "None": - return None, None + return VaeResolution(resolved=False) - vae_from_options = vae_dict.get(shared.opts.sd_vae, None) - if vae_from_options is not None: - return vae_from_options, 'specified in settings' - if not is_automatic: - print(f"Couldn't find VAE named {shared.opts.sd_vae}; using None instead") +def resolve_vae(checkpoint_file) -> VaeResolution: + if shared.cmd_opts.vae_path is not None: + return VaeResolution(shared.cmd_opts.vae_path, 'from commandline argument') + + if shared.opts.sd_vae_overrides_per_model_preferences and not is_automatic(): + return resolve_vae_from_setting() + + res = resolve_vae_from_user_metadata(checkpoint_file) + if res.resolved: + return res + + res = resolve_vae_near_checkpoint(checkpoint_file) + if res.resolved: + return res + + res = resolve_vae_from_setting() - return None, None + return res def load_vae_dict(filename, map_location): @@ -201,7 +240,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): checkpoint_file = checkpoint_info.filename if vae_file == unspecified: - vae_file, vae_source = resolve_vae(checkpoint_file) + vae_file, vae_source = resolve_vae(checkpoint_file).tuple() else: vae_source = "from function argument" diff --git a/modules/shared.py b/modules/shared.py index 078e8135..da53f2d9 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -479,7 +479,7 @@ For img2img, VAE is used to process user's input image before the sampling, and """), "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), - "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"), + "sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"), "auto_vae_precision": OptionInfo(True, "Automaticlly revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"), @@ -733,6 +733,10 @@ class Options: with open(filename, "r", encoding="utf8") as file: self.data = json.load(file) + # 1.6.0 VAE defaults + if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: + self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') + # 1.1.1 quicksettings list migration if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] diff --git a/modules/ui_extra_networks_checkpoints_user_metadata.py b/modules/ui_extra_networks_checkpoints_user_metadata.py index 2c69aab8..25df0a80 100644 --- a/modules/ui_extra_networks_checkpoints_user_metadata.py +++ b/modules/ui_extra_networks_checkpoints_user_metadata.py @@ -1,6 +1,6 @@ import gradio as gr -from modules import ui_extra_networks_user_metadata, sd_vae +from modules import ui_extra_networks_user_metadata, sd_vae, shared from modules.ui_common import create_refresh_button @@ -18,6 +18,10 @@ class CheckpointUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataE self.write_user_metadata(name, user_metadata) + def update_vae(self, name): + if name == shared.sd_model.sd_checkpoint_info.name_for_extra: + sd_vae.reload_vae_weights() + def put_values_into_components(self, name): user_metadata = self.get_user_metadata(name) values = super().put_values_into_components(name) @@ -58,3 +62,5 @@ class CheckpointUserMetadataEditor(ui_extra_networks_user_metadata.UserMetadataE ] self.setup_save_handler(self.button_save, self.save_user_metadata, edited_components) + self.button_save.click(fn=self.update_vae, inputs=[self.edit_name_input]) + diff --git a/webui.py b/webui.py index 1803ea8a..a5b11575 100644 --- a/webui.py +++ b/webui.py @@ -211,7 +211,7 @@ def configure_sigint_handler(): def configure_opts_onchange(): shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()), call=False) shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) - shared.opts.onchange("sd_vae_as_default", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) + shared.opts.onchange("sd_vae_overrides_per_model_preferences", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False) shared.opts.onchange("temp_dir", ui_tempdir.on_tmpdir_changed) shared.opts.onchange("gradio_theme", shared.reload_gradio_theme) shared.opts.onchange("cross_attention_optimization", wrap_queued_call(lambda: modules.sd_hijack.model_hijack.redo_hijack(shared.sd_model)), call=False) -- cgit v1.2.3 From 6e7828e1d271c644840047c3db60e669a232402a Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 7 Aug 2023 08:16:20 +0300 Subject: apply unet overrides after switching model --- modules/sd_models.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index d65735e3..53c1df54 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -699,6 +699,7 @@ def reload_model_weights(sd_model=None, info=None): print(f"Weights loaded in {timer.summary()}.") model_data.set_sd_model(sd_model) + sd_unet.apply_unet() return sd_model -- cgit v1.2.3 From 8c200c21564992b7af1d2d692524051158e533db Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Tue, 8 Aug 2023 10:48:03 +0900 Subject: Fix mismatch between shared.sd_model & shared.opts --- modules/sd_models.py | 2 ++ 1 file changed, 2 insertions(+) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 53c1df54..cded27d4 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -623,6 +623,8 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): timer.record("send model to device") model_data.set_sd_model(already_loaded) + 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()}") return model_data.sd_model elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit: -- cgit v1.2.3 From 386245a26427a64f364f66f6fecd03b3bccfd7f3 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 10:25:35 +0300 Subject: split shared.py into multiple files; should resolve all circular reference import errors related to shared.py --- modules/devices.py | 10 +- modules/extensions.py | 4 +- modules/generation_parameters_copypaste.py | 3 +- modules/images.py | 28 +- modules/localization.py | 3 +- modules/mac_specific.py | 4 +- modules/options.py | 236 +++++++ modules/rng.py | 3 +- modules/sd_models.py | 9 +- modules/sd_models_config.py | 3 +- modules/sd_vae.py | 5 +- modules/shared.py | 961 ++--------------------------- modules/shared_cmd_options.py | 18 + modules/shared_gradio_themes.py | 66 ++ modules/shared_init.py | 51 ++ modules/shared_items.py | 49 ++ modules/shared_options.py | 692 +-------------------- modules/shared_state.py | 159 +++++ modules/shared_total_tqdm.py | 37 ++ modules/sysinfo.py | 7 +- modules/ui.py | 6 +- modules/ui_common.py | 4 +- modules/util.py | 58 ++ webui.py | 11 +- 24 files changed, 762 insertions(+), 1665 deletions(-) create mode 100644 modules/options.py create mode 100644 modules/shared_cmd_options.py create mode 100644 modules/shared_gradio_themes.py create mode 100644 modules/shared_init.py create mode 100644 modules/shared_state.py create mode 100644 modules/shared_total_tqdm.py create mode 100644 modules/util.py (limited to 'modules/sd_models.py') diff --git a/modules/devices.py b/modules/devices.py index ce59dc53..c01f0602 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -3,7 +3,7 @@ import contextlib from functools import lru_cache import torch -from modules import errors +from modules import errors, shared if sys.platform == "darwin": from modules import mac_specific @@ -17,8 +17,6 @@ def has_mps() -> bool: def get_cuda_device_string(): - from modules import shared - if shared.cmd_opts.device_id is not None: return f"cuda:{shared.cmd_opts.device_id}" @@ -40,8 +38,6 @@ def get_optimal_device(): def get_device_for(task): - from modules import shared - if task in shared.cmd_opts.use_cpu: return cpu @@ -97,8 +93,6 @@ nv_rng = None def autocast(disable=False): - from modules import shared - if disable: return contextlib.nullcontext() @@ -117,8 +111,6 @@ class NansException(Exception): def test_for_nans(x, where): - from modules import shared - if shared.cmd_opts.disable_nan_check: return diff --git a/modules/extensions.py b/modules/extensions.py index e4633af4..bf9a1878 100644 --- a/modules/extensions.py +++ b/modules/extensions.py @@ -1,7 +1,7 @@ import os import threading -from modules import shared, errors, cache +from modules import shared, errors, cache, scripts from modules.gitpython_hack import Repo from modules.paths_internal import extensions_dir, extensions_builtin_dir, script_path # noqa: F401 @@ -90,8 +90,6 @@ class Extension: self.have_info_from_repo = True def list_files(self, subdir, extension): - from modules import scripts - dirpath = os.path.join(self.path, subdir) if not os.path.isdir(dirpath): return [] diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 5758e6f3..d932c67d 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -6,7 +6,7 @@ import re import gradio as gr from modules.paths import data_path -from modules import shared, ui_tempdir, script_callbacks +from modules import shared, ui_tempdir, script_callbacks, processing from PIL import Image re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)' @@ -198,7 +198,6 @@ def restore_old_hires_fix_params(res): height = int(res.get("Size-2", 512)) if firstpass_width == 0 or firstpass_height == 0: - from modules import processing firstpass_width, firstpass_height = processing.old_hires_fix_first_pass_dimensions(width, height) res['Size-1'] = firstpass_width diff --git a/modules/images.py b/modules/images.py index ba3c43a4..019c1d60 100644 --- a/modules/images.py +++ b/modules/images.py @@ -21,8 +21,6 @@ from modules import sd_samplers, shared, script_callbacks, errors from modules.paths_internal import roboto_ttf_file from modules.shared import opts -import modules.sd_vae as sd_vae - LANCZOS = (Image.Resampling.LANCZOS if hasattr(Image, 'Resampling') else Image.LANCZOS) @@ -342,16 +340,6 @@ def sanitize_filename_part(text, replace_spaces=True): class FilenameGenerator: - def get_vae_filename(self): #get the name of the VAE file. - if sd_vae.loaded_vae_file is None: - return "NoneType" - file_name = os.path.basename(sd_vae.loaded_vae_file) - split_file_name = file_name.split('.') - if len(split_file_name) > 1 and split_file_name[0] == '': - return split_file_name[1] # if the first character of the filename is "." then [1] is obtained. - else: - return split_file_name[0] - replacements = { 'seed': lambda self: self.seed if self.seed is not None else '', 'seed_first': lambda self: self.seed if self.p.batch_size == 1 else self.p.all_seeds[0], @@ -391,6 +379,22 @@ class FilenameGenerator: self.image = image self.zip = zip + def get_vae_filename(self): + """Get the name of the VAE file.""" + + import modules.sd_vae as sd_vae + + if sd_vae.loaded_vae_file is None: + return "NoneType" + + file_name = os.path.basename(sd_vae.loaded_vae_file) + split_file_name = file_name.split('.') + if len(split_file_name) > 1 and split_file_name[0] == '': + return split_file_name[1] # if the first character of the filename is "." then [1] is obtained. + else: + return split_file_name[0] + + def hasprompt(self, *args): lower = self.prompt.lower() if self.p is None or self.prompt is None: diff --git a/modules/localization.py b/modules/localization.py index e8f585da..c1320288 100644 --- a/modules/localization.py +++ b/modules/localization.py @@ -1,7 +1,7 @@ import json import os -from modules import errors +from modules import errors, scripts localizations = {} @@ -16,7 +16,6 @@ def list_localizations(dirname): localizations[fn] = os.path.join(dirname, file) - from modules import scripts for file in scripts.list_scripts("localizations", ".json"): fn, ext = os.path.splitext(file.filename) localizations[fn] = file.path diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 9ceb43ba..bce527cc 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -4,6 +4,7 @@ import torch import platform from modules.sd_hijack_utils import CondFunc from packaging import version +from modules import shared log = logging.getLogger(__name__) @@ -30,8 +31,7 @@ has_mps = check_for_mps() def torch_mps_gc() -> None: try: - from modules.shared import state - if state.current_latent is not None: + if shared.state.current_latent is not None: log.debug("`current_latent` is set, skipping MPS garbage collection") return from torch.mps import empty_cache diff --git a/modules/options.py b/modules/options.py new file mode 100644 index 00000000..59cb75ec --- /dev/null +++ b/modules/options.py @@ -0,0 +1,236 @@ +import json +import sys + +import gradio as gr + +from modules import errors +from modules.shared_cmd_options import cmd_opts + + +class OptionInfo: + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): + self.default = default + self.label = label + self.component = component + self.component_args = component_args + self.onchange = onchange + self.section = section + self.refresh = refresh + self.do_not_save = False + + self.comment_before = comment_before + """HTML text that will be added after label in UI""" + + self.comment_after = comment_after + """HTML text that will be added before label in UI""" + + def link(self, label, url): + self.comment_before += f"[{label}]" + return self + + def js(self, label, js_func): + self.comment_before += f"[{label}]" + return self + + def info(self, info): + self.comment_after += f"({info})" + return self + + def html(self, html): + self.comment_after += html + return self + + def needs_restart(self): + self.comment_after += " (requires restart)" + return self + + def needs_reload_ui(self): + self.comment_after += " (requires Reload UI)" + return self + + +class OptionHTML(OptionInfo): + def __init__(self, text): + super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs)) + + self.do_not_save = True + + +def options_section(section_identifier, options_dict): + for v in options_dict.values(): + v.section = section_identifier + + return options_dict + + +options_builtin_fields = {"data_labels", "data", "restricted_opts", "typemap"} + + +class Options: + typemap = {int: float} + + def __init__(self, data_labels, restricted_opts): + self.data_labels = data_labels + self.data = {k: v.default for k, v in self.data_labels.items()} + self.restricted_opts = restricted_opts + + def __setattr__(self, key, value): + if key in options_builtin_fields: + return super(Options, self).__setattr__(key, value) + + if self.data is not None: + if key in self.data or key in self.data_labels: + assert not cmd_opts.freeze_settings, "changing settings is disabled" + + info = self.data_labels.get(key, None) + if info.do_not_save: + return + + comp_args = info.component_args if info else None + if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: + raise RuntimeError(f"not possible to set {key} because it is restricted") + + if cmd_opts.hide_ui_dir_config and key in self.restricted_opts: + raise RuntimeError(f"not possible to set {key} because it is restricted") + + self.data[key] = value + return + + return super(Options, self).__setattr__(key, value) + + def __getattr__(self, item): + if item in options_builtin_fields: + return super(Options, self).__getattribute__(item) + + if self.data is not None: + if item in self.data: + return self.data[item] + + if item in self.data_labels: + return self.data_labels[item].default + + return super(Options, self).__getattribute__(item) + + def set(self, key, value): + """sets an option and calls its onchange callback, returning True if the option changed and False otherwise""" + + oldval = self.data.get(key, None) + if oldval == value: + return False + + if self.data_labels[key].do_not_save: + return False + + try: + setattr(self, key, value) + except RuntimeError: + return False + + if self.data_labels[key].onchange is not None: + try: + self.data_labels[key].onchange() + except Exception as e: + errors.display(e, f"changing setting {key} to {value}") + setattr(self, key, oldval) + return False + + return True + + def get_default(self, key): + """returns the default value for the key""" + + data_label = self.data_labels.get(key) + if data_label is None: + return None + + return data_label.default + + def save(self, filename): + assert not cmd_opts.freeze_settings, "saving settings is disabled" + + with open(filename, "w", encoding="utf8") as file: + json.dump(self.data, file, indent=4) + + def same_type(self, x, y): + if x is None or y is None: + return True + + type_x = self.typemap.get(type(x), type(x)) + type_y = self.typemap.get(type(y), type(y)) + + return type_x == type_y + + def load(self, filename): + with open(filename, "r", encoding="utf8") as file: + self.data = json.load(file) + + # 1.6.0 VAE defaults + if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: + self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') + + # 1.1.1 quicksettings list migration + if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: + self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] + + # 1.4.0 ui_reorder + if isinstance(self.data.get('ui_reorder'), str) and self.data.get('ui_reorder') and "ui_reorder_list" not in self.data: + self.data['ui_reorder_list'] = [i.strip() for i in self.data.get('ui_reorder').split(',')] + + bad_settings = 0 + for k, v in self.data.items(): + info = self.data_labels.get(k, None) + if info is not None and not self.same_type(info.default, v): + print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr) + bad_settings += 1 + + if bad_settings > 0: + print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr) + + def onchange(self, key, func, call=True): + item = self.data_labels.get(key) + item.onchange = func + + if call: + func() + + def dumpjson(self): + d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} + d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} + d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} + return json.dumps(d) + + def add_option(self, key, info): + self.data_labels[key] = info + + def reorder(self): + """reorder settings so that all items related to section always go together""" + + section_ids = {} + settings_items = self.data_labels.items() + for _, item in settings_items: + if item.section not in section_ids: + section_ids[item.section] = len(section_ids) + + self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) + + def cast_value(self, key, value): + """casts an arbitrary to the same type as this setting's value with key + Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str) + """ + + if value is None: + return None + + default_value = self.data_labels[key].default + if default_value is None: + default_value = getattr(self, key, None) + if default_value is None: + return None + + expected_type = type(default_value) + if expected_type == bool and value == "False": + value = False + else: + value = expected_type(value) + + return value diff --git a/modules/rng.py b/modules/rng.py index 2d7baea5..f927a318 100644 --- a/modules/rng.py +++ b/modules/rng.py @@ -63,9 +63,8 @@ def randn_without_seed(shape, generator=None): def manual_seed(seed): """Set up a global random number generator using the specified seed.""" - from modules.shared import opts - if opts.randn_source == "NV": + if shared.opts.randn_source == "NV": global nv_rng nv_rng = rng_philox.Generator(seed) return diff --git a/modules/sd_models.py b/modules/sd_models.py index 53c1df54..88a09899 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -14,7 +14,7 @@ import ldm.modules.midas as midas from ldm.util import instantiate_from_config -from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache +from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache, extra_networks, processing, lowvram, sd_hijack from modules.timer import Timer import tomesd @@ -473,7 +473,6 @@ model_data = SdModelData() def get_empty_cond(sd_model): - from modules import extra_networks, processing p = processing.StableDiffusionProcessingTxt2Img() extra_networks.activate(p, {}) @@ -486,8 +485,6 @@ def get_empty_cond(sd_model): def send_model_to_cpu(m): - from modules import lowvram - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: lowvram.send_everything_to_cpu() else: @@ -497,8 +494,6 @@ def send_model_to_cpu(m): def send_model_to_device(m): - from modules import lowvram - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) else: @@ -642,7 +637,6 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): def reload_model_weights(sd_model=None, info=None): - from modules import devices, sd_hijack checkpoint_info = info or select_checkpoint() timer = Timer() @@ -705,7 +699,6 @@ def reload_model_weights(sd_model=None, info=None): def unload_model_weights(sd_model=None, info=None): - from modules import devices, sd_hijack timer = Timer() if model_data.sd_model: diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py index 8266fa39..08dd03f1 100644 --- a/modules/sd_models_config.py +++ b/modules/sd_models_config.py @@ -2,7 +2,7 @@ import os import torch -from modules import shared, paths, sd_disable_initialization +from modules import shared, paths, sd_disable_initialization, devices sd_configs_path = shared.sd_configs_path sd_repo_configs_path = os.path.join(paths.paths['Stable Diffusion'], "configs", "stable-diffusion") @@ -29,7 +29,6 @@ def is_using_v_parameterization_for_sd2(state_dict): """ import ldm.modules.diffusionmodules.openaimodel - from modules import devices device = devices.cpu diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 38bcb840..5ac1ac31 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -2,7 +2,8 @@ import os import collections from dataclasses import dataclass -from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks +from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks, lowvram, sd_hijack + import glob from copy import deepcopy @@ -231,8 +232,6 @@ unspecified = object() def reload_vae_weights(sd_model=None, vae_file=unspecified): - from modules import lowvram, devices, sd_hijack - if not sd_model: sd_model = shared.sd_model diff --git a/modules/shared.py b/modules/shared.py index e9b980a4..8ba72f49 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -1,843 +1,51 @@ -import datetime -import json -import os -import re import sys -import threading -import time -import logging import gradio as gr -import torch -import tqdm -import launch -import modules.interrogate -import modules.memmon -import modules.styles -import modules.devices as devices -from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args, rng # noqa: F401 +from modules import shared_cmd_options, shared_gradio_themes, options, shared_items from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 from ldm.models.diffusion.ddpm import LatentDiffusion -from typing import Optional +from modules import util -log = logging.getLogger(__name__) - -demo = None - -parser = cmd_args.parser - -script_loading.preload_extensions(extensions_dir, parser, extension_list=launch.list_extensions(launch.args.ui_settings_file)) -script_loading.preload_extensions(extensions_builtin_dir, parser) - -if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None: - cmd_opts = parser.parse_args() -else: - cmd_opts, _ = parser.parse_known_args() - - -restricted_opts = { - "samples_filename_pattern", - "directories_filename_pattern", - "outdir_samples", - "outdir_txt2img_samples", - "outdir_img2img_samples", - "outdir_extras_samples", - "outdir_grids", - "outdir_txt2img_grids", - "outdir_save", - "outdir_init_images" -} - -# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json -gradio_hf_hub_themes = [ - "gradio/base", - "gradio/glass", - "gradio/monochrome", - "gradio/seafoam", - "gradio/soft", - "gradio/dracula_test", - "abidlabs/dracula_test", - "abidlabs/Lime", - "abidlabs/pakistan", - "Ama434/neutral-barlow", - "dawood/microsoft_windows", - "finlaymacklon/smooth_slate", - "Franklisi/darkmode", - "freddyaboulton/dracula_revamped", - "freddyaboulton/test-blue", - "gstaff/xkcd", - "Insuz/Mocha", - "Insuz/SimpleIndigo", - "JohnSmith9982/small_and_pretty", - "nota-ai/theme", - "nuttea/Softblue", - "ParityError/Anime", - "reilnuud/polite", - "remilia/Ghostly", - "rottenlittlecreature/Moon_Goblin", - "step-3-profit/Midnight-Deep", - "Taithrah/Minimal", - "ysharma/huggingface", - "ysharma/steampunk" -] - - -cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access - -devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \ - (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer']) - -devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 -devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 - -device = devices.device -weight_load_location = None if cmd_opts.lowram else "cpu" +cmd_opts = shared_cmd_options.cmd_opts +parser = shared_cmd_options.parser batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram) parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram -xformers_available = False -config_filename = cmd_opts.ui_settings_file - -os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) -hypernetworks = {} -loaded_hypernetworks = [] - - -def reload_hypernetworks(): - from modules.hypernetworks import hypernetwork - global hypernetworks - - hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) - - -class State: - skipped = False - interrupted = False - job = "" - job_no = 0 - job_count = 0 - processing_has_refined_job_count = False - job_timestamp = '0' - sampling_step = 0 - sampling_steps = 0 - current_latent = None - current_image = None - current_image_sampling_step = 0 - id_live_preview = 0 - textinfo = None - time_start = None - server_start = None - _server_command_signal = threading.Event() - _server_command: Optional[str] = None - - @property - def need_restart(self) -> bool: - # Compatibility getter for need_restart. - return self.server_command == "restart" - - @need_restart.setter - def need_restart(self, value: bool) -> None: - # Compatibility setter for need_restart. - if value: - self.server_command = "restart" - - @property - def server_command(self): - return self._server_command - - @server_command.setter - def server_command(self, value: Optional[str]) -> None: - """ - Set the server command to `value` and signal that it's been set. - """ - self._server_command = value - self._server_command_signal.set() - - def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]: - """ - Wait for server command to get set; return and clear the value and signal. - """ - if self._server_command_signal.wait(timeout): - self._server_command_signal.clear() - req = self._server_command - self._server_command = None - return req - return None - - def request_restart(self) -> None: - self.interrupt() - self.server_command = "restart" - log.info("Received restart request") - - def skip(self): - self.skipped = True - log.info("Received skip request") - - def interrupt(self): - self.interrupted = True - log.info("Received interrupt request") - - def nextjob(self): - if opts.live_previews_enable and opts.show_progress_every_n_steps == -1: - self.do_set_current_image() - - self.job_no += 1 - self.sampling_step = 0 - self.current_image_sampling_step = 0 - - def dict(self): - obj = { - "skipped": self.skipped, - "interrupted": self.interrupted, - "job": self.job, - "job_count": self.job_count, - "job_timestamp": self.job_timestamp, - "job_no": self.job_no, - "sampling_step": self.sampling_step, - "sampling_steps": self.sampling_steps, - } - - return obj - - def begin(self, job: str = "(unknown)"): - self.sampling_step = 0 - self.job_count = -1 - self.processing_has_refined_job_count = False - self.job_no = 0 - self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") - self.current_latent = None - self.current_image = None - self.current_image_sampling_step = 0 - self.id_live_preview = 0 - self.skipped = False - self.interrupted = False - self.textinfo = None - self.time_start = time.time() - self.job = job - devices.torch_gc() - log.info("Starting job %s", job) - - def end(self): - duration = time.time() - self.time_start - log.info("Ending job %s (%.2f seconds)", self.job, duration) - self.job = "" - self.job_count = 0 - - devices.torch_gc() - - def set_current_image(self): - """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" - if not parallel_processing_allowed: - return - - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.live_previews_enable and opts.show_progress_every_n_steps != -1: - self.do_set_current_image() - - def do_set_current_image(self): - if self.current_latent is None: - return - - import modules.sd_samplers - - try: - if opts.show_progress_grid: - self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) - else: - self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) - - self.current_image_sampling_step = self.sampling_step - - except Exception: - # when switching models during genration, VAE would be on CPU, so creating an image will fail. - # we silently ignore this error - errors.record_exception() - - def assign_current_image(self, image): - self.current_image = image - self.id_live_preview += 1 - - -state = State() -state.server_start = time.time() - styles_filename = cmd_opts.styles_file -prompt_styles = modules.styles.StyleDatabase(styles_filename) - -interrogator = modules.interrogate.InterrogateModels("interrogate") - -face_restorers = [] - - -class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): - self.default = default - self.label = label - self.component = component - self.component_args = component_args - self.onchange = onchange - self.section = section - self.refresh = refresh - self.do_not_save = False - - self.comment_before = comment_before - """HTML text that will be added after label in UI""" - - self.comment_after = comment_after - """HTML text that will be added before label in UI""" - - def link(self, label, url): - self.comment_before += f"[{label}]" - return self - - def js(self, label, js_func): - self.comment_before += f"[{label}]" - return self - - def info(self, info): - self.comment_after += f"({info})" - return self - - def html(self, html): - self.comment_after += html - return self - - def needs_restart(self): - self.comment_after += " (requires restart)" - return self - - def needs_reload_ui(self): - self.comment_after += " (requires Reload UI)" - return self - - -class OptionHTML(OptionInfo): - def __init__(self, text): - super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs)) - - self.do_not_save = True - - -def options_section(section_identifier, options_dict): - for v in options_dict.values(): - v.section = section_identifier - - return options_dict - - -def list_checkpoint_tiles(): - import modules.sd_models - return modules.sd_models.checkpoint_tiles() - - -def refresh_checkpoints(): - import modules.sd_models - return modules.sd_models.list_models() - - -def list_samplers(): - import modules.sd_samplers - return modules.sd_samplers.all_samplers - - +config_filename = cmd_opts.ui_settings_file hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} -tab_names = [] - -options_templates = {} - -options_templates.update(options_section(('saving-images', "Saving images/grids"), { - "samples_save": OptionInfo(True, "Always save all generated images"), - "samples_format": OptionInfo('png', 'File format for images'), - "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), - "save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs), - - "grid_save": OptionInfo(True, "Always save all generated image grids"), - "grid_format": OptionInfo('png', 'File format for grids'), - "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"), - "grid_only_if_multiple": OptionInfo(True, "Do not save grids consisting of one picture"), - "grid_prevent_empty_spots": OptionInfo(False, "Prevent empty spots in grid (when set to autodetect)"), - "grid_zip_filename_pattern": OptionInfo("", "Archive filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), - "n_rows": OptionInfo(-1, "Grid row count; use -1 for autodetect and 0 for it to be same as batch size", gr.Slider, {"minimum": -1, "maximum": 16, "step": 1}), - "font": OptionInfo("", "Font for image grids that have text"), - "grid_text_active_color": OptionInfo("#000000", "Text color for image grids", ui_components.FormColorPicker, {}), - "grid_text_inactive_color": OptionInfo("#999999", "Inactive text color for image grids", ui_components.FormColorPicker, {}), - "grid_background_color": OptionInfo("#ffffff", "Background color for image grids", ui_components.FormColorPicker, {}), - - "enable_pnginfo": OptionInfo(True, "Save text information about generation parameters as chunks to png files"), - "save_txt": OptionInfo(False, "Create a text file next to every image with generation parameters."), - "save_images_before_face_restoration": OptionInfo(False, "Save a copy of image before doing face restoration."), - "save_images_before_highres_fix": OptionInfo(False, "Save a copy of image before applying highres fix."), - "save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"), - "save_mask": OptionInfo(False, "For inpainting, save a copy of the greyscale mask"), - "save_mask_composite": OptionInfo(False, "For inpainting, save a masked composite"), - "jpeg_quality": OptionInfo(80, "Quality for saved jpeg images", gr.Slider, {"minimum": 1, "maximum": 100, "step": 1}), - "webp_lossless": OptionInfo(False, "Use lossless compression for webp images"), - "export_for_4chan": OptionInfo(True, "Save copy of large images as JPG").info("if the file size is above the limit, or either width or height are above the limit"), - "img_downscale_threshold": OptionInfo(4.0, "File size limit for the above option, MB", gr.Number), - "target_side_length": OptionInfo(4000, "Width/height limit for the above option, in pixels", gr.Number), - "img_max_size_mp": OptionInfo(200, "Maximum image size", gr.Number).info("in megapixels"), - - "use_original_name_batch": OptionInfo(True, "Use original name for output filename during batch process in extras tab"), - "use_upscaler_name_as_suffix": OptionInfo(False, "Use upscaler name as filename suffix in the extras tab"), - "save_selected_only": OptionInfo(True, "When using 'Save' button, only save a single selected image"), - "save_init_img": OptionInfo(False, "Save init images when using img2img"), - - "temp_dir": OptionInfo("", "Directory for temporary images; leave empty for default"), - "clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"), - - "save_incomplete_images": OptionInfo(False, "Save incomplete images").info("save images that has been interrupted in mid-generation; even if not saved, they will still show up in webui output."), -})) - -options_templates.update(options_section(('saving-paths', "Paths for saving"), { - "outdir_samples": OptionInfo("", "Output directory for images; if empty, defaults to three directories below", component_args=hide_dirs), - "outdir_txt2img_samples": OptionInfo("outputs/txt2img-images", 'Output directory for txt2img images', component_args=hide_dirs), - "outdir_img2img_samples": OptionInfo("outputs/img2img-images", 'Output directory for img2img images', component_args=hide_dirs), - "outdir_extras_samples": OptionInfo("outputs/extras-images", 'Output directory for images from extras tab', component_args=hide_dirs), - "outdir_grids": OptionInfo("", "Output directory for grids; if empty, defaults to two directories below", component_args=hide_dirs), - "outdir_txt2img_grids": OptionInfo("outputs/txt2img-grids", 'Output directory for txt2img grids', component_args=hide_dirs), - "outdir_img2img_grids": OptionInfo("outputs/img2img-grids", 'Output directory for img2img grids', component_args=hide_dirs), - "outdir_save": OptionInfo("log/images", "Directory for saving images using the Save button", component_args=hide_dirs), - "outdir_init_images": OptionInfo("outputs/init-images", "Directory for saving init images when using img2img", component_args=hide_dirs), -})) - -options_templates.update(options_section(('saving-to-dirs', "Saving to a directory"), { - "save_to_dirs": OptionInfo(True, "Save images to a subdirectory"), - "grid_save_to_dirs": OptionInfo(True, "Save grids to a subdirectory"), - "use_save_to_dirs_for_ui": OptionInfo(False, "When using \"Save\" button, save images to a subdirectory"), - "directories_filename_pattern": OptionInfo("[date]", "Directory name pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"), - "directories_max_prompt_words": OptionInfo(8, "Max prompt words for [prompt_words] pattern", gr.Slider, {"minimum": 1, "maximum": 20, "step": 1, **hide_dirs}), -})) - -options_templates.update(options_section(('upscaling', "Upscaling"), { - "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"), - "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"), - "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), - "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), -})) - -options_templates.update(options_section(('face-restoration', "Face restoration"), { - "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), - "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), - "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), -})) - -options_templates.update(options_section(('system', "System"), { - "auto_launch_browser": OptionInfo("Local", "Automatically open webui in browser on startup", gr.Radio, lambda: {"choices": ["Disable", "Local", "Remote"]}), - "show_warnings": OptionInfo(False, "Show warnings in console.").needs_reload_ui(), - "show_gradio_deprecation_warnings": OptionInfo(True, "Show gradio deprecation warnings in console.").needs_reload_ui(), - "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}).info("0 = disable"), - "samples_log_stdout": OptionInfo(False, "Always print all generation info to standard output"), - "multiple_tqdm": OptionInfo(True, "Add a second progress bar to the console that shows progress for an entire job."), - "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console."), - "list_hidden_files": OptionInfo(True, "Load models/files in hidden directories").info("directory is hidden if its name starts with \".\""), - "disable_mmap_load_safetensors": OptionInfo(False, "Disable memmapping for loading .safetensors files.").info("fixes very slow loading speed in some cases"), - "hide_ldm_prints": OptionInfo(True, "Prevent Stability-AI's ldm/sgm modules from printing noise to console."), -})) - -options_templates.update(options_section(('training', "Training"), { - "unload_models_when_training": OptionInfo(False, "Move VAE and CLIP to RAM when training if possible. Saves VRAM."), - "pin_memory": OptionInfo(False, "Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."), - "save_optimizer_state": OptionInfo(False, "Saves Optimizer state as separate *.optim file. Training of embedding or HN can be resumed with the matching optim file."), - "save_training_settings_to_txt": OptionInfo(True, "Save textual inversion and hypernet settings to a text file whenever training starts."), - "dataset_filename_word_regex": OptionInfo("", "Filename word regex"), - "dataset_filename_join_string": OptionInfo(" ", "Filename join string"), - "training_image_repeats_per_epoch": OptionInfo(1, "Number of repeats for a single input image per epoch; used only for displaying epoch number", gr.Number, {"precision": 0}), - "training_write_csv_every": OptionInfo(500, "Save an csv containing the loss to log directory every N steps, 0 to disable"), - "training_xattention_optimizations": OptionInfo(False, "Use cross attention optimizations while training"), - "training_enable_tensorboard": OptionInfo(False, "Enable tensorboard logging."), - "training_tensorboard_save_images": OptionInfo(False, "Save generated images within tensorboard."), - "training_tensorboard_flush_every": OptionInfo(120, "How often, in seconds, to flush the pending tensorboard events and summaries to disk."), -})) - -options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), - "sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}), - "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"), - "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"), - "sd_unet": OptionInfo("Automatic", "SD Unet", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list).info("choose Unet model: Automatic = use one with same filename as checkpoint; None = use Unet from checkpoint"), - "enable_quantization": OptionInfo(False, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds").needs_reload_ui(), - "enable_emphasis": OptionInfo(True, "Enable emphasis").info("use (text) to make model pay more attention to text and [text] to make it pay less attention"), - "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image"), - "comma_padding_backtrack": OptionInfo(20, "Prompt word wrap length limit", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1}).info("in tokens - for texts shorter than specified, if they don't fit into 75 token limit, move them to the next 75 token chunk"), - "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"), - "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), - "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), -})) - -options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { - "sdxl_crop_top": OptionInfo(0, "crop top coordinate"), - "sdxl_crop_left": OptionInfo(0, "crop left coordinate"), - "sdxl_refiner_low_aesthetic_score": OptionInfo(2.5, "SDXL low aesthetic score", gr.Number).info("used for refiner model negative prompt"), - "sdxl_refiner_high_aesthetic_score": OptionInfo(6.0, "SDXL high aesthetic score", gr.Number).info("used for refiner model prompt"), -})) -options_templates.update(options_section(('vae', "VAE"), { - "sd_vae_explanation": OptionHTML(""" -VAE is a neural network that transforms a standard RGB -image into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling -(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished. -For img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling. -"""), - "sd_vae_checkpoint_cache": OptionInfo(0, "VAE Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), - "sd_vae": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list).info("choose VAE model: Automatic = use one with same filename as checkpoint; None = use VAE from checkpoint"), - "sd_vae_overrides_per_model_preferences": OptionInfo(True, "Selected VAE overrides per-model preferences").info("you can set per-model VAE either by editing user metadata for checkpoints, or by making the VAE have same name as checkpoint"), - "auto_vae_precision": OptionInfo(True, "Automatically revert VAE to 32-bit floats").info("triggers when a tensor with NaNs is produced in VAE; disabling the option in this case will result in a black square image"), - "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to encode image to latent (use in img2img, hires-fix or inpaint mask)"), - "sd_vae_decode_method": OptionInfo("Full", "VAE type for decode", gr.Radio, {"choices": ["Full", "TAESD"]}).info("method to decode latent to image"), -})) - -options_templates.update(options_section(('img2img', "img2img"), { - "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), - "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}), - "img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."), - "img2img_fix_steps": OptionInfo(False, "With img2img, do exactly the amount of steps the slider specifies.").info("normally you'd do less with less denoising"), - "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill transparent parts of the input image with this color.", ui_components.FormColorPicker, {}), - "img2img_editor_height": OptionInfo(720, "Height of the image editor", gr.Slider, {"minimum": 80, "maximum": 1600, "step": 1}).info("in pixels").needs_reload_ui(), - "img2img_sketch_default_brush_color": OptionInfo("#ffffff", "Sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img sketch").needs_reload_ui(), - "img2img_inpaint_mask_brush_color": OptionInfo("#ffffff", "Inpaint mask brush color", ui_components.FormColorPicker, {}).info("brush color of inpaint mask").needs_reload_ui(), - "img2img_inpaint_sketch_default_brush_color": OptionInfo("#ffffff", "Inpaint sketch initial brush color", ui_components.FormColorPicker, {}).info("default brush color of img2img inpaint sketch").needs_reload_ui(), - "return_mask": OptionInfo(False, "For inpainting, include the greyscale mask in results for web"), - "return_mask_composite": OptionInfo(False, "For inpainting, include masked composite in results for web"), -})) - -options_templates.update(options_section(('optimizations', "Optimizations"), { - "cross_attention_optimization": OptionInfo("Automatic", "Cross attention optimization", gr.Dropdown, lambda: {"choices": shared_items.cross_attention_optimizations()}), - "s_min_uncond": OptionInfo(0.0, "Negative Guidance minimum sigma", gr.Slider, {"minimum": 0.0, "maximum": 15.0, "step": 0.01}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9177").info("skip negative prompt for some steps when the image is almost ready; 0=disable, higher=faster"), - "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"), - "token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"), - "token_merging_ratio_hr": OptionInfo(0.0, "Token merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"), - "pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length").info("improves performance when prompt and negative prompt have different lengths; changes seeds"), - "persistent_cond_cache": OptionInfo(True, "Persistent cond cache").info("Do not recalculate conds from prompts if prompts have not changed since previous calculation"), -})) - -options_templates.update(options_section(('compatibility', "Compatibility"), { - "use_old_emphasis_implementation": OptionInfo(False, "Use old emphasis implementation. Can be useful to reproduce old seeds."), - "use_old_karras_scheduler_sigmas": OptionInfo(False, "Use old karras scheduler sigmas (0.1 to 10)."), - "no_dpmpp_sde_batch_determinism": OptionInfo(False, "Do not make DPM++ SDE deterministic across different batch sizes."), - "use_old_hires_fix_width_height": OptionInfo(False, "For hires fix, use width/height sliders to set final resolution rather than first pass (disables Upscale by, Resize width/height to)."), - "dont_fix_second_order_samplers_schedule": OptionInfo(False, "Do not fix prompt schedule for second order samplers."), - "hires_fix_use_firstpass_conds": OptionInfo(False, "For hires fix, calculate conds of second pass using extra networks of first pass."), -})) - -options_templates.update(options_section(('interrogate', "Interrogate"), { - "interrogate_keep_models_in_memory": OptionInfo(False, "Keep models in VRAM"), - "interrogate_return_ranks": OptionInfo(False, "Include ranks of model tags matches in results.").info("booru only"), - "interrogate_clip_num_beams": OptionInfo(1, "BLIP: num_beams", gr.Slider, {"minimum": 1, "maximum": 16, "step": 1}), - "interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), - "interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), - "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"), - "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types), - "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), - "deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"), - "deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"), - "deepbooru_escape": OptionInfo(True, "deepbooru: escape (\\) brackets").info("so they are used as literal brackets and not for emphasis"), - "deepbooru_filter_tags": OptionInfo("", "deepbooru: filter out those tags").info("separate by comma"), -})) - -options_templates.update(options_section(('extra_networks', "Extra Networks"), { - "extra_networks_show_hidden_directories": OptionInfo(True, "Show hidden directories").info("directory is hidden if its name starts with \".\"."), - "extra_networks_hidden_models": OptionInfo("When searched", "Show cards for models in hidden directories", gr.Radio, {"choices": ["Always", "When searched", "Never"]}).info('"When searched" option will only show the item when the search string has 4 characters or more'), - "extra_networks_default_multiplier": OptionInfo(1.0, "Default multiplier for extra networks", gr.Slider, {"minimum": 0.0, "maximum": 2.0, "step": 0.01}), - "extra_networks_card_width": OptionInfo(0, "Card width for Extra Networks").info("in pixels"), - "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks").info("in pixels"), - "extra_networks_card_text_scale": OptionInfo(1.0, "Card text scale", gr.Slider, {"minimum": 0.0, "maximum": 2.0, "step": 0.01}).info("1 = original size"), - "extra_networks_card_show_desc": OptionInfo(True, "Show description on card"), - "extra_networks_add_text_separator": OptionInfo(" ", "Extra networks separator").info("extra text to add before <...> when adding extra network to prompt"), - "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_reload_ui(), - "textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"), - "textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), -})) - -options_templates.update(options_section(('ui', "User interface"), { - "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_reload_ui(), - "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).info("you can also manually enter any of themes from the gallery.").needs_reload_ui(), - "gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"), - "return_grid": OptionInfo(True, "Show grid in results for web"), - "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), - "send_seed": OptionInfo(True, "Send seed when sending prompt or image to other interface"), - "send_size": OptionInfo(True, "Send size when sending prompt or image to another interface"), - "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer"), - "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer"), - "js_modal_lightbox_gamepad": OptionInfo(False, "Navigate image viewer with gamepad"), - "js_modal_lightbox_gamepad_repeat": OptionInfo(250, "Gamepad repeat period, in milliseconds"), - "show_progress_in_title": OptionInfo(True, "Show generation progress in window title."), - "samplers_in_dropdown": OptionInfo(True, "Use dropdown for sampler selection instead of radio group").needs_reload_ui(), - "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_reload_ui(), - "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), - "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), - "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), - "keyedit_move": OptionInfo(True, "Alt+left/right moves prompt elements"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(), - "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), - "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), - "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_reload_ui(), - "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_reload_ui(), - "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_reload_ui(), - "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_reload_ui(), -})) - - -options_templates.update(options_section(('infotext', "Infotext"), { - "add_model_hash_to_info": OptionInfo(True, "Add model hash to generation information"), - "add_model_name_to_info": OptionInfo(True, "Add model name to generation information"), - "add_user_name_to_info": OptionInfo(False, "Add user name to generation information when authenticated"), - "add_version_to_infotext": OptionInfo(True, "Add program version to generation information"), - "disable_weights_auto_swap": OptionInfo(True, "Disregard checkpoint information from pasted infotext").info("when reading generation parameters from text into UI"), - "infotext_styles": OptionInfo("Apply if any", "Infer styles from prompts of pasted infotext", gr.Radio, {"choices": ["Ignore", "Apply", "Discard", "Apply if any"]}).info("when reading generation parameters from text into UI)").html("""
    -
  • Ignore: keep prompt and styles dropdown as it is.
    • -
  • Apply: remove style text from prompt, always replace styles dropdown value with found styles (even if none are found).
    • -
  • Discard: remove style text from prompt, keep styles dropdown as it is.
    • -
  • Apply if any: remove style text from prompt; if any styles are found in prompt, put them into styles dropdown, otherwise keep it as it is.
    • -
"""), - -})) - -options_templates.update(options_section(('ui', "Live previews"), { - "show_progressbar": OptionInfo(True, "Show progressbar"), - "live_previews_enable": OptionInfo(True, "Show live previews of the created image"), - "live_previews_image_format": OptionInfo("png", "Live preview file format", gr.Radio, {"choices": ["jpeg", "png", "webp"]}), - "show_progress_grid": OptionInfo(True, "Show previews of all images generated in a batch as a grid"), - "show_progress_every_n_steps": OptionInfo(10, "Live preview display period", gr.Slider, {"minimum": -1, "maximum": 32, "step": 1}).info("in sampling steps - show new live preview image every N sampling steps; -1 = only show after completion of batch"), - "show_progress_type": OptionInfo("Approx NN", "Live preview method", gr.Radio, {"choices": ["Full", "Approx NN", "Approx cheap", "TAESD"]}).info("Full = slow but pretty; Approx NN and TAESD = fast but low quality; Approx cheap = super fast but terrible otherwise"), - "live_preview_content": OptionInfo("Prompt", "Live preview subject", gr.Radio, {"choices": ["Combined", "Prompt", "Negative prompt"]}), - "live_preview_refresh_period": OptionInfo(1000, "Progressbar and preview update period").info("in milliseconds"), -})) - -options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}).needs_reload_ui(), - "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), - "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), - "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), - 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}).info('amount of stochasticity; only applies to Euler, Heun, and DPM2'), - 's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 10.0, "step": 0.01}).info('enable stochasticity; start value of the sigma range; only applies to Euler, Heun, and DPM2'), - 's_tmax': OptionInfo(0.0, "sigma tmax", gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}).info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"), - 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}).info('amount of additional noise to counteract loss of detail during sampling; only applies to Euler, Heun, and DPM2'), - 'k_sched_type': OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}).info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"), - 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"), - 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"), - 'rho': OptionInfo(0.0, "rho", gr.Number).info("0 = default (7 for karras, 1 for polyexponential); higher values result in a steeper noise schedule (decreases faster)"), - 'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"), - 'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"), - 'uni_pc_variant': OptionInfo("bh1", "UniPC variant", gr.Radio, {"choices": ["bh1", "bh2", "vary_coeff"]}), - 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}), - 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}).info("must be < sampling steps"), - 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final"), -})) - -options_templates.update(options_section(('postprocessing', "Postprocessing"), { - 'postprocessing_enable_in_main_ui': OptionInfo([], "Enable postprocessing operations in txt2img and img2img tabs", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}), - 'postprocessing_operation_order': OptionInfo([], "Postprocessing operation order", ui_components.DropdownMulti, lambda: {"choices": [x.name for x in shared_items.postprocessing_scripts()]}), - 'upscaling_max_images_in_cache': OptionInfo(5, "Maximum number of images in upscaling cache", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}), -})) - -options_templates.update(options_section((None, "Hidden options"), { - "disabled_extensions": OptionInfo([], "Disable these extensions"), - "disable_all_extensions": OptionInfo("none", "Disable all extensions (preserves the list of disabled extensions)", gr.Radio, {"choices": ["none", "extra", "all"]}), - "restore_config_state_file": OptionInfo("", "Config state file to restore from, under 'config-states/' folder"), - "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), -})) - - -options_templates.update() - - -class Options: - data = None - data_labels = options_templates - typemap = {int: float} - - def __init__(self): - self.data = {k: v.default for k, v in self.data_labels.items()} - - def __setattr__(self, key, value): - if self.data is not None: - if key in self.data or key in self.data_labels: - assert not cmd_opts.freeze_settings, "changing settings is disabled" - - info = opts.data_labels.get(key, None) - if info.do_not_save: - return - - comp_args = info.component_args if info else None - if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - if cmd_opts.hide_ui_dir_config and key in restricted_opts: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - self.data[key] = value - return - - return super(Options, self).__setattr__(key, value) - - def __getattr__(self, item): - if self.data is not None: - if item in self.data: - return self.data[item] - - if item in self.data_labels: - return self.data_labels[item].default - - return super(Options, self).__getattribute__(item) - - def set(self, key, value): - """sets an option and calls its onchange callback, returning True if the option changed and False otherwise""" - - oldval = self.data.get(key, None) - if oldval == value: - return False - - if self.data_labels[key].do_not_save: - return False - - try: - setattr(self, key, value) - except RuntimeError: - return False - - if self.data_labels[key].onchange is not None: - try: - self.data_labels[key].onchange() - except Exception as e: - errors.display(e, f"changing setting {key} to {value}") - setattr(self, key, oldval) - return False - - return True - - def get_default(self, key): - """returns the default value for the key""" - - data_label = self.data_labels.get(key) - if data_label is None: - return None - - return data_label.default - - def save(self, filename): - assert not cmd_opts.freeze_settings, "saving settings is disabled" - - with open(filename, "w", encoding="utf8") as file: - json.dump(self.data, file, indent=4) - - def same_type(self, x, y): - if x is None or y is None: - return True - - type_x = self.typemap.get(type(x), type(x)) - type_y = self.typemap.get(type(y), type(y)) - - return type_x == type_y - - def load(self, filename): - with open(filename, "r", encoding="utf8") as file: - self.data = json.load(file) - - # 1.6.0 VAE defaults - if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: - self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') - - # 1.1.1 quicksettings list migration - if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: - self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] - - # 1.4.0 ui_reorder - if isinstance(self.data.get('ui_reorder'), str) and self.data.get('ui_reorder') and "ui_reorder_list" not in self.data: - self.data['ui_reorder_list'] = [i.strip() for i in self.data.get('ui_reorder').split(',')] - - bad_settings = 0 - for k, v in self.data.items(): - info = self.data_labels.get(k, None) - if info is not None and not self.same_type(info.default, v): - print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr) - bad_settings += 1 - - if bad_settings > 0: - print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr) - - def onchange(self, key, func, call=True): - item = self.data_labels.get(key) - item.onchange = func - - if call: - func() - - def dumpjson(self): - d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} - d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} - d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} - return json.dumps(d) - - def add_option(self, key, info): - self.data_labels[key] = info - - def reorder(self): - """reorder settings so that all items related to section always go together""" - - section_ids = {} - settings_items = self.data_labels.items() - for _, item in settings_items: - if item.section not in section_ids: - section_ids[item.section] = len(section_ids) - - self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) - - def cast_value(self, key, value): - """casts an arbitrary to the same type as this setting's value with key - Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str) - """ - - if value is None: - return None - - default_value = self.data_labels[key].default - if default_value is None: - default_value = getattr(self, key, None) - if default_value is None: - return None - - expected_type = type(default_value) - if expected_type == bool and value == "False": - value = False - else: - value = expected_type(value) - - return value +demo = None +device = None -opts = Options() -if os.path.exists(config_filename): - opts.load(config_filename) +weight_load_location = None +xformers_available = False -class Shared(sys.modules[__name__].__class__): - """ - this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than - at program startup. - """ +hypernetworks = {} - sd_model_val = None +loaded_hypernetworks = [] - @property - def sd_model(self): - import modules.sd_models +state = None - return modules.sd_models.model_data.get_sd_model() +prompt_styles = None - @sd_model.setter - def sd_model(self, value): - import modules.sd_models +interrogator = None - modules.sd_models.model_data.set_sd_model(value) +face_restorers = [] +options_templates = None +opts = None -sd_model: LatentDiffusion = None # this var is here just for IDE's type checking; it cannot be accessed because the class field above will be accessed instead -sys.modules[__name__].__class__ = Shared +sd_model: LatentDiffusion = None settings_components = None """assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings""" +tab_names = [] + latent_upscale_default_mode = "Latent" latent_upscale_modes = { "Latent": {"mode": "bilinear", "antialias": False}, @@ -856,121 +64,24 @@ progress_print_out = sys.stdout gradio_theme = gr.themes.Base() +total_tqdm = None -def reload_gradio_theme(theme_name=None): - global gradio_theme - if not theme_name: - theme_name = opts.gradio_theme - - default_theme_args = dict( - font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], - font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], - ) - - if theme_name == "Default": - gradio_theme = gr.themes.Default(**default_theme_args) - else: - try: - theme_cache_dir = os.path.join(script_path, 'tmp', 'gradio_themes') - theme_cache_path = os.path.join(theme_cache_dir, f'{theme_name.replace("/", "_")}.json') - if opts.gradio_themes_cache and os.path.exists(theme_cache_path): - gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) - else: - os.makedirs(theme_cache_dir, exist_ok=True) - gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) - gradio_theme.dump(theme_cache_path) - except Exception as e: - errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default(**default_theme_args) - - -class TotalTQDM: - def __init__(self): - self._tqdm = None - - def reset(self): - self._tqdm = tqdm.tqdm( - desc="Total progress", - total=state.job_count * state.sampling_steps, - position=1, - file=progress_print_out - ) - - def update(self): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.update() - - def updateTotal(self, new_total): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.total = new_total - - def clear(self): - if self._tqdm is not None: - self._tqdm.refresh() - self._tqdm.close() - self._tqdm = None - - -total_tqdm = TotalTQDM() - -mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts) -mem_mon.start() - - -def natural_sort_key(s, regex=re.compile('([0-9]+)')): - return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)] - - -def listfiles(dirname): - filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=natural_sort_key) if not x.startswith(".")] - return [file for file in filenames if os.path.isfile(file)] - - -def html_path(filename): - return os.path.join(script_path, "html", filename) - - -def html(filename): - path = html_path(filename) - - if os.path.exists(path): - with open(path, encoding="utf8") as file: - return file.read() - - return "" - - -def walk_files(path, allowed_extensions=None): - if not os.path.exists(path): - return - - if allowed_extensions is not None: - allowed_extensions = set(allowed_extensions) - - items = list(os.walk(path, followlinks=True)) - items = sorted(items, key=lambda x: natural_sort_key(x[0])) - - for root, _, files in items: - for filename in sorted(files, key=natural_sort_key): - if allowed_extensions is not None: - _, ext = os.path.splitext(filename) - if ext not in allowed_extensions: - continue - - if not opts.list_hidden_files and ("/." in root or "\\." in root): - continue +mem_mon = None - yield os.path.join(root, filename) +options_section = options.options_section +OptionInfo = options.OptionInfo +OptionHTML = options.OptionHTML +natural_sort_key = util.natural_sort_key +listfiles = util.listfiles +html_path = util.html_path +html = util.html +walk_files = util.walk_files +ldm_print = util.ldm_print -def ldm_print(*args, **kwargs): - if opts.hide_ldm_prints: - return +reload_gradio_theme = shared_gradio_themes.reload_gradio_theme - print(*args, **kwargs) +list_checkpoint_tiles = shared_items.list_checkpoint_tiles +refresh_checkpoints = shared_items.refresh_checkpoints +list_samplers = shared_items.list_samplers +reload_hypernetworks = shared_items.reload_hypernetworks diff --git a/modules/shared_cmd_options.py b/modules/shared_cmd_options.py new file mode 100644 index 00000000..af24938b --- /dev/null +++ b/modules/shared_cmd_options.py @@ -0,0 +1,18 @@ +import os + +import launch +from modules import cmd_args, script_loading +from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 + +parser = cmd_args.parser + +script_loading.preload_extensions(extensions_dir, parser, extension_list=launch.list_extensions(launch.args.ui_settings_file)) +script_loading.preload_extensions(extensions_builtin_dir, parser) + +if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None: + cmd_opts = parser.parse_args() +else: + cmd_opts, _ = parser.parse_known_args() + + +cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access diff --git a/modules/shared_gradio_themes.py b/modules/shared_gradio_themes.py new file mode 100644 index 00000000..ad1f2212 --- /dev/null +++ b/modules/shared_gradio_themes.py @@ -0,0 +1,66 @@ +import os + +import gradio as gr + +from modules import errors, shared +from modules.paths_internal import script_path + + +# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json +gradio_hf_hub_themes = [ + "gradio/base", + "gradio/glass", + "gradio/monochrome", + "gradio/seafoam", + "gradio/soft", + "gradio/dracula_test", + "abidlabs/dracula_test", + "abidlabs/Lime", + "abidlabs/pakistan", + "Ama434/neutral-barlow", + "dawood/microsoft_windows", + "finlaymacklon/smooth_slate", + "Franklisi/darkmode", + "freddyaboulton/dracula_revamped", + "freddyaboulton/test-blue", + "gstaff/xkcd", + "Insuz/Mocha", + "Insuz/SimpleIndigo", + "JohnSmith9982/small_and_pretty", + "nota-ai/theme", + "nuttea/Softblue", + "ParityError/Anime", + "reilnuud/polite", + "remilia/Ghostly", + "rottenlittlecreature/Moon_Goblin", + "step-3-profit/Midnight-Deep", + "Taithrah/Minimal", + "ysharma/huggingface", + "ysharma/steampunk" +] + + +def reload_gradio_theme(theme_name=None): + if not theme_name: + theme_name = shared.opts.gradio_theme + + default_theme_args = dict( + font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], + font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], + ) + + if theme_name == "Default": + shared.gradio_theme = gr.themes.Default(**default_theme_args) + else: + try: + theme_cache_dir = os.path.join(script_path, 'tmp', 'gradio_themes') + theme_cache_path = os.path.join(theme_cache_dir, f'{theme_name.replace("/", "_")}.json') + if shared.opts.gradio_themes_cache and os.path.exists(theme_cache_path): + shared.gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) + else: + os.makedirs(theme_cache_dir, exist_ok=True) + gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) + gradio_theme.dump(theme_cache_path) + except Exception as e: + errors.display(e, "changing gradio theme") + shared.gradio_theme = gr.themes.Default(**default_theme_args) diff --git a/modules/shared_init.py b/modules/shared_init.py new file mode 100644 index 00000000..e7fc18d2 --- /dev/null +++ b/modules/shared_init.py @@ -0,0 +1,51 @@ +import os + +import torch + +from modules import shared +from modules.shared import cmd_opts + +import sys +sys.setrecursionlimit(1000) + + +def initialize(): + """Initializes fields inside the shared module in a controlled manner. + + Should be called early because some other modules you can import mingt need these fields to be already set. + """ + + os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) + + from modules import options, shared_options + shared.options_templates = shared_options.options_templates + shared.opts = options.Options(shared_options.options_templates, shared_options.restricted_opts) + if os.path.exists(shared.config_filename): + shared.opts.load(shared.config_filename) + + from modules import devices + devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \ + (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer']) + + devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 + devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 + + shared.device = devices.device + shared.weight_load_location = None if cmd_opts.lowram else "cpu" + + from modules import shared_state + shared.state = shared_state.State() + + from modules import styles + shared.prompt_styles = styles.StyleDatabase(shared.styles_filename) + + from modules import interrogate + shared.interrogator = interrogate.InterrogateModels("interrogate") + + from modules import shared_total_tqdm + shared.total_tqdm = shared_total_tqdm.TotalTQDM() + + from modules import memmon, devices + shared.mem_mon = memmon.MemUsageMonitor("MemMon", devices.device, shared.opts) + shared.mem_mon.start() + diff --git a/modules/shared_items.py b/modules/shared_items.py index 89792e88..e4ec40a8 100644 --- a/modules/shared_items.py +++ b/modules/shared_items.py @@ -1,3 +1,6 @@ +import sys + +from modules.shared_cmd_options import cmd_opts def realesrgan_models_names(): @@ -41,6 +44,28 @@ def refresh_unet_list(): modules.sd_unet.list_unets() +def list_checkpoint_tiles(): + import modules.sd_models + return modules.sd_models.checkpoint_tiles() + + +def refresh_checkpoints(): + import modules.sd_models + return modules.sd_models.list_models() + + +def list_samplers(): + import modules.sd_samplers + return modules.sd_samplers.all_samplers + + +def reload_hypernetworks(): + from modules.hypernetworks import hypernetwork + from modules import shared + + shared.hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) + + ui_reorder_categories_builtin_items = [ "inpaint", "sampler", @@ -67,3 +92,27 @@ def ui_reorder_categories(): yield from sections yield "scripts" + + +class Shared(sys.modules[__name__].__class__): + """ + this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than + at program startup. + """ + + sd_model_val = None + + @property + def sd_model(self): + import modules.sd_models + + return modules.sd_models.model_data.get_sd_model() + + @sd_model.setter + def sd_model(self, value): + import modules.sd_models + + modules.sd_models.model_data.set_sd_model(value) + + +sys.modules['modules.shared'].__class__ = Shared diff --git a/modules/shared_options.py b/modules/shared_options.py index e9b980a4..7468bc81 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -1,40 +1,12 @@ -import datetime -import json -import os -import re -import sys -import threading -import time -import logging - import gradio as gr -import torch -import tqdm - -import launch -import modules.interrogate -import modules.memmon -import modules.styles -import modules.devices as devices -from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args, rng # noqa: F401 -from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 -from ldm.models.diffusion.ddpm import LatentDiffusion -from typing import Optional - -log = logging.getLogger(__name__) - -demo = None - -parser = cmd_args.parser -script_loading.preload_extensions(extensions_dir, parser, extension_list=launch.list_extensions(launch.args.ui_settings_file)) -script_loading.preload_extensions(extensions_builtin_dir, parser) - -if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None: - cmd_opts = parser.parse_args() -else: - cmd_opts, _ = parser.parse_known_args() +from modules import localization, ui_components, shared_items, shared, interrogate, shared_gradio_themes +from modules.paths_internal import models_path, script_path, data_path, sd_configs_path, sd_default_config, sd_model_file, default_sd_model_file, extensions_dir, extensions_builtin_dir # noqa: F401 +from modules.shared_cmd_options import cmd_opts +from modules.options import options_section, OptionInfo, OptionHTML +options_templates = {} +hide_dirs = shared.hide_dirs restricted_opts = { "samples_filename_pattern", @@ -49,302 +21,6 @@ restricted_opts = { "outdir_init_images" } -# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json -gradio_hf_hub_themes = [ - "gradio/base", - "gradio/glass", - "gradio/monochrome", - "gradio/seafoam", - "gradio/soft", - "gradio/dracula_test", - "abidlabs/dracula_test", - "abidlabs/Lime", - "abidlabs/pakistan", - "Ama434/neutral-barlow", - "dawood/microsoft_windows", - "finlaymacklon/smooth_slate", - "Franklisi/darkmode", - "freddyaboulton/dracula_revamped", - "freddyaboulton/test-blue", - "gstaff/xkcd", - "Insuz/Mocha", - "Insuz/SimpleIndigo", - "JohnSmith9982/small_and_pretty", - "nota-ai/theme", - "nuttea/Softblue", - "ParityError/Anime", - "reilnuud/polite", - "remilia/Ghostly", - "rottenlittlecreature/Moon_Goblin", - "step-3-profit/Midnight-Deep", - "Taithrah/Minimal", - "ysharma/huggingface", - "ysharma/steampunk" -] - - -cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure_extension_access - -devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \ - (devices.cpu if any(y in cmd_opts.use_cpu for y in [x, 'all']) else devices.get_optimal_device() for x in ['sd', 'interrogate', 'gfpgan', 'esrgan', 'codeformer']) - -devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16 -devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16 - -device = devices.device -weight_load_location = None if cmd_opts.lowram else "cpu" - -batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram) -parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram -xformers_available = False -config_filename = cmd_opts.ui_settings_file - -os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True) -hypernetworks = {} -loaded_hypernetworks = [] - - -def reload_hypernetworks(): - from modules.hypernetworks import hypernetwork - global hypernetworks - - hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir) - - -class State: - skipped = False - interrupted = False - job = "" - job_no = 0 - job_count = 0 - processing_has_refined_job_count = False - job_timestamp = '0' - sampling_step = 0 - sampling_steps = 0 - current_latent = None - current_image = None - current_image_sampling_step = 0 - id_live_preview = 0 - textinfo = None - time_start = None - server_start = None - _server_command_signal = threading.Event() - _server_command: Optional[str] = None - - @property - def need_restart(self) -> bool: - # Compatibility getter for need_restart. - return self.server_command == "restart" - - @need_restart.setter - def need_restart(self, value: bool) -> None: - # Compatibility setter for need_restart. - if value: - self.server_command = "restart" - - @property - def server_command(self): - return self._server_command - - @server_command.setter - def server_command(self, value: Optional[str]) -> None: - """ - Set the server command to `value` and signal that it's been set. - """ - self._server_command = value - self._server_command_signal.set() - - def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]: - """ - Wait for server command to get set; return and clear the value and signal. - """ - if self._server_command_signal.wait(timeout): - self._server_command_signal.clear() - req = self._server_command - self._server_command = None - return req - return None - - def request_restart(self) -> None: - self.interrupt() - self.server_command = "restart" - log.info("Received restart request") - - def skip(self): - self.skipped = True - log.info("Received skip request") - - def interrupt(self): - self.interrupted = True - log.info("Received interrupt request") - - def nextjob(self): - if opts.live_previews_enable and opts.show_progress_every_n_steps == -1: - self.do_set_current_image() - - self.job_no += 1 - self.sampling_step = 0 - self.current_image_sampling_step = 0 - - def dict(self): - obj = { - "skipped": self.skipped, - "interrupted": self.interrupted, - "job": self.job, - "job_count": self.job_count, - "job_timestamp": self.job_timestamp, - "job_no": self.job_no, - "sampling_step": self.sampling_step, - "sampling_steps": self.sampling_steps, - } - - return obj - - def begin(self, job: str = "(unknown)"): - self.sampling_step = 0 - self.job_count = -1 - self.processing_has_refined_job_count = False - self.job_no = 0 - self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") - self.current_latent = None - self.current_image = None - self.current_image_sampling_step = 0 - self.id_live_preview = 0 - self.skipped = False - self.interrupted = False - self.textinfo = None - self.time_start = time.time() - self.job = job - devices.torch_gc() - log.info("Starting job %s", job) - - def end(self): - duration = time.time() - self.time_start - log.info("Ending job %s (%.2f seconds)", self.job, duration) - self.job = "" - self.job_count = 0 - - devices.torch_gc() - - def set_current_image(self): - """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" - if not parallel_processing_allowed: - return - - if self.sampling_step - self.current_image_sampling_step >= opts.show_progress_every_n_steps and opts.live_previews_enable and opts.show_progress_every_n_steps != -1: - self.do_set_current_image() - - def do_set_current_image(self): - if self.current_latent is None: - return - - import modules.sd_samplers - - try: - if opts.show_progress_grid: - self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) - else: - self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) - - self.current_image_sampling_step = self.sampling_step - - except Exception: - # when switching models during genration, VAE would be on CPU, so creating an image will fail. - # we silently ignore this error - errors.record_exception() - - def assign_current_image(self, image): - self.current_image = image - self.id_live_preview += 1 - - -state = State() -state.server_start = time.time() - -styles_filename = cmd_opts.styles_file -prompt_styles = modules.styles.StyleDatabase(styles_filename) - -interrogator = modules.interrogate.InterrogateModels("interrogate") - -face_restorers = [] - - -class OptionInfo: - def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''): - self.default = default - self.label = label - self.component = component - self.component_args = component_args - self.onchange = onchange - self.section = section - self.refresh = refresh - self.do_not_save = False - - self.comment_before = comment_before - """HTML text that will be added after label in UI""" - - self.comment_after = comment_after - """HTML text that will be added before label in UI""" - - def link(self, label, url): - self.comment_before += f"[{label}]" - return self - - def js(self, label, js_func): - self.comment_before += f"[{label}]" - return self - - def info(self, info): - self.comment_after += f"({info})" - return self - - def html(self, html): - self.comment_after += html - return self - - def needs_restart(self): - self.comment_after += " (requires restart)" - return self - - def needs_reload_ui(self): - self.comment_after += " (requires Reload UI)" - return self - - -class OptionHTML(OptionInfo): - def __init__(self, text): - super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs)) - - self.do_not_save = True - - -def options_section(section_identifier, options_dict): - for v in options_dict.values(): - v.section = section_identifier - - return options_dict - - -def list_checkpoint_tiles(): - import modules.sd_models - return modules.sd_models.checkpoint_tiles() - - -def refresh_checkpoints(): - import modules.sd_models - return modules.sd_models.list_models() - - -def list_samplers(): - import modules.sd_samplers - return modules.sd_samplers.all_samplers - - -hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} -tab_names = [] - -options_templates = {} - options_templates.update(options_section(('saving-images', "Saving images/grids"), { "samples_save": OptionInfo(True, "Always save all generated images"), "samples_format": OptionInfo('png', 'File format for images'), @@ -412,11 +88,11 @@ options_templates.update(options_section(('upscaling', "Upscaling"), { "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"), "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"), "realesrgan_enabled_models": OptionInfo(["R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"], "Select which Real-ESRGAN models to show in the web UI.", gr.CheckboxGroup, lambda: {"choices": shared_items.realesrgan_models_names()}), - "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}), + "upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in shared.sd_upscalers]}), })) options_templates.update(options_section(('face-restoration', "Face restoration"), { - "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}), + "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in shared.face_restorers]}), "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"), "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"), })) @@ -450,7 +126,7 @@ options_templates.update(options_section(('training', "Training"), { })) options_templates.update(options_section(('sd', "Stable Diffusion"), { - "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints), "sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}), "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"), "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"), @@ -526,7 +202,7 @@ options_templates.update(options_section(('interrogate', "Interrogate"), { "interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}), "interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}), "interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"), - "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types), + "interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": interrogate.category_types()}, refresh=interrogate.category_types), "interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}), "deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"), "deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"), @@ -546,12 +222,12 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), { "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_reload_ui(), "textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"), "textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"), - "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks), + "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *shared.hypernetworks]}, refresh=shared_items.reload_hypernetworks), })) options_templates.update(options_section(('ui', "User interface"), { "localization": OptionInfo("None", "Localization", gr.Dropdown, lambda: {"choices": ["None"] + list(localization.localizations.keys())}, refresh=lambda: localization.list_localizations(cmd_opts.localizations_dir)).needs_reload_ui(), - "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + gradio_hf_hub_themes}).info("you can also manually enter any of themes from the gallery.").needs_reload_ui(), + "gradio_theme": OptionInfo("Default", "Gradio theme", ui_components.DropdownEditable, lambda: {"choices": ["Default"] + shared_gradio_themes.gradio_hf_hub_themes}).info("you can also manually enter any of themes from the gallery.").needs_reload_ui(), "gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"), "return_grid": OptionInfo(True, "Show grid in results for web"), "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"), @@ -568,9 +244,9 @@ options_templates.update(options_section(('ui', "User interface"), { "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing ", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}), "keyedit_delimiters": OptionInfo(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"), "keyedit_move": OptionInfo(True, "Alt+left/right moves prompt elements"), - "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(), - "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), - "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(tab_names)}).needs_reload_ui(), + "quicksettings_list": OptionInfo(["sd_model_checkpoint"], "Quicksettings list", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that appear at the top of page rather than in settings tab").needs_reload_ui(), + "ui_tab_order": OptionInfo([], "UI tab order", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(), + "hidden_tabs": OptionInfo([], "Hidden UI tabs", ui_components.DropdownMulti, lambda: {"choices": list(shared.tab_names)}).needs_reload_ui(), "ui_reorder_list": OptionInfo([], "txt2img/img2img UI item order", ui_components.DropdownMulti, lambda: {"choices": list(shared_items.ui_reorder_categories())}).info("selected items appear first").needs_reload_ui(), "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_reload_ui(), "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_reload_ui(), @@ -605,7 +281,7 @@ options_templates.update(options_section(('ui', "Live previews"), { })) options_templates.update(options_section(('sampler-params', "Sampler parameters"), { - "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers()]}).needs_reload_ui(), + "hide_samplers": OptionInfo([], "Hide samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in shared_items.list_samplers()]}).needs_reload_ui(), "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; higher = more unperdictable results"), "eta_ancestral": OptionInfo(1.0, "Eta for ancestral samplers", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}).info("noise multiplier; applies to Euler a and other samplers that have a in them"), "ddim_discretize": OptionInfo('uniform', "img2img DDIM discretize", gr.Radio, {"choices": ['uniform', 'quad']}), @@ -638,339 +314,3 @@ options_templates.update(options_section((None, "Hidden options"), { "sd_checkpoint_hash": OptionInfo("", "SHA256 hash of the current checkpoint"), })) - -options_templates.update() - - -class Options: - data = None - data_labels = options_templates - typemap = {int: float} - - def __init__(self): - self.data = {k: v.default for k, v in self.data_labels.items()} - - def __setattr__(self, key, value): - if self.data is not None: - if key in self.data or key in self.data_labels: - assert not cmd_opts.freeze_settings, "changing settings is disabled" - - info = opts.data_labels.get(key, None) - if info.do_not_save: - return - - comp_args = info.component_args if info else None - if isinstance(comp_args, dict) and comp_args.get('visible', True) is False: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - if cmd_opts.hide_ui_dir_config and key in restricted_opts: - raise RuntimeError(f"not possible to set {key} because it is restricted") - - self.data[key] = value - return - - return super(Options, self).__setattr__(key, value) - - def __getattr__(self, item): - if self.data is not None: - if item in self.data: - return self.data[item] - - if item in self.data_labels: - return self.data_labels[item].default - - return super(Options, self).__getattribute__(item) - - def set(self, key, value): - """sets an option and calls its onchange callback, returning True if the option changed and False otherwise""" - - oldval = self.data.get(key, None) - if oldval == value: - return False - - if self.data_labels[key].do_not_save: - return False - - try: - setattr(self, key, value) - except RuntimeError: - return False - - if self.data_labels[key].onchange is not None: - try: - self.data_labels[key].onchange() - except Exception as e: - errors.display(e, f"changing setting {key} to {value}") - setattr(self, key, oldval) - return False - - return True - - def get_default(self, key): - """returns the default value for the key""" - - data_label = self.data_labels.get(key) - if data_label is None: - return None - - return data_label.default - - def save(self, filename): - assert not cmd_opts.freeze_settings, "saving settings is disabled" - - with open(filename, "w", encoding="utf8") as file: - json.dump(self.data, file, indent=4) - - def same_type(self, x, y): - if x is None or y is None: - return True - - type_x = self.typemap.get(type(x), type(x)) - type_y = self.typemap.get(type(y), type(y)) - - return type_x == type_y - - def load(self, filename): - with open(filename, "r", encoding="utf8") as file: - self.data = json.load(file) - - # 1.6.0 VAE defaults - if self.data.get('sd_vae_as_default') is not None and self.data.get('sd_vae_overrides_per_model_preferences') is None: - self.data['sd_vae_overrides_per_model_preferences'] = not self.data.get('sd_vae_as_default') - - # 1.1.1 quicksettings list migration - if self.data.get('quicksettings') is not None and self.data.get('quicksettings_list') is None: - self.data['quicksettings_list'] = [i.strip() for i in self.data.get('quicksettings').split(',')] - - # 1.4.0 ui_reorder - if isinstance(self.data.get('ui_reorder'), str) and self.data.get('ui_reorder') and "ui_reorder_list" not in self.data: - self.data['ui_reorder_list'] = [i.strip() for i in self.data.get('ui_reorder').split(',')] - - bad_settings = 0 - for k, v in self.data.items(): - info = self.data_labels.get(k, None) - if info is not None and not self.same_type(info.default, v): - print(f"Warning: bad setting value: {k}: {v} ({type(v).__name__}; expected {type(info.default).__name__})", file=sys.stderr) - bad_settings += 1 - - if bad_settings > 0: - print(f"The program is likely to not work with bad settings.\nSettings file: {filename}\nEither fix the file, or delete it and restart.", file=sys.stderr) - - def onchange(self, key, func, call=True): - item = self.data_labels.get(key) - item.onchange = func - - if call: - func() - - def dumpjson(self): - d = {k: self.data.get(k, v.default) for k, v in self.data_labels.items()} - d["_comments_before"] = {k: v.comment_before for k, v in self.data_labels.items() if v.comment_before is not None} - d["_comments_after"] = {k: v.comment_after for k, v in self.data_labels.items() if v.comment_after is not None} - return json.dumps(d) - - def add_option(self, key, info): - self.data_labels[key] = info - - def reorder(self): - """reorder settings so that all items related to section always go together""" - - section_ids = {} - settings_items = self.data_labels.items() - for _, item in settings_items: - if item.section not in section_ids: - section_ids[item.section] = len(section_ids) - - self.data_labels = dict(sorted(settings_items, key=lambda x: section_ids[x[1].section])) - - def cast_value(self, key, value): - """casts an arbitrary to the same type as this setting's value with key - Example: cast_value("eta_noise_seed_delta", "12") -> returns 12 (an int rather than str) - """ - - if value is None: - return None - - default_value = self.data_labels[key].default - if default_value is None: - default_value = getattr(self, key, None) - if default_value is None: - return None - - expected_type = type(default_value) - if expected_type == bool and value == "False": - value = False - else: - value = expected_type(value) - - return value - - -opts = Options() -if os.path.exists(config_filename): - opts.load(config_filename) - - -class Shared(sys.modules[__name__].__class__): - """ - this class is here to provide sd_model field as a property, so that it can be created and loaded on demand rather than - at program startup. - """ - - sd_model_val = None - - @property - def sd_model(self): - import modules.sd_models - - return modules.sd_models.model_data.get_sd_model() - - @sd_model.setter - def sd_model(self, value): - import modules.sd_models - - modules.sd_models.model_data.set_sd_model(value) - - -sd_model: LatentDiffusion = None # this var is here just for IDE's type checking; it cannot be accessed because the class field above will be accessed instead -sys.modules[__name__].__class__ = Shared - -settings_components = None -"""assinged from ui.py, a mapping on setting names to gradio components repsponsible for those settings""" - -latent_upscale_default_mode = "Latent" -latent_upscale_modes = { - "Latent": {"mode": "bilinear", "antialias": False}, - "Latent (antialiased)": {"mode": "bilinear", "antialias": True}, - "Latent (bicubic)": {"mode": "bicubic", "antialias": False}, - "Latent (bicubic antialiased)": {"mode": "bicubic", "antialias": True}, - "Latent (nearest)": {"mode": "nearest", "antialias": False}, - "Latent (nearest-exact)": {"mode": "nearest-exact", "antialias": False}, -} - -sd_upscalers = [] - -clip_model = None - -progress_print_out = sys.stdout - -gradio_theme = gr.themes.Base() - - -def reload_gradio_theme(theme_name=None): - global gradio_theme - if not theme_name: - theme_name = opts.gradio_theme - - default_theme_args = dict( - font=["Source Sans Pro", 'ui-sans-serif', 'system-ui', 'sans-serif'], - font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'], - ) - - if theme_name == "Default": - gradio_theme = gr.themes.Default(**default_theme_args) - else: - try: - theme_cache_dir = os.path.join(script_path, 'tmp', 'gradio_themes') - theme_cache_path = os.path.join(theme_cache_dir, f'{theme_name.replace("/", "_")}.json') - if opts.gradio_themes_cache and os.path.exists(theme_cache_path): - gradio_theme = gr.themes.ThemeClass.load(theme_cache_path) - else: - os.makedirs(theme_cache_dir, exist_ok=True) - gradio_theme = gr.themes.ThemeClass.from_hub(theme_name) - gradio_theme.dump(theme_cache_path) - except Exception as e: - errors.display(e, "changing gradio theme") - gradio_theme = gr.themes.Default(**default_theme_args) - - -class TotalTQDM: - def __init__(self): - self._tqdm = None - - def reset(self): - self._tqdm = tqdm.tqdm( - desc="Total progress", - total=state.job_count * state.sampling_steps, - position=1, - file=progress_print_out - ) - - def update(self): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.update() - - def updateTotal(self, new_total): - if not opts.multiple_tqdm or cmd_opts.disable_console_progressbars: - return - if self._tqdm is None: - self.reset() - self._tqdm.total = new_total - - def clear(self): - if self._tqdm is not None: - self._tqdm.refresh() - self._tqdm.close() - self._tqdm = None - - -total_tqdm = TotalTQDM() - -mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts) -mem_mon.start() - - -def natural_sort_key(s, regex=re.compile('([0-9]+)')): - return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)] - - -def listfiles(dirname): - filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=natural_sort_key) if not x.startswith(".")] - return [file for file in filenames if os.path.isfile(file)] - - -def html_path(filename): - return os.path.join(script_path, "html", filename) - - -def html(filename): - path = html_path(filename) - - if os.path.exists(path): - with open(path, encoding="utf8") as file: - return file.read() - - return "" - - -def walk_files(path, allowed_extensions=None): - if not os.path.exists(path): - return - - if allowed_extensions is not None: - allowed_extensions = set(allowed_extensions) - - items = list(os.walk(path, followlinks=True)) - items = sorted(items, key=lambda x: natural_sort_key(x[0])) - - for root, _, files in items: - for filename in sorted(files, key=natural_sort_key): - if allowed_extensions is not None: - _, ext = os.path.splitext(filename) - if ext not in allowed_extensions: - continue - - if not opts.list_hidden_files and ("/." in root or "\\." in root): - continue - - yield os.path.join(root, filename) - - -def ldm_print(*args, **kwargs): - if opts.hide_ldm_prints: - return - - print(*args, **kwargs) diff --git a/modules/shared_state.py b/modules/shared_state.py new file mode 100644 index 00000000..3dc9c788 --- /dev/null +++ b/modules/shared_state.py @@ -0,0 +1,159 @@ +import datetime +import logging +import threading +import time + +from modules import errors, shared, devices +from typing import Optional + +log = logging.getLogger(__name__) + + +class State: + skipped = False + interrupted = False + job = "" + job_no = 0 + job_count = 0 + processing_has_refined_job_count = False + job_timestamp = '0' + sampling_step = 0 + sampling_steps = 0 + current_latent = None + current_image = None + current_image_sampling_step = 0 + id_live_preview = 0 + textinfo = None + time_start = None + server_start = None + _server_command_signal = threading.Event() + _server_command: Optional[str] = None + + def __init__(self): + self.server_start = time.time() + + @property + def need_restart(self) -> bool: + # Compatibility getter for need_restart. + return self.server_command == "restart" + + @need_restart.setter + def need_restart(self, value: bool) -> None: + # Compatibility setter for need_restart. + if value: + self.server_command = "restart" + + @property + def server_command(self): + return self._server_command + + @server_command.setter + def server_command(self, value: Optional[str]) -> None: + """ + Set the server command to `value` and signal that it's been set. + """ + self._server_command = value + self._server_command_signal.set() + + def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]: + """ + Wait for server command to get set; return and clear the value and signal. + """ + if self._server_command_signal.wait(timeout): + self._server_command_signal.clear() + req = self._server_command + self._server_command = None + return req + return None + + def request_restart(self) -> None: + self.interrupt() + self.server_command = "restart" + log.info("Received restart request") + + def skip(self): + self.skipped = True + log.info("Received skip request") + + def interrupt(self): + self.interrupted = True + log.info("Received interrupt request") + + def nextjob(self): + if shared.opts.live_previews_enable and shared.opts.show_progress_every_n_steps == -1: + self.do_set_current_image() + + self.job_no += 1 + self.sampling_step = 0 + self.current_image_sampling_step = 0 + + def dict(self): + obj = { + "skipped": self.skipped, + "interrupted": self.interrupted, + "job": self.job, + "job_count": self.job_count, + "job_timestamp": self.job_timestamp, + "job_no": self.job_no, + "sampling_step": self.sampling_step, + "sampling_steps": self.sampling_steps, + } + + return obj + + def begin(self, job: str = "(unknown)"): + self.sampling_step = 0 + self.job_count = -1 + self.processing_has_refined_job_count = False + self.job_no = 0 + self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S") + self.current_latent = None + self.current_image = None + self.current_image_sampling_step = 0 + self.id_live_preview = 0 + self.skipped = False + self.interrupted = False + self.textinfo = None + self.time_start = time.time() + self.job = job + devices.torch_gc() + log.info("Starting job %s", job) + + def end(self): + duration = time.time() - self.time_start + log.info("Ending job %s (%.2f seconds)", self.job, duration) + self.job = "" + self.job_count = 0 + + devices.torch_gc() + + def set_current_image(self): + """sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this""" + if not shared.parallel_processing_allowed: + return + + if self.sampling_step - self.current_image_sampling_step >= shared.opts.show_progress_every_n_steps and shared.opts.live_previews_enable and shared.opts.show_progress_every_n_steps != -1: + self.do_set_current_image() + + def do_set_current_image(self): + if self.current_latent is None: + return + + import modules.sd_samplers + + try: + if shared.opts.show_progress_grid: + self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent)) + else: + self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent)) + + self.current_image_sampling_step = self.sampling_step + + except Exception: + # when switching models during genration, VAE would be on CPU, so creating an image will fail. + # we silently ignore this error + errors.record_exception() + + def assign_current_image(self, image): + self.current_image = image + self.id_live_preview += 1 diff --git a/modules/shared_total_tqdm.py b/modules/shared_total_tqdm.py new file mode 100644 index 00000000..cf82e104 --- /dev/null +++ b/modules/shared_total_tqdm.py @@ -0,0 +1,37 @@ +import tqdm + +from modules import shared + + +class TotalTQDM: + def __init__(self): + self._tqdm = None + + def reset(self): + self._tqdm = tqdm.tqdm( + desc="Total progress", + total=shared.state.job_count * shared.state.sampling_steps, + position=1, + file=shared.progress_print_out + ) + + def update(self): + if not shared.opts.multiple_tqdm or shared.cmd_opts.disable_console_progressbars: + return + if self._tqdm is None: + self.reset() + self._tqdm.update() + + def updateTotal(self, new_total): + if not shared.opts.multiple_tqdm or shared.cmd_opts.disable_console_progressbars: + return + if self._tqdm is None: + self.reset() + self._tqdm.total = new_total + + def clear(self): + if self._tqdm is not None: + self._tqdm.refresh() + self._tqdm.close() + self._tqdm = None + diff --git a/modules/sysinfo.py b/modules/sysinfo.py index cf24c6dd..7d906e1f 100644 --- a/modules/sysinfo.py +++ b/modules/sysinfo.py @@ -10,7 +10,7 @@ import psutil import re import launch -from modules import paths_internal, timer +from modules import paths_internal, timer, shared, extensions, errors checksum_token = "DontStealMyGamePlz__WINNERS_DONT_USE_DRUGS__DONT_COPY_THAT_FLOPPY" environment_whitelist = { @@ -115,8 +115,6 @@ def format_exception(e, tb): def get_exceptions(): try: - from modules import errors - return list(reversed(errors.exception_records)) except Exception as e: return str(e) @@ -142,8 +140,6 @@ def get_torch_sysinfo(): def get_extensions(*, enabled): try: - from modules import extensions - def to_json(x: extensions.Extension): return { "name": x.name, @@ -160,7 +156,6 @@ def get_extensions(*, enabled): def get_config(): try: - from modules import shared return shared.opts.data except Exception as e: return str(e) diff --git a/modules/ui.py b/modules/ui.py index e3753e97..30b80417 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -13,7 +13,7 @@ from PIL import Image, PngImagePlugin # noqa: F401 from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call from modules import gradio_extensons # noqa: F401 -from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, ui_prompt_styles, scripts, sd_samplers +from modules import sd_hijack, sd_models, script_callbacks, ui_extensions, deepbooru, extra_networks, ui_common, ui_postprocessing, progress, ui_loadsave, errors, shared_items, ui_settings, timer, sysinfo, ui_checkpoint_merger, ui_prompt_styles, scripts, sd_samplers, processing, devices, ui_extra_networks from modules.ui_components import FormRow, FormGroup, ToolButton, FormHTML from modules.paths import script_path from modules.ui_common import create_refresh_button @@ -91,8 +91,6 @@ def send_gradio_gallery_to_image(x): def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y): - from modules import processing, devices - if not enable: return "" @@ -630,7 +628,6 @@ def create_ui(): toprow.token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps], outputs=[toprow.token_counter]) toprow.negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_token_counter]) - from modules import ui_extra_networks extra_networks_ui = ui_extra_networks.create_ui(txt2img_interface, [txt2img_generation_tab], 'txt2img') ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery) @@ -995,7 +992,6 @@ def create_ui(): paste_button=toprow.paste, tabname="img2img", source_text_component=toprow.prompt, source_image_component=None, )) - from modules import ui_extra_networks extra_networks_ui_img2img = ui_extra_networks.create_ui(img2img_interface, [img2img_generation_tab], 'img2img') ui_extra_networks.setup_ui(extra_networks_ui_img2img, img2img_gallery) diff --git a/modules/ui_common.py b/modules/ui_common.py index 303af9cd..99d19ff0 100644 --- a/modules/ui_common.py +++ b/modules/ui_common.py @@ -11,7 +11,7 @@ from modules import call_queue, shared from modules.generation_parameters_copypaste import image_from_url_text import modules.images from modules.ui_components import ToolButton - +import modules.generation_parameters_copypaste as parameters_copypaste folder_symbol = '\U0001f4c2' # 📂 refresh_symbol = '\U0001f504' # 🔄 @@ -105,8 +105,6 @@ def save_files(js_data, images, do_make_zip, index): def create_output_panel(tabname, outdir): - from modules import shared - import modules.generation_parameters_copypaste as parameters_copypaste def open_folder(f): if not os.path.exists(f): diff --git a/modules/util.py b/modules/util.py new file mode 100644 index 00000000..60afc067 --- /dev/null +++ b/modules/util.py @@ -0,0 +1,58 @@ +import os +import re + +from modules import shared +from modules.paths_internal import script_path + + +def natural_sort_key(s, regex=re.compile('([0-9]+)')): + return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)] + + +def listfiles(dirname): + filenames = [os.path.join(dirname, x) for x in sorted(os.listdir(dirname), key=natural_sort_key) if not x.startswith(".")] + return [file for file in filenames if os.path.isfile(file)] + + +def html_path(filename): + return os.path.join(script_path, "html", filename) + + +def html(filename): + path = html_path(filename) + + if os.path.exists(path): + with open(path, encoding="utf8") as file: + return file.read() + + return "" + + +def walk_files(path, allowed_extensions=None): + if not os.path.exists(path): + return + + if allowed_extensions is not None: + allowed_extensions = set(allowed_extensions) + + items = list(os.walk(path, followlinks=True)) + items = sorted(items, key=lambda x: natural_sort_key(x[0])) + + for root, _, files in items: + for filename in sorted(files, key=natural_sort_key): + if allowed_extensions is not None: + _, ext = os.path.splitext(filename) + if ext not in allowed_extensions: + continue + + if not shared.opts.list_hidden_files and ("/." in root or "\\." in root): + continue + + yield os.path.join(root, filename) + + +def ldm_print(*args, **kwargs): + if shared.opts.hide_ldm_prints: + return + + print(*args, **kwargs) diff --git a/webui.py b/webui.py index 6d36f880..0f1ace97 100644 --- a/webui.py +++ b/webui.py @@ -43,12 +43,15 @@ startup_timer.record("import torch") import gradio # noqa: F401 startup_timer.record("import gradio") -from modules import paths, timer, import_hook, errors, devices # noqa: F401 +from modules import paths, timer, import_hook, errors # noqa: F401 startup_timer.record("setup paths") import ldm.modules.encoders.modules # noqa: F401 startup_timer.record("import ldm") +from modules import shared_init, shared, shared_items +shared_init.initialize() +startup_timer.record("initialize shared") from modules import extra_networks from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, queue_lock # noqa: F401 @@ -58,8 +61,6 @@ if ".dev" in torch.__version__ or "+git" in torch.__version__: torch.__long_version__ = torch.__version__ torch.__version__ = re.search(r'[\d.]+[\d]', torch.__version__).group(0) -from modules import shared - if not shared.cmd_opts.skip_version_check: errors.check_versions() @@ -82,7 +83,7 @@ import modules.textual_inversion.textual_inversion import modules.progress import modules.ui -from modules import modelloader +from modules import modelloader, devices from modules.shared import cmd_opts import modules.hypernetworks.hypernetwork @@ -297,7 +298,7 @@ def initialize_rest(*, reload_script_modules=False): Thread(target=load_model).start() - shared.reload_hypernetworks() + shared_items.reload_hypernetworks() startup_timer.record("reload hypernetworks") ui_extra_networks.initialize() -- cgit v1.2.3 From aa10faa591f1ca0bd93ae3d53a0a4c15a3fbaf82 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 9 Aug 2023 14:47:44 +0300 Subject: fix checkpoint name jumping around in the list of checkpoints for no good reason --- modules/sd_models.py | 12 +++++++++--- 1 file changed, 9 insertions(+), 3 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index b490fa99..7a866a07 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -68,7 +68,9 @@ class CheckpointInfo: self.title = name if self.shorthash is None else f'{name} [{self.shorthash}]' self.short_title = self.name_for_extra if self.shorthash is None else f'{self.name_for_extra} [{self.shorthash}]' - self.ids = [self.hash, self.model_name, self.title, name, self.name_for_extra, f'{name} [{self.hash}]'] + ([self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] if self.shorthash else []) + self.ids = [self.hash, self.model_name, self.title, name, self.name_for_extra, f'{name} [{self.hash}]'] + if self.shorthash: + self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]', f'{self.name_for_extra} [{self.shorthash}]'] def register(self): checkpoints_list[self.title] = self @@ -80,10 +82,14 @@ class CheckpointInfo: if self.sha256 is None: return - self.shorthash = self.sha256[0:10] + shorthash = self.sha256[0:10] + if self.shorthash == self.sha256[0:10]: + return self.shorthash + + self.shorthash = shorthash if self.shorthash not in self.ids: - self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]'] + self.ids += [self.shorthash, self.sha256, f'{self.name} [{self.shorthash}]', f'{self.name_for_extra} [{self.shorthash}]'] checkpoints_list.pop(self.title, None) self.title = f'{self.name} [{self.shorthash}]' -- cgit v1.2.3 From ac8a5d18d3ede6bcb8fa5a3da1c7c28e064cd65d Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 17:04:59 +0300 Subject: resolve merge issues --- modules/sd_models.py | 7 +++++-- modules/sd_samplers_kdiffusion.py | 3 +-- modules/shared_options.py | 2 ++ 3 files changed, 8 insertions(+), 4 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index f6cb2f34..a178adca 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -640,8 +640,11 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): timer.record("send model to device") model_data.set_sd_model(already_loaded) - shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title - shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256 + + 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()}") return model_data.sd_model elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit: diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index e1854980..95a43cef 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -1,8 +1,7 @@ import torch import inspect import k_diffusion.sampling -from modules import sd_samplers_common, sd_samplers_extra -from modules.sd_samplers_cfg_denoiser import CFGDenoiser +from modules import sd_samplers_common, sd_samplers_extra, sd_samplers_cfg_denoiser from modules.shared import opts import modules.shared as shared diff --git a/modules/shared_options.py b/modules/shared_options.py index 9ae51f18..1e5b64ea 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -140,6 +140,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), "tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"), + "sd_refiner_checkpoint": OptionInfo("None", "Refiner checkpoint", gr.Dropdown, lambda: {"choices": ["None"] + shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext="Refiner").info("switch to another model in the middle of generation"), + "sd_refiner_switch_at": OptionInfo(1.0, "Refiner switch at", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Refiner switch at').info("fraction of sampling steps when the swtch to refiner model should happen; 1=never, 0.5=switch in the middle of generation"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { -- cgit v1.2.3 From 64311faa6848d641cc452115e4e1eb47d2a7b519 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sat, 12 Aug 2023 12:39:59 +0300 Subject: put refiner into main UI, into the new accordions section add VAE from main model into infotext, not from refiner model option to make scripts UI without gr.Group fix inconsistencies with refiner when usings samplers that do more denoising than steps --- modules/processing.py | 22 ++++++++----- modules/processing_scripts/refiner.py | 55 +++++++++++++++++++++++++++++++++ modules/scripts.py | 24 ++++++++++----- modules/sd_models.py | 3 ++ modules/sd_samplers_cfg_denoiser.py | 6 +++- modules/sd_samplers_common.py | 40 ++++++++++++++---------- modules/sd_samplers_kdiffusion.py | 3 +- modules/shared_items.py | 4 +-- modules/shared_options.py | 2 -- modules/ui.py | 58 ++++++++++++++++++++--------------- modules/ui_components.py | 18 ++++++++--- style.css | 32 +++++++++++-------- 12 files changed, 188 insertions(+), 79 deletions(-) create mode 100644 modules/processing_scripts/refiner.py (limited to 'modules/sd_models.py') diff --git a/modules/processing.py b/modules/processing.py index 131c4c3c..5996cbac 100755 --- a/modules/processing.py +++ b/modules/processing.py @@ -373,9 +373,10 @@ class StableDiffusionProcessing: negative_prompts = prompt_parser.SdConditioning(self.negative_prompts, width=self.width, height=self.height, is_negative_prompt=True) sampler_config = sd_samplers.find_sampler_config(self.sampler_name) - self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1 - self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, self.steps * self.step_multiplier, [self.cached_uc], self.extra_network_data) - self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, self.steps * self.step_multiplier, [self.cached_c], self.extra_network_data) + total_steps = sampler_config.total_steps(self.steps) if sampler_config else self.steps + self.step_multiplier = total_steps // self.steps + self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, total_steps, [self.cached_uc], self.extra_network_data) + self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data) def get_conds(self): return self.c, self.uc @@ -579,8 +580,8 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Size": f"{p.width}x{p.height}", "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash), "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra), - "VAE hash": sd_vae.get_loaded_vae_hash() if opts.add_model_hash_to_info else None, - "VAE": sd_vae.get_loaded_vae_name() if opts.add_model_name_to_info else None, + "VAE hash": p.loaded_vae_hash if opts.add_model_hash_to_info else None, + "VAE": p.loaded_vae_name if opts.add_model_name_to_info else None, "Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])), "Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength), "Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"), @@ -669,6 +670,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.tiling is None: p.tiling = opts.tiling + p.loaded_vae_name = sd_vae.get_loaded_vae_name() + p.loaded_vae_hash = sd_vae.get_loaded_vae_hash() + modules.sd_hijack.model_hijack.apply_circular(p.tiling) modules.sd_hijack.model_hijack.clear_comments() @@ -1188,8 +1192,12 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): hr_prompts = prompt_parser.SdConditioning(self.hr_prompts, width=self.hr_upscale_to_x, height=self.hr_upscale_to_y) hr_negative_prompts = prompt_parser.SdConditioning(self.hr_negative_prompts, width=self.hr_upscale_to_x, height=self.hr_upscale_to_y, is_negative_prompt=True) - self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, self.steps * self.step_multiplier, [self.cached_hr_uc, self.cached_uc], self.hr_extra_network_data) - self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, self.steps * self.step_multiplier, [self.cached_hr_c, self.cached_c], self.hr_extra_network_data) + sampler_config = sd_samplers.find_sampler_config(self.hr_sampler_name or self.sampler_name) + steps = self.hr_second_pass_steps or self.steps + total_steps = sampler_config.total_steps(steps) if sampler_config else steps + + self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, total_steps, [self.cached_hr_uc, self.cached_uc], self.hr_extra_network_data) + self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, total_steps, [self.cached_hr_c, self.cached_c], self.hr_extra_network_data) def setup_conds(self): super().setup_conds() diff --git a/modules/processing_scripts/refiner.py b/modules/processing_scripts/refiner.py new file mode 100644 index 00000000..5a82991a --- /dev/null +++ b/modules/processing_scripts/refiner.py @@ -0,0 +1,55 @@ +import gradio as gr + +from modules import scripts, sd_models +from modules.ui_common import create_refresh_button +from modules.ui_components import InputAccordion + + +class ScriptRefiner(scripts.Script): + section = "accordions" + create_group = False + + def __init__(self): + pass + + def title(self): + return "Refiner" + + def show(self, is_img2img): + return scripts.AlwaysVisible + + def ui(self, is_img2img): + with InputAccordion(False, label="Refiner", elem_id=self.elem_id("enable")) as enable_refiner: + with gr.Row(): + refiner_checkpoint = gr.Dropdown(label='Checkpoint', elem_id=self.elem_id("checkpoint"), choices=sd_models.checkpoint_tiles(), value='', tooltip="switch to another model in the middle of generation") + create_refresh_button(refiner_checkpoint, sd_models.list_models, lambda: {"choices": sd_models.checkpoint_tiles()}, self.elem_id("checkpoint_refresh")) + + refiner_switch_at = gr.Slider(value=0.8, label="Switch at", minimum=0.01, maximum=1.0, step=0.01, elem_id=self.elem_id("switch_at"), tooltip="fraction of sampling steps when the swtch to refiner model should happen; 1=never, 0.5=switch in the middle of generation") + + def lookup_checkpoint(title): + info = sd_models.get_closet_checkpoint_match(title) + return None if info is None else info.title + + self.infotext_fields = [ + (enable_refiner, lambda d: 'Refiner' in d), + (refiner_checkpoint, lambda d: lookup_checkpoint(d.get('Refiner'))), + (refiner_switch_at, 'Refiner switch at'), + ] + + return enable_refiner, refiner_checkpoint, refiner_switch_at + + def before_process(self, p, enable_refiner, refiner_checkpoint, refiner_switch_at): + # the actual implementation is in sd_samplers_common.py, apply_refiner + + p.refiner_checkpoint_info = None + p.refiner_switch_at = None + + if not enable_refiner or refiner_checkpoint in (None, "", "None"): + return + + refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(refiner_checkpoint) + if refiner_checkpoint_info is None: + raise Exception(f'Could not find checkpoint with name {refiner_checkpoint}') + + p.refiner_checkpoint_info = refiner_checkpoint_info + p.refiner_switch_at = refiner_switch_at diff --git a/modules/scripts.py b/modules/scripts.py index f7d060aa..51da732a 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -37,7 +37,10 @@ class Script: is_img2img = False group = None - """A gr.Group component that has all script's UI inside it""" + """A gr.Group component that has all script's UI inside it.""" + + create_group = True + """If False, for alwayson scripts, a group component will not be created.""" infotext_fields = None """if set in ui(), this is a list of pairs of gradio component + text; the text will be used when @@ -232,6 +235,7 @@ class Script: """ pass + current_basedir = paths.script_path @@ -250,7 +254,7 @@ postprocessing_scripts_data = [] ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir", "module"]) -def list_scripts(scriptdirname, extension): +def list_scripts(scriptdirname, extension, *, include_extensions=True): scripts_list = [] basedir = os.path.join(paths.script_path, scriptdirname) @@ -258,8 +262,9 @@ def list_scripts(scriptdirname, extension): for filename in sorted(os.listdir(basedir)): scripts_list.append(ScriptFile(paths.script_path, filename, os.path.join(basedir, filename))) - for ext in extensions.active(): - scripts_list += ext.list_files(scriptdirname, extension) + if include_extensions: + for ext in extensions.active(): + scripts_list += ext.list_files(scriptdirname, extension) scripts_list = [x for x in scripts_list if os.path.splitext(x.path)[1].lower() == extension and os.path.isfile(x.path)] @@ -288,7 +293,7 @@ def load_scripts(): postprocessing_scripts_data.clear() script_callbacks.clear_callbacks() - scripts_list = list_scripts("scripts", ".py") + scripts_list = list_scripts("scripts", ".py") + list_scripts("modules/processing_scripts", ".py", include_extensions=False) syspath = sys.path @@ -429,10 +434,13 @@ class ScriptRunner: if script.alwayson and script.section != section: continue - with gr.Group(visible=script.alwayson) as group: - self.create_script_ui(script) + if script.create_group: + with gr.Group(visible=script.alwayson) as group: + self.create_script_ui(script) - script.group = group + script.group = group + else: + self.create_script_ui(script) def prepare_ui(self): self.inputs = [None] diff --git a/modules/sd_models.py b/modules/sd_models.py index a178adca..f6fbdcd6 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -147,6 +147,9 @@ re_strip_checksum = re.compile(r"\s*\[[^]]+]\s*$") def get_closet_checkpoint_match(search_string): + if not search_string: + return None + checkpoint_info = checkpoint_aliases.get(search_string, None) if checkpoint_info is not None: return checkpoint_info diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py index a532e013..113425b2 100644 --- a/modules/sd_samplers_cfg_denoiser.py +++ b/modules/sd_samplers_cfg_denoiser.py @@ -45,6 +45,11 @@ class CFGDenoiser(torch.nn.Module): self.nmask = None self.init_latent = None self.steps = None + """number of steps as specified by user in UI""" + + self.total_steps = None + """expected number of calls to denoiser calculated from self.steps and specifics of the selected sampler""" + self.step = 0 self.image_cfg_scale = None self.padded_cond_uncond = False @@ -56,7 +61,6 @@ class CFGDenoiser(torch.nn.Module): def inner_model(self): raise NotImplementedError() - def combine_denoised(self, x_out, conds_list, uncond, cond_scale): denoised_uncond = x_out[-uncond.shape[0]:] denoised = torch.clone(denoised_uncond) diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index 35c4d657..85f3c7e0 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -7,7 +7,16 @@ from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, s from modules.shared import opts, state import k_diffusion.sampling -SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options']) + +SamplerDataTuple = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options']) + + +class SamplerData(SamplerDataTuple): + def total_steps(self, steps): + if self.options.get("second_order", False): + steps = steps * 2 + + return steps def setup_img2img_steps(p, steps=None): @@ -131,31 +140,26 @@ def replace_torchsde_browinan(): replace_torchsde_browinan() -def apply_refiner(sampler): - completed_ratio = sampler.step / sampler.steps +def apply_refiner(cfg_denoiser): + completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps + refiner_switch_at = cfg_denoiser.p.refiner_switch_at + refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info - if completed_ratio <= shared.opts.sd_refiner_switch_at: + if refiner_switch_at is not None and completed_ratio <= refiner_switch_at: return False - if shared.opts.sd_refiner_checkpoint == "None": + if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info: return False - if shared.sd_model.sd_checkpoint_info.title == shared.opts.sd_refiner_checkpoint: - return False - - refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(shared.opts.sd_refiner_checkpoint) - if refiner_checkpoint_info is None: - raise Exception(f'Could not find checkpoint with name {shared.opts.sd_refiner_checkpoint}') - - sampler.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title - sampler.p.extra_generation_params['Refiner switch at'] = shared.opts.sd_refiner_switch_at + cfg_denoiser.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title + cfg_denoiser.p.extra_generation_params['Refiner switch at'] = refiner_switch_at with sd_models.SkipWritingToConfig(): sd_models.reload_model_weights(info=refiner_checkpoint_info) devices.torch_gc() - sampler.p.setup_conds() - sampler.update_inner_model() + cfg_denoiser.p.setup_conds() + cfg_denoiser.update_inner_model() return True @@ -192,7 +196,7 @@ class Sampler: self.sampler_noises = None self.stop_at = None self.eta = None - self.config = None # set by the function calling the constructor + self.config: SamplerData = None # set by the function calling the constructor self.last_latent = None self.s_min_uncond = None self.s_churn = 0.0 @@ -208,6 +212,7 @@ class Sampler: self.p = None self.model_wrap_cfg = None self.sampler_extra_args = None + self.options = {} def callback_state(self, d): step = d['i'] @@ -220,6 +225,7 @@ class Sampler: def launch_sampling(self, steps, func): self.model_wrap_cfg.steps = steps + self.model_wrap_cfg.total_steps = self.config.total_steps(steps) state.sampling_steps = steps state.sampling_step = 0 diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index d10fe12e..1f8e9c4b 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -64,9 +64,10 @@ class CFGDenoiserKDiffusion(sd_samplers_cfg_denoiser.CFGDenoiser): class KDiffusionSampler(sd_samplers_common.Sampler): - def __init__(self, funcname, sd_model): + def __init__(self, funcname, sd_model, options=None): super().__init__(funcname) + self.options = options or {} self.func = funcname if callable(funcname) else getattr(k_diffusion.sampling, self.funcname) self.model_wrap_cfg = CFGDenoiserKDiffusion(self) diff --git a/modules/shared_items.py b/modules/shared_items.py index e4ec40a8..754166d2 100644 --- a/modules/shared_items.py +++ b/modules/shared_items.py @@ -69,8 +69,8 @@ def reload_hypernetworks(): ui_reorder_categories_builtin_items = [ "inpaint", "sampler", + "accordions", "checkboxes", - "hires_fix", "dimensions", "cfg", "seed", @@ -86,7 +86,7 @@ def ui_reorder_categories(): sections = {} for script in scripts.scripts_txt2img.scripts + scripts.scripts_img2img.scripts: - if isinstance(script.section, str): + if isinstance(script.section, str) and script.section not in ui_reorder_categories_builtin_items: sections[script.section] = 1 yield from sections diff --git a/modules/shared_options.py b/modules/shared_options.py index 1e5b64ea..9ae51f18 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -140,8 +140,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), "tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"), - "sd_refiner_checkpoint": OptionInfo("None", "Refiner checkpoint", gr.Dropdown, lambda: {"choices": ["None"] + shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext="Refiner").info("switch to another model in the middle of generation"), - "sd_refiner_switch_at": OptionInfo(1.0, "Refiner switch at", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Refiner switch at').info("fraction of sampling steps when the swtch to refiner model should happen; 1=never, 0.5=switch in the middle of generation"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { diff --git a/modules/ui.py b/modules/ui.py index 05292734..3321b94d 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -438,35 +438,38 @@ def create_ui(): with FormRow(elem_classes="checkboxes-row", variant="compact"): pass - elif category == "hires_fix": - with InputAccordion(False, label="Hires. fix") as enable_hr: - with enable_hr.extra(): - hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False, min_width=0) + elif category == "accordions": + with gr.Row(elem_id="txt2img_accordions", elem_classes="accordions"): + with InputAccordion(False, label="Hires. fix", elem_id="txt2img_hr") as enable_hr: + with enable_hr.extra(): + hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False, min_width=0) - with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"): - hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode) - hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps") - denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength") + with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"): + hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode) + hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps") + denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength") - with FormRow(elem_id="txt2img_hires_fix_row2", variant="compact"): - hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale") - hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x") - hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y") + with FormRow(elem_id="txt2img_hires_fix_row2", variant="compact"): + hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale") + hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x") + hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y") - with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container: + with FormRow(elem_id="txt2img_hires_fix_row3", variant="compact", visible=opts.hires_fix_show_sampler) as hr_sampler_container: - hr_checkpoint_name = gr.Dropdown(label='Hires checkpoint', elem_id="hr_checkpoint", choices=["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True), value="Use same checkpoint") - create_refresh_button(hr_checkpoint_name, modules.sd_models.list_models, lambda: {"choices": ["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True)}, "hr_checkpoint_refresh") + hr_checkpoint_name = gr.Dropdown(label='Hires checkpoint', elem_id="hr_checkpoint", choices=["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True), value="Use same checkpoint") + create_refresh_button(hr_checkpoint_name, modules.sd_models.list_models, lambda: {"choices": ["Use same checkpoint"] + modules.sd_models.checkpoint_tiles(use_short=True)}, "hr_checkpoint_refresh") - hr_sampler_name = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + sd_samplers.visible_sampler_names(), value="Use same sampler") + hr_sampler_name = gr.Dropdown(label='Hires sampling method', elem_id="hr_sampler", choices=["Use same sampler"] + sd_samplers.visible_sampler_names(), value="Use same sampler") - with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container: - with gr.Column(scale=80): - with gr.Row(): - hr_prompt = gr.Textbox(label="Hires prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"]) - with gr.Column(scale=80): - with gr.Row(): - hr_negative_prompt = gr.Textbox(label="Hires negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"]) + with FormRow(elem_id="txt2img_hires_fix_row4", variant="compact", visible=opts.hires_fix_show_prompts) as hr_prompts_container: + with gr.Column(scale=80): + with gr.Row(): + hr_prompt = gr.Textbox(label="Hires prompt", elem_id="hires_prompt", show_label=False, lines=3, placeholder="Prompt for hires fix pass.\nLeave empty to use the same prompt as in first pass.", elem_classes=["prompt"]) + with gr.Column(scale=80): + with gr.Row(): + hr_negative_prompt = gr.Textbox(label="Hires negative prompt", elem_id="hires_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt for hires fix pass.\nLeave empty to use the same negative prompt as in first pass.", elem_classes=["prompt"]) + + scripts.scripts_txt2img.setup_ui_for_section(category) elif category == "batch": if not opts.dimensions_and_batch_together: @@ -482,7 +485,7 @@ def create_ui(): with FormGroup(elem_id="txt2img_script_container"): custom_inputs = scripts.scripts_txt2img.setup_ui() - else: + if category not in {"accordions"}: scripts.scripts_txt2img.setup_ui_for_section(category) hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y] @@ -794,6 +797,10 @@ def create_ui(): with FormRow(elem_classes="checkboxes-row", variant="compact"): pass + elif category == "accordions": + with gr.Row(elem_id="img2img_accordions", elem_classes="accordions"): + scripts.scripts_img2img.setup_ui_for_section(category) + elif category == "batch": if not opts.dimensions_and_batch_together: with FormRow(elem_id="img2img_column_batch"): @@ -836,7 +843,8 @@ def create_ui(): inputs=[], outputs=[inpaint_controls, mask_alpha], ) - else: + + if category not in {"accordions"}: scripts.scripts_img2img.setup_ui_for_section(category) img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples) diff --git a/modules/ui_components.py b/modules/ui_components.py index bfe2fbd9..d08b2b99 100644 --- a/modules/ui_components.py +++ b/modules/ui_components.py @@ -87,13 +87,23 @@ class InputAccordion(gr.Checkbox): self.accordion_id = f"input-accordion-{InputAccordion.global_index}" InputAccordion.global_index += 1 - kwargs['elem_id'] = self.accordion_id + "-checkbox" - kwargs['visible'] = False - super().__init__(value, **kwargs) + kwargs_checkbox = { + **kwargs, + "elem_id": f"{self.accordion_id}-checkbox", + "visible": False, + } + super().__init__(value, **kwargs_checkbox) self.change(fn=None, _js='function(checked){ inputAccordionChecked("' + self.accordion_id + '", checked); }', inputs=[self]) - self.accordion = gr.Accordion(kwargs.get('label', 'Accordion'), open=value, elem_id=self.accordion_id, elem_classes=['input-accordion']) + kwargs_accordion = { + **kwargs, + "elem_id": self.accordion_id, + "label": kwargs.get('label', 'Accordion'), + "elem_classes": ['input-accordion'], + "open": value, + } + self.accordion = gr.Accordion(**kwargs_accordion) def extra(self): """Allows you to put something into the label of the accordion. diff --git a/style.css b/style.css index 4cdce87c..260b1056 100644 --- a/style.css +++ b/style.css @@ -166,16 +166,6 @@ a{ color: var(--button-secondary-text-color-hover); } -.checkboxes-row{ - margin-bottom: 0.5em; - margin-left: 0em; -} -.checkboxes-row > div{ - flex: 0; - white-space: nowrap; - min-width: auto !important; -} - button.custom-button{ border-radius: var(--button-large-radius); padding: var(--button-large-padding); @@ -352,7 +342,7 @@ div.block.gradio-accordion { } div.dimensions-tools{ - min-width: 0 !important; + min-width: 1.6em !important; max-width: fit-content; flex-direction: column; place-content: center; @@ -1012,10 +1002,28 @@ div.block.gradio-box.popup-dialog > div:last-child, .popup-dialog > div:last-chi } div.block.input-accordion{ - margin-bottom: 0.4em; + } .input-accordion-extra{ flex: 0 0 auto !important; margin: 0 0.5em 0 auto; } + +div.accordions > div.input-accordion{ + min-width: fit-content !important; +} + +div.accordions > div.gradio-accordion .label-wrap span{ + white-space: nowrap; + margin-right: 0.25em; +} + +div.accordions{ + gap: 0.5em; +} + +div.accordions > div.input-accordion.input-accordion-open{ + flex: 1 auto; +} + -- cgit v1.2.3 From 0815c45bcdec0a2e5c60bdd5b33d95813d799c01 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 16 Aug 2023 10:44:17 +0300 Subject: send weights to target device instead of CPU memory --- modules/sd_models.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index f6fbdcd6..b01d44c5 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -579,7 +579,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): timer.record("create model") - with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): + with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.device): load_model_weights(sd_model, checkpoint_info, state_dict, timer) timer.record("load weights from state dict") -- cgit v1.2.3 From 57e59c14c8a13a99d6422597d27d92ad10a51ca1 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 16 Aug 2023 11:28:00 +0300 Subject: Revert "send weights to target device instead of CPU memory" This reverts commit 0815c45bcdec0a2e5c60bdd5b33d95813d799c01. --- modules/sd_models.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index b01d44c5..f6fbdcd6 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -579,7 +579,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): timer.record("create model") - with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.device): + with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): load_model_weights(sd_model, checkpoint_info, state_dict, timer) timer.record("load weights from state dict") -- cgit v1.2.3 From eaba3d7349c6f0e151be66ade3fdc848d693a10d Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 16 Aug 2023 12:11:01 +0300 Subject: send weights to target device instead of CPU memory --- modules/sd_disable_initialization.py | 24 +++++++++++++++--------- modules/sd_models.py | 17 ++++++++++++++++- 2 files changed, 31 insertions(+), 10 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py index 719eeb93..8863107a 100644 --- a/modules/sd_disable_initialization.py +++ b/modules/sd_disable_initialization.py @@ -155,10 +155,16 @@ class LoadStateDictOnMeta(ReplaceHelper): ``` """ - def __init__(self, state_dict, device): + def __init__(self, state_dict, device, weight_dtype_conversion=None): super().__init__() self.state_dict = state_dict self.device = device + self.weight_dtype_conversion = weight_dtype_conversion or {} + self.default_dtype = self.weight_dtype_conversion.get('') + + def get_weight_dtype(self, key): + key_first_term, _ = key.split('.', 1) + return self.weight_dtype_conversion.get(key_first_term, self.default_dtype) def __enter__(self): if shared.cmd_opts.disable_model_loading_ram_optimization: @@ -167,24 +173,24 @@ class LoadStateDictOnMeta(ReplaceHelper): sd = self.state_dict device = self.device - def load_from_state_dict(original, self, state_dict, prefix, *args, **kwargs): + def load_from_state_dict(original, module, state_dict, prefix, *args, **kwargs): used_param_keys = [] - for name, param in self._parameters.items(): + for name, param in module._parameters.items(): if param is None: continue key = prefix + name sd_param = sd.pop(key, None) if sd_param is not None: - state_dict[key] = sd_param + state_dict[key] = sd_param.to(dtype=self.get_weight_dtype(key)) used_param_keys.append(key) if param.is_meta: dtype = sd_param.dtype if sd_param is not None else param.dtype - self._parameters[name] = torch.nn.parameter.Parameter(torch.zeros_like(param, device=device, dtype=dtype), requires_grad=param.requires_grad) + module._parameters[name] = torch.nn.parameter.Parameter(torch.zeros_like(param, device=device, dtype=dtype), requires_grad=param.requires_grad) - for name in self._buffers: + for name in module._buffers: key = prefix + name sd_param = sd.pop(key, None) @@ -192,12 +198,12 @@ class LoadStateDictOnMeta(ReplaceHelper): state_dict[key] = sd_param used_param_keys.append(key) - original(self, state_dict, prefix, *args, **kwargs) + original(module, state_dict, prefix, *args, **kwargs) for key in used_param_keys: state_dict.pop(key, None) - def load_state_dict(original, self, state_dict, strict=True): + def load_state_dict(original, module, state_dict, strict=True): """torch makes a lot of copies of the dictionary with weights, so just deleting entries from state_dict does not help because the same values are stored in multiple copies of the dict. The trick used here is to give torch a dict with all weights on meta device, i.e. deleted, and then it doesn't matter how many copies torch makes. @@ -212,7 +218,7 @@ class LoadStateDictOnMeta(ReplaceHelper): if state_dict == sd: state_dict = {k: v.to(device="meta", dtype=v.dtype) for k, v in state_dict.items()} - original(self, state_dict, strict=strict) + original(module, state_dict, strict=strict) module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs)) module_load_from_state_dict = self.replace(torch.nn.Module, '_load_from_state_dict', lambda *args, **kwargs: load_from_state_dict(module_load_from_state_dict, *args, **kwargs)) diff --git a/modules/sd_models.py b/modules/sd_models.py index f6fbdcd6..f912fe16 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -518,6 +518,13 @@ def send_model_to_cpu(m): devices.torch_gc() +def model_target_device(): + if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + return devices.cpu + else: + return devices.device + + def send_model_to_device(m): if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) @@ -579,7 +586,15 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): timer.record("create model") - with sd_disable_initialization.LoadStateDictOnMeta(state_dict, devices.cpu): + if shared.cmd_opts.no_half: + weight_dtype_conversion = None + else: + weight_dtype_conversion = { + 'first_stage_model': None, + '': torch.float16, + } + + with sd_disable_initialization.LoadStateDictOnMeta(state_dict, device=model_target_device(), weight_dtype_conversion=weight_dtype_conversion): load_model_weights(sd_model, checkpoint_info, state_dict, timer) timer.record("load weights from state dict") -- cgit v1.2.3 From 0dc74545c0b5510911757ed9f2be703aab58f014 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 17 Aug 2023 07:54:07 +0300 Subject: resolve the issue with loading fp16 checkpoints while using --no-half --- modules/sd_models.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index f912fe16..685585b1 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -343,7 +343,10 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer model.to(memory_format=torch.channels_last) timer.record("apply channels_last") - if not shared.cmd_opts.no_half: + if shared.cmd_opts.no_half: + model.float() + timer.record("apply float()") + else: vae = model.first_stage_model depth_model = getattr(model, 'depth_model', None) -- cgit v1.2.3 From 042e1d5d0b1fc0bfd358e3a90db7d163934bd238 Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Sun, 20 Aug 2023 15:00:14 +0900 Subject: Fix SD VAE switch error after model reuse --- modules/sd_models.py | 22 ++++++++++++++++++++-- 1 file changed, 20 insertions(+), 2 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 685585b1..2c976561 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -462,6 +462,7 @@ class SdModelData: def __init__(self): self.sd_model = None self.loaded_sd_models = [] + self.loaded_vae_states = {} self.was_loaded_at_least_once = False self.lock = threading.Lock() @@ -485,16 +486,27 @@ class SdModelData: return self.sd_model - def set_sd_model(self, v): + def set_sd_model(self, v, already_loaded=False): self.sd_model = v + if already_loaded: + sd_vae_state = self.loaded_vae_states.get(v.sd_model_hash, {}) + sd_vae.base_vae = sd_vae_state.get("base_vae", None) + sd_vae.loaded_vae_file = sd_vae_state.get("loaded_vae_file", None) + sd_vae.checkpoint_info = sd_vae_state.get("checkpoint_info", None) try: self.loaded_sd_models.remove(v) + self.loaded_vae_states.pop(v.sd_model_hash, {}).clear() except ValueError: pass if v is not None: self.loaded_sd_models.insert(0, v) + self.loaded_vae_states[v.sd_model_hash] = dict( + base_vae=sd_vae.base_vae, + loaded_vae_file=sd_vae.loaded_vae_file, + checkpoint_info=sd_vae.checkpoint_info, + ) model_data = SdModelData() @@ -649,6 +661,7 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): 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() + model_data.loaded_vae_states.pop(loaded_model.sd_model_hash, {}).clear() send_model_to_trash(loaded_model) timer.record("send model to trash") @@ -660,7 +673,7 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): send_model_to_device(already_loaded) timer.record("send model to device") - model_data.set_sd_model(already_loaded) + 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 @@ -678,6 +691,11 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): sd_model = model_data.loaded_sd_models.pop() model_data.sd_model = sd_model + sd_vae_state = model_data.loaded_vae_states.pop(sd_model.sd_model_hash, {}) + sd_vae.base_vae = sd_vae_state.get("base_vae", None) + sd_vae.loaded_vae_file = sd_vae_state.get("loaded_vae_file", None) + sd_vae.checkpoint_info = sd_vae_state.get("checkpoint_info", None) + print(f"Reusing loaded model {sd_model.sd_checkpoint_info.title} to load {checkpoint_info.title}") return sd_model else: -- cgit v1.2.3 From 5159edbf0e0e1d5a25fbd588e000487746790117 Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Sun, 20 Aug 2023 19:44:37 +0900 Subject: Store base_vae and loaded_vae_file in sd_model --- modules/sd_models.py | 24 ++++++++---------------- 1 file changed, 8 insertions(+), 16 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 2c976561..150d550b 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -462,7 +462,6 @@ class SdModelData: def __init__(self): self.sd_model = None self.loaded_sd_models = [] - self.loaded_vae_states = {} self.was_loaded_at_least_once = False self.lock = threading.Lock() @@ -489,24 +488,19 @@ class SdModelData: def set_sd_model(self, v, already_loaded=False): self.sd_model = v if already_loaded: - sd_vae_state = self.loaded_vae_states.get(v.sd_model_hash, {}) - sd_vae.base_vae = sd_vae_state.get("base_vae", None) - sd_vae.loaded_vae_file = sd_vae_state.get("loaded_vae_file", None) - sd_vae.checkpoint_info = sd_vae_state.get("checkpoint_info", None) + sd_vae.base_vae = getattr(v, "base_vae", None) + sd_vae.loaded_vae_file = getattr(v, "loaded_vae_file", None) + sd_vae.checkpoint_info = v.sd_checkpoint_info try: self.loaded_sd_models.remove(v) - self.loaded_vae_states.pop(v.sd_model_hash, {}).clear() except ValueError: pass if v is not None: + setattr(v, "base_vae", sd_vae.base_vae) + setattr(v, "loaded_vae_file", sd_vae.loaded_vae_file) self.loaded_sd_models.insert(0, v) - self.loaded_vae_states[v.sd_model_hash] = dict( - base_vae=sd_vae.base_vae, - loaded_vae_file=sd_vae.loaded_vae_file, - checkpoint_info=sd_vae.checkpoint_info, - ) model_data = SdModelData() @@ -661,7 +655,6 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): 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() - model_data.loaded_vae_states.pop(loaded_model.sd_model_hash, {}).clear() send_model_to_trash(loaded_model) timer.record("send model to trash") @@ -691,10 +684,9 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): sd_model = model_data.loaded_sd_models.pop() model_data.sd_model = sd_model - sd_vae_state = model_data.loaded_vae_states.pop(sd_model.sd_model_hash, {}) - sd_vae.base_vae = sd_vae_state.get("base_vae", None) - sd_vae.loaded_vae_file = sd_vae_state.get("loaded_vae_file", None) - sd_vae.checkpoint_info = sd_vae_state.get("checkpoint_info", None) + 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 -- cgit v1.2.3 From af5d2e8e5fc4440691fb7f1aa3492def1c755722 Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Sun, 20 Aug 2023 20:08:22 +0900 Subject: Change to access sd_model attribute with dot --- modules/sd_models.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 150d550b..dd749122 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -498,8 +498,8 @@ class SdModelData: pass if v is not None: - setattr(v, "base_vae", sd_vae.base_vae) - setattr(v, "loaded_vae_file", sd_vae.loaded_vae_file) + v.base_vae = sd_vae.base_vae + v.loaded_vae_file = sd_vae.loaded_vae_file self.loaded_sd_models.insert(0, v) -- cgit v1.2.3 From 549b0fc5267e9539f321f0891aa757619b7248cb Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Sun, 20 Aug 2023 23:06:51 +0900 Subject: Change where VAE state are stored in model --- modules/sd_models.py | 2 -- modules/sd_vae.py | 4 +++- 2 files changed, 3 insertions(+), 3 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index dd749122..d3775ec6 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -498,8 +498,6 @@ class SdModelData: pass if v is not None: - v.base_vae = sd_vae.base_vae - v.loaded_vae_file = sd_vae.loaded_vae_file self.loaded_sd_models.insert(0, v) diff --git a/modules/sd_vae.py b/modules/sd_vae.py index dbade067..ee118656 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -192,7 +192,7 @@ def load_vae_dict(filename, map_location): def load_vae(model, vae_file=None, vae_source="from unknown source"): - global vae_dict, loaded_vae_file + global vae_dict, base_vae, loaded_vae_file # save_settings = False cache_enabled = shared.opts.sd_vae_checkpoint_cache > 0 @@ -230,6 +230,8 @@ def load_vae(model, vae_file=None, vae_source="from unknown source"): restore_base_vae(model) loaded_vae_file = vae_file + model.base_vae = base_vae + model.loaded_vae_file = loaded_vae_file # don't call this from outside -- cgit v1.2.3 From be301f224d26ac4363ce3bd8bcb510b00bd6db27 Mon Sep 17 00:00:00 2001 From: Uminosachi <49424133+Uminosachi@users.noreply.github.com> Date: Mon, 21 Aug 2023 11:28:53 +0900 Subject: Fix for consistency with shared.opts.sd_vae of UI --- modules/sd_models.py | 1 + 1 file changed, 1 insertion(+) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index d3775ec6..27d15e66 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -671,6 +671,7 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer): 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})") -- cgit v1.2.3 From 016554e43740e0b7ded75e89255de81270de9d6c Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Tue, 22 Aug 2023 18:49:08 +0300 Subject: add --medvram-sdxl --- modules/cmd_args.py | 1 + modules/interrogate.py | 5 ++--- modules/lowvram.py | 18 ++++++++++++++++-- modules/sd_models.py | 16 ++++++++-------- modules/sd_unet.py | 2 +- modules/sd_vae.py | 4 ++-- modules/shared.py | 2 +- 7 files changed, 31 insertions(+), 17 deletions(-) (limited to 'modules/sd_models.py') diff --git a/modules/cmd_args.py b/modules/cmd_args.py index 9f8e5b30..f0f361bd 100644 --- a/modules/cmd_args.py +++ b/modules/cmd_args.py @@ -35,6 +35,7 @@ parser.add_argument("--hypernetwork-dir", type=str, default=os.path.join(models_ parser.add_argument("--localizations-dir", type=str, default=os.path.join(script_path, 'localizations'), help="localizations directory") parser.add_argument("--allow-code", action='store_true', help="allow custom script execution from webui") parser.add_argument("--medvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a little speed for low VRM usage") +parser.add_argument("--medvram-sdxl", action='store_true', help="enable --medvram optimization just for SDXL models") parser.add_argument("--lowvram", action='store_true', help="enable stable diffusion model optimizations for sacrificing a lot of speed for very low VRM usage") parser.add_argument("--lowram", action='store_true', help="load stable diffusion checkpoint weights to VRAM instead of RAM") parser.add_argument("--always-batch-cond-uncond", action='store_true', help="does not do anything") diff --git a/modules/interrogate.py b/modules/interrogate.py index a3ae1dd5..3045560d 100644 --- a/modules/interrogate.py +++ b/modules/interrogate.py @@ -186,9 +186,8 @@ class InterrogateModels: res = "" shared.state.begin(job="interrogate") try: - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.send_everything_to_cpu() - devices.torch_gc() + lowvram.send_everything_to_cpu() + devices.torch_gc() self.load() diff --git a/modules/lowvram.py b/modules/lowvram.py index 96f52b7b..45701046 100644 --- a/modules/lowvram.py +++ b/modules/lowvram.py @@ -1,5 +1,5 @@ import torch -from modules import devices +from modules import devices, shared module_in_gpu = None cpu = torch.device("cpu") @@ -14,6 +14,20 @@ def send_everything_to_cpu(): module_in_gpu = None +def is_needed(sd_model): + return shared.cmd_opts.lowvram or shared.cmd_opts.medvram or shared.cmd_opts.medvram_sdxl and hasattr(sd_model, 'conditioner') + + +def apply(sd_model): + enable = is_needed(sd_model) + shared.parallel_processing_allowed = not enable + + if enable: + setup_for_low_vram(sd_model, not shared.cmd_opts.lowvram) + else: + sd_model.lowvram = False + + def setup_for_low_vram(sd_model, use_medvram): if getattr(sd_model, 'lowvram', False): return @@ -130,4 +144,4 @@ def setup_for_low_vram(sd_model, use_medvram): def is_enabled(sd_model): - return getattr(sd_model, 'lowvram', False) + return sd_model.lowvram diff --git a/modules/sd_models.py b/modules/sd_models.py index 27d15e66..4331853a 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -517,7 +517,7 @@ def get_empty_cond(sd_model): def send_model_to_cpu(m): - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + if m.lowvram: lowvram.send_everything_to_cpu() else: m.to(devices.cpu) @@ -525,17 +525,17 @@ def send_model_to_cpu(m): devices.torch_gc() -def model_target_device(): - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: +def model_target_device(m): + if lowvram.is_needed(m): return devices.cpu else: return devices.device def send_model_to_device(m): - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: - lowvram.setup_for_low_vram(m, shared.cmd_opts.medvram) - else: + lowvram.apply(m) + + if not m.lowvram: m.to(shared.device) @@ -601,7 +601,7 @@ def load_model(checkpoint_info=None, already_loaded_state_dict=None): '': torch.float16, } - with sd_disable_initialization.LoadStateDictOnMeta(state_dict, device=model_target_device(), weight_dtype_conversion=weight_dtype_conversion): + with sd_disable_initialization.LoadStateDictOnMeta(state_dict, device=model_target_device(sd_model), weight_dtype_conversion=weight_dtype_conversion): load_model_weights(sd_model, checkpoint_info, state_dict, timer) timer.record("load weights from state dict") @@ -743,7 +743,7 @@ def reload_model_weights(sd_model=None, info=None): script_callbacks.model_loaded_callback(sd_model) timer.record("script callbacks") - if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram: + if not sd_model.lowvram: sd_model.to(devices.device) timer.record("move model to device") diff --git a/modules/sd_unet.py b/modules/sd_unet.py index 6d708ad2..5525cfbc 100644 --- a/modules/sd_unet.py +++ b/modules/sd_unet.py @@ -47,7 +47,7 @@ def apply_unet(option=None): if current_unet_option is None: current_unet = None - if not (shared.cmd_opts.lowvram or shared.cmd_opts.medvram): + if not shared.sd_model.lowvram: shared.sd_model.model.diffusion_model.to(devices.device) return diff --git a/modules/sd_vae.py b/modules/sd_vae.py index ee118656..669097da 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -263,7 +263,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): if loaded_vae_file == vae_file: return - if shared.cmd_opts.lowvram or shared.cmd_opts.medvram: + if sd_model.lowvram: lowvram.send_everything_to_cpu() else: sd_model.to(devices.cpu) @@ -275,7 +275,7 @@ def reload_vae_weights(sd_model=None, vae_file=unspecified): sd_hijack.model_hijack.hijack(sd_model) script_callbacks.model_loaded_callback(sd_model) - if not shared.cmd_opts.lowvram and not shared.cmd_opts.medvram: + if not sd_model.lowvram: sd_model.to(devices.device) print("VAE weights loaded.") diff --git a/modules/shared.py b/modules/shared.py index 0c57b712..f321159d 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -11,7 +11,7 @@ cmd_opts = shared_cmd_options.cmd_opts parser = shared_cmd_options.parser batch_cond_uncond = True # old field, unused now in favor of shared.opts.batch_cond_uncond -parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram +parallel_processing_allowed = True styles_filename = cmd_opts.styles_file config_filename = cmd_opts.ui_settings_file hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config} -- cgit v1.2.3 From 0232a987bb8cbf337a5b34f38f7718aef92af269 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Wed, 23 Aug 2023 07:10:43 +0300 Subject: set devices.dtype_unet correctly --- modules/sd_models.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'modules/sd_models.py') diff --git a/modules/sd_models.py b/modules/sd_models.py index 4331853a..547e93c4 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -345,6 +345,7 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer if shared.cmd_opts.no_half: model.float() + devices.dtype_unet = torch.float32 timer.record("apply float()") else: vae = model.first_stage_model @@ -362,9 +363,9 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer if depth_model: model.depth_model = depth_model + devices.dtype_unet = torch.float16 timer.record("apply half()") - devices.dtype_unet = torch.float16 if model.is_sdxl and not shared.cmd_opts.no_half else model.model.diffusion_model.dtype devices.unet_needs_upcast = shared.cmd_opts.upcast_sampling and devices.dtype == torch.float16 and devices.dtype_unet == torch.float16 model.first_stage_model.to(devices.dtype_vae) -- cgit v1.2.3