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 +++ 1 file changed, 3 insertions(+) (limited to 'modules/generation_parameters_copypaste.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"] = "" -- cgit v1.2.3 From aa744cadc8e357e696a608c8d0c77a7bfc1c9f39 Mon Sep 17 00:00:00 2001 From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com> Date: Sat, 5 Aug 2023 12:35:40 +0800 Subject: add infotext --- modules/generation_parameters_copypaste.py | 8 ++++++++ modules/processing.py | 3 +++ 2 files changed, 11 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a3448be9..0713dbf0 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -304,6 +304,12 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model if "Schedule rho" not in res: res["Schedule rho"] = 0 + if "VAE Encoder" not in res: + res["VAE Encoder"] = "Full" + + if "VAE Decoder" not in res: + res["VAE Decoder"] = "Full" + return res @@ -329,6 +335,8 @@ infotext_to_setting_name_mapping = [ ('RNG', 'randn_source'), ('NGMS', 's_min_uncond'), ('Pad conds', 'pad_cond_uncond'), + ('VAE Encoder', 'sd_vae_encode_method'), + ('VAE Decoder', 'sd_vae_decode_method'), ] diff --git a/modules/processing.py b/modules/processing.py index aa6d4d2a..a9ee7507 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -788,6 +788,7 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: with devices.without_autocast() if devices.unet_needs_upcast else devices.autocast(): samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts) + p.extra_generation_params['VAE Decoder'] = opts.sd_vae_decode_method x_samples_ddim = decode_latent_batch(p.sd_model, samples_ddim, target_device=devices.cpu, check_for_nans=True) x_samples_ddim = torch.stack(x_samples_ddim).float() x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0) @@ -1100,6 +1101,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): decoded_samples = torch.from_numpy(np.array(batch_images)) decoded_samples = decoded_samples.to(shared.device) + self.extra_generation_params['VAE Encoder'] = opts.sd_vae_encode_method samples = images_tensor_to_samples(decoded_samples, approximation_indexes.get(opts.sd_vae_encode_method)) image_conditioning = self.img2img_image_conditioning(decoded_samples, samples) @@ -1338,6 +1340,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): raise RuntimeError(f"bad number of images passed: {len(imgs)}; expecting {self.batch_size} or less") image = torch.from_numpy(batch_images) + self.extra_generation_params['VAE Encoder'] = opts.sd_vae_encode_method self.init_latent = images_tensor_to_samples(image, approximation_indexes.get(opts.sd_vae_encode_method), self.sd_model) devices.torch_gc() -- cgit v1.2.3 From 31506f07718803190e67cbbd8180af313d9e2a08 Mon Sep 17 00:00:00 2001 From: catboxanon <122327233+catboxanon@users.noreply.github.com> Date: Sat, 5 Aug 2023 22:37:25 -0400 Subject: Add sigma params to infotext --- modules/generation_parameters_copypaste.py | 4 ++++ modules/sd_samplers_kdiffusion.py | 34 +++++++++++++++++++++++++++++- 2 files changed, 37 insertions(+), 1 deletion(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 593abfef..e71c9601 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -328,6 +328,10 @@ infotext_to_setting_name_mapping = [ ('Noise multiplier', 'initial_noise_multiplier'), ('Eta', 'eta_ancestral'), ('Eta DDIM', 'eta_ddim'), + ('Sigma churn', 's_churn'), + ('Sigma tmin', 's_tmin'), + ('Sigma tmax', 's_tmax'), + ('Sigma noise', 's_noise'), ('Discard penultimate sigma', 'always_discard_next_to_last_sigma'), ('UniPC variant', 'uni_pc_variant'), ('UniPC skip type', 'uni_pc_skip_type'), diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 8bb639f5..6f46da7c 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -4,6 +4,7 @@ import inspect import k_diffusion.sampling from modules import prompt_parser, devices, sd_samplers_common, sd_samplers_extra +from modules.processing import StableDiffusionProcessing from modules.shared import opts, state import modules.shared as shared from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback @@ -280,6 +281,14 @@ class KDiffusionSampler: self.last_latent = None self.s_min_uncond = None + # NOTE: These are also defined in the StableDiffusionProcessing class. + # They should have been here to begin with but we're going to + # leave that class __init__ signature alone. + self.s_churn = 0.0 + self.s_tmin = 0.0 + self.s_tmax = float('inf') + self.s_noise = 1.0 + self.conditioning_key = sd_model.model.conditioning_key def callback_state(self, d): @@ -314,7 +323,7 @@ class KDiffusionSampler: def number_of_needed_noises(self, p): return p.steps - def initialize(self, p): + def initialize(self, p: StableDiffusionProcessing): 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 @@ -335,6 +344,29 @@ class KDiffusionSampler: extra_params_kwargs['eta'] = self.eta + if len(self.extra_params) > 0: + s_churn = p.override_settings.get('s_churn', p.s_churn) + s_tmin = p.override_settings.get('s_tmin', p.s_tmin) + s_tmax = p.override_settings.get('s_tmax', p.s_tmax) + s_noise = p.override_settings.get('s_noise', p.s_noise) + + if s_churn != self.s_churn: + extra_params_kwargs['s_churn'] = s_churn + p.s_churn = s_churn + p.extra_generation_params['Sigma churn'] = s_churn + if s_tmin != self.s_tmin: + extra_params_kwargs['s_tmin'] = s_churn + p.s_tmin = s_tmin + p.extra_generation_params['Sigma tmin'] = s_tmin + if s_tmax != self.s_tmax: + extra_params_kwargs['s_tmax'] = s_churn + p.s_tmax = s_tmax + p.extra_generation_params['Sigma tmax'] = s_tmax + if s_noise != self.s_noise: + extra_params_kwargs['s_noise'] = s_churn + p.s_noise = s_noise + p.extra_generation_params['Sigma noise'] = s_noise + return extra_params_kwargs def get_sigmas(self, p, steps): -- cgit v1.2.3 From 4c72377bbf227276914c4012b339f0b3da8b366b Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Mon, 7 Aug 2023 09:42:13 +0300 Subject: Options in main UI update - correctly read values from pasted infotext - setting for column count - infotext paste: do not add a field to override settings if some other component is already handling it --- .../scripts/extra_options_section.py | 39 +++++++++++++++++----- modules/generation_parameters_copypaste.py | 5 +++ modules/shared.py | 2 +- 3 files changed, 37 insertions(+), 9 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/extensions-builtin/extra-options-section/scripts/extra_options_section.py b/extensions-builtin/extra-options-section/scripts/extra_options_section.py index 7bb0a1bb..d5c29bf2 100644 --- a/extensions-builtin/extra-options-section/scripts/extra_options_section.py +++ b/extensions-builtin/extra-options-section/scripts/extra_options_section.py @@ -1,5 +1,7 @@ +import math + import gradio as gr -from modules import scripts, shared, ui_components, ui_settings +from modules import scripts, shared, ui_components, ui_settings, generation_parameters_copypaste from modules.ui_components import FormColumn @@ -19,15 +21,33 @@ class ExtraOptionsSection(scripts.Script): def ui(self, is_img2img): self.comps = [] self.setting_names = [] + self.infotext_fields = [] + + mapping = {k: v for v, k in generation_parameters_copypaste.infotext_to_setting_name_mapping} with gr.Blocks() as interface: - with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(), gr.Row(): - for setting_name in shared.opts.extra_options: - with FormColumn(): - comp = ui_settings.create_setting_component(setting_name) + with gr.Accordion("Options", open=False) if shared.opts.extra_options_accordion and shared.opts.extra_options else gr.Group(): + + row_count = math.ceil(len(shared.opts.extra_options) / shared.opts.extra_options_cols) + + for row in range(row_count): + with gr.Row(): + for col in range(shared.opts.extra_options_cols): + index = row * shared.opts.extra_options_cols + col + if index >= len(shared.opts.extra_options): + break + + setting_name = shared.opts.extra_options[index] - self.comps.append(comp) - self.setting_names.append(setting_name) + with FormColumn(): + comp = ui_settings.create_setting_component(setting_name) + + self.comps.append(comp) + self.setting_names.append(setting_name) + + setting_infotext_name = mapping.get(setting_name) + if setting_infotext_name is not None: + self.infotext_fields.append((comp, setting_infotext_name)) def get_settings_values(): return [ui_settings.get_value_for_setting(key) for key in self.setting_names] @@ -44,5 +64,8 @@ class ExtraOptionsSection(scripts.Script): shared.options_templates.update(shared.options_section(('ui', "User interface"), { "extra_options": shared.OptionInfo([], "Options in main UI", ui_components.DropdownMulti, lambda: {"choices": list(shared.opts.data_labels.keys())}).js("info", "settingsHintsShowQuicksettings").info("setting entries that also appear in txt2img/img2img interfaces").needs_reload_ui(), - "extra_options_accordion": shared.OptionInfo(False, "Place options in main UI into an accordion").needs_restart() + "extra_options_cols": shared.OptionInfo(1, "Options in main UI - number of columns", gr.Number, {"precision": 0}).needs_reload_ui(), + "extra_options_accordion": shared.OptionInfo(False, "Options in main UI - place into an accordion").needs_reload_ui() })) + + diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index e71c9601..5758e6f3 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -414,10 +414,15 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, return res if override_settings_component is not None: + already_handled_fields = {key: 1 for _, key in paste_fields} + def paste_settings(params): vals = {} for param_name, setting_name in infotext_to_setting_name_mapping: + if param_name in already_handled_fields: + continue + v = params.get(param_name, None) if v is None: continue diff --git a/modules/shared.py b/modules/shared.py index 115e5276..4d854928 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -612,7 +612,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters" '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"), + '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)"), -- 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/generation_parameters_copypaste.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(""""""), - -})) - -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 33446acf47a8c3e0c0964782189562df3c4bcf4f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 12:41:41 +0300 Subject: face restoration and tiling moved to settings - use "Options in main UI" setting if you want them back --- modules/generation_parameters_copypaste.py | 2 ++ modules/img2img.py | 4 +--- modules/processing.py | 11 +++++++++-- modules/shared_options.py | 2 ++ modules/txt2img.py | 4 +--- modules/ui.py | 12 ++---------- 6 files changed, 17 insertions(+), 18 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index d932c67d..bdff3266 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -343,6 +343,8 @@ infotext_to_setting_name_mapping = [ ('Pad conds', 'pad_cond_uncond'), ('VAE Encoder', 'sd_vae_encode_method'), ('VAE Decoder', 'sd_vae_decode_method'), + ('Tiling', 'tiling'), + ('Face restoration', 'face_restoration'), ] diff --git a/modules/img2img.py b/modules/img2img.py index e06ac1d6..c7bbbac8 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -116,7 +116,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal process_images(p) -def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_name: str, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args): +def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_name: str, mask_blur: int, mask_alpha: float, inpainting_fill: int, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args): override_settings = create_override_settings_dict(override_settings_texts) is_batch = mode == 5 @@ -179,8 +179,6 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s cfg_scale=cfg_scale, width=width, height=height, - restore_faces=restore_faces, - tiling=tiling, init_images=[image], mask=mask, mask_blur=mask_blur, diff --git a/modules/processing.py b/modules/processing.py index 7819644c..68a8f1c6 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -111,7 +111,7 @@ class StableDiffusionProcessing: cached_uc = [None, None] cached_c = [None, None] - def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): + def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = None, tiling: bool = None, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): if sampler_index is not None: print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr) @@ -564,7 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "CFG scale": p.cfg_scale, "Image CFG scale": getattr(p, 'image_cfg_scale', None), "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index], - "Face restoration": (opts.face_restoration_model if p.restore_faces else None), + "Face restoration": opts.face_restoration_model if p.restore_faces else None, "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), @@ -580,6 +580,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Init image hash": getattr(p, 'init_img_hash', None), "RNG": opts.randn_source if opts.randn_source != "GPU" and opts.randn_source != "NV" else None, "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond, + "Tiling": "True" if p.tiling else None, **p.extra_generation_params, "Version": program_version() if opts.add_version_to_infotext else None, "User": p.user if opts.add_user_name_to_info else None, @@ -645,6 +646,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: seed = get_fixed_seed(p.seed) subseed = get_fixed_seed(p.subseed) + if p.restore_faces is None: + p.restore_faces = opts.face_restoration + + if p.tiling is None: + p.tiling = opts.tiling + modules.sd_hijack.model_hijack.apply_circular(p.tiling) modules.sd_hijack.model_hijack.clear_comments() diff --git a/modules/shared_options.py b/modules/shared_options.py index 7468bc81..f72859d9 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -92,6 +92,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), { })) options_templates.update(options_section(('face-restoration', "Face restoration"), { + "face_restoration": OptionInfo(False, "Restore faces").info("will use a third-party model on generation result to reconstruct faces"), "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"), @@ -138,6 +139,7 @@ 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"), + "tiling": OptionInfo(False, "Tiling").info("produce a tileable picture"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { diff --git a/modules/txt2img.py b/modules/txt2img.py index edad8930..5ea96bba 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_name: str, 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_name: str, 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_name: str, 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_name: str, 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( @@ -32,8 +32,6 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step cfg_scale=cfg_scale, width=width, height=height, - restore_faces=restore_faces, - tiling=tiling, enable_hr=enable_hr, denoising_strength=denoising_strength if enable_hr else None, hr_scale=hr_scale, diff --git a/modules/ui.py b/modules/ui.py index cbad3afe..09a826fd 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -432,8 +432,7 @@ def create_ui(): elif category == "checkboxes": with FormRow(elem_classes="checkboxes-row", variant="compact"): - restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces") - tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling") + pass elif category == "hires_fix": with InputAccordion(False, label="Hires. fix") as enable_hr: @@ -516,8 +515,6 @@ def create_ui(): toprow.ui_styles.dropdown, steps, sampler_name, - restore_faces, - tiling, batch_count, batch_size, cfg_scale, @@ -572,7 +569,6 @@ def create_ui(): (toprow.negative_prompt, "Negative prompt"), (steps, "Steps"), (sampler_name, "Sampler"), - (restore_faces, "Face restoration"), (cfg_scale, "CFG scale"), (seed, "Seed"), (width, "Size-1"), @@ -792,8 +788,7 @@ def create_ui(): elif category == "checkboxes": with FormRow(elem_classes="checkboxes-row", variant="compact"): - restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces") - tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling") + pass elif category == "batch": if not opts.dimensions_and_batch_together: @@ -866,8 +861,6 @@ def create_ui(): mask_blur, mask_alpha, inpainting_fill, - restore_faces, - tiling, batch_count, batch_size, cfg_scale, @@ -959,7 +952,6 @@ def create_ui(): (toprow.negative_prompt, "Negative prompt"), (steps, "Steps"), (sampler_name, "Sampler"), - (restore_faces, "Face restoration"), (cfg_scale, "CFG scale"), (image_cfg_scale, "Image CFG scale"), (seed, "Seed"), -- cgit v1.2.3 From 9d78d317ae492db59ebf8b31fda9a049f6c9bd14 Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:22:10 +0300 Subject: add VAE to infotext --- modules/generation_parameters_copypaste.py | 1 + modules/processing.py | 2 ++ modules/sd_vae.py | 16 +++++++++++++++- 3 files changed, 18 insertions(+), 1 deletion(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index bdff3266..6ace29cf 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -341,6 +341,7 @@ infotext_to_setting_name_mapping = [ ('RNG', 'randn_source'), ('NGMS', 's_min_uncond'), ('Pad conds', 'pad_cond_uncond'), + ('VAE', 'sd_vae'), ('VAE Encoder', 'sd_vae_encode_method'), ('VAE Decoder', 'sd_vae_decode_method'), ('Tiling', 'tiling'), diff --git a/modules/processing.py b/modules/processing.py index f06c374a..44d47e8c 100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -576,6 +576,8 @@ 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, "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}"), diff --git a/modules/sd_vae.py b/modules/sd_vae.py index 5ac1ac31..1db01992 100644 --- a/modules/sd_vae.py +++ b/modules/sd_vae.py @@ -2,7 +2,7 @@ import os import collections from dataclasses import dataclass -from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks, lowvram, sd_hijack +from modules import paths, shared, devices, script_callbacks, sd_models, extra_networks, lowvram, sd_hijack, hashes import glob from copy import deepcopy @@ -20,6 +20,20 @@ checkpoint_info = None checkpoints_loaded = collections.OrderedDict() +def get_loaded_vae_name(): + if loaded_vae_file is None: + return None + + return os.path.basename(loaded_vae_file) + + +def get_loaded_vae_hash(): + if loaded_vae_file is None: + return None + + return hashes.sha256(loaded_vae_file, 'vae')[0:10] + + def get_base_vae(model): if base_vae is not None and checkpoint_info == model.sd_checkpoint_info and model: return base_vae -- cgit v1.2.3 From 070b034cd5b49eb5056a18b43f88aa223fec9e0b Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Thu, 10 Aug 2023 16:42:26 +0300 Subject: put infotext label for setting into OptionInfo definition rather than in a separate list --- modules/generation_parameters_copypaste.py | 39 ++++++--------------- modules/options.py | 4 ++- modules/shared_options.py | 56 +++++++++++++++--------------- 3 files changed, 42 insertions(+), 57 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 6ace29cf..386517ac 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -316,37 +316,18 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model infotext_to_setting_name_mapping = [ - ('Clip skip', 'CLIP_stop_at_last_layers', ), + +] +"""Mapping of infotext labels to setting names. Only left for backwards compatibility - use OptionInfo(..., infotext='...') instead. +Example content: + +infotext_to_setting_name_mapping = [ ('Conditional mask weight', 'inpainting_mask_weight'), ('Model hash', 'sd_model_checkpoint'), ('ENSD', 'eta_noise_seed_delta'), ('Schedule type', 'k_sched_type'), - ('Schedule max sigma', 'sigma_max'), - ('Schedule min sigma', 'sigma_min'), - ('Schedule rho', 'rho'), - ('Noise multiplier', 'initial_noise_multiplier'), - ('Eta', 'eta_ancestral'), - ('Eta DDIM', 'eta_ddim'), - ('Sigma churn', 's_churn'), - ('Sigma tmin', 's_tmin'), - ('Sigma tmax', 's_tmax'), - ('Sigma noise', 's_noise'), - ('Discard penultimate sigma', 'always_discard_next_to_last_sigma'), - ('UniPC variant', 'uni_pc_variant'), - ('UniPC skip type', 'uni_pc_skip_type'), - ('UniPC order', 'uni_pc_order'), - ('UniPC lower order final', 'uni_pc_lower_order_final'), - ('Token merging ratio', 'token_merging_ratio'), - ('Token merging ratio hr', 'token_merging_ratio_hr'), - ('RNG', 'randn_source'), - ('NGMS', 's_min_uncond'), - ('Pad conds', 'pad_cond_uncond'), - ('VAE', 'sd_vae'), - ('VAE Encoder', 'sd_vae_encode_method'), - ('VAE Decoder', 'sd_vae_decode_method'), - ('Tiling', 'tiling'), - ('Face restoration', 'face_restoration'), ] +""" def create_override_settings_dict(text_pairs): @@ -367,7 +348,8 @@ def create_override_settings_dict(text_pairs): params[k] = v.strip() - for param_name, setting_name in infotext_to_setting_name_mapping: + mapping = [(info.infotext, k) for k, info in shared.opts.data_labels.items() if info.infotext] + for param_name, setting_name in mapping + infotext_to_setting_name_mapping: value = params.get(param_name, None) if value is None: @@ -421,7 +403,8 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component, def paste_settings(params): vals = {} - for param_name, setting_name in infotext_to_setting_name_mapping: + mapping = [(info.infotext, k) for k, info in shared.opts.data_labels.items() if info.infotext] + for param_name, setting_name in mapping + infotext_to_setting_name_mapping: if param_name in already_handled_fields: continue diff --git a/modules/options.py b/modules/options.py index 59cb75ec..db1fb157 100644 --- a/modules/options.py +++ b/modules/options.py @@ -8,7 +8,7 @@ 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=''): + def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after='', infotext=None): self.default = default self.label = label self.component = component @@ -24,6 +24,8 @@ class OptionInfo: self.comment_after = comment_after """HTML text that will be added before label in UI""" + self.infotext = infotext + def link(self, label, url): self.comment_before += f"[{label}]" return self diff --git a/modules/shared_options.py b/modules/shared_options.py index f72859d9..9ae51f18 100644 --- a/modules/shared_options.py +++ b/modules/shared_options.py @@ -92,7 +92,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), { })) options_templates.update(options_section(('face-restoration', "Face restoration"), { - "face_restoration": OptionInfo(False, "Restore faces").info("will use a third-party model on generation result to reconstruct faces"), + "face_restoration": OptionInfo(False, "Restore faces", infotext='Face restoration').info("will use a third-party model on generation result to reconstruct faces"), "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"), @@ -127,7 +127,7 @@ 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": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints), + "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext='Model hash'), "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"), @@ -136,10 +136,10 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), { "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"), + "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}, infotext="Clip skip").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"), - "tiling": OptionInfo(False, "Tiling").info("produce a tileable picture"), + "tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"), })) options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { @@ -157,16 +157,16 @@ image into latent space representation and back. Latent space representation is 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": OptionInfo("Automatic", "SD VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list, infotext='VAE').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"), + "sd_vae_encode_method": OptionInfo("Full", "VAE type for encode", gr.Radio, {"choices": ["Full", "TAESD"]}, infotext='VAE Encoder').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"]}, infotext='VAE Decoder').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}), + "inpainting_mask_weight": OptionInfo(1.0, "Inpainting conditioning mask strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Conditional mask weight'), + "initial_noise_multiplier": OptionInfo(1.0, "Noise multiplier for img2img", gr.Slider, {"minimum": 0.5, "maximum": 1.5, "step": 0.01}, infotext='Noise multiplier'), "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, {}), @@ -181,10 +181,10 @@ options_templates.update(options_section(('img2img', "img2img"), { 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": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}, infotext='Token merging ratio').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"), + "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}, infotext='Token merging ratio hr').info("only applies if non-zero and overrides above"), + "pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length", infotext='Pad conds').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"), })) @@ -284,23 +284,23 @@ 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 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"), + "eta_ddim": OptionInfo(0.0, "Eta for DDIM", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}, infotext='Eta DDIM').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}, infotext='Eta').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"), + 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 100.0, "step": 0.01}, infotext='Sigma churn').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}, infotext='Sigma tmin').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}, infotext='Sigma tmax').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}, infotext='Sigma noise').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"]}, infotext='Schedule type').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, infotext='Schedule max sigma').info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"), + 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number, infotext='Schedule min sigma').info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"), + 'rho': OptionInfo(0.0, "rho", gr.Number, infotext='Schedule rho').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}, infotext='ENSD').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", infotext='Discard penultimate 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"]}, infotext='UniPC variant'), + 'uni_pc_skip_type': OptionInfo("time_uniform", "UniPC skip type", gr.Radio, {"choices": ["time_uniform", "time_quadratic", "logSNR"]}, infotext='UniPC skip type'), + 'uni_pc_order': OptionInfo(3, "UniPC order", gr.Slider, {"minimum": 1, "maximum": 50, "step": 1}, infotext='UniPC order').info("must be < sampling steps"), + 'uni_pc_lower_order_final': OptionInfo(True, "UniPC lower order final", infotext='UniPC lower order final'), })) options_templates.update(options_section(('postprocessing', "Postprocessing"), { -- cgit v1.2.3 From bd5c16e8da5837b2b08fe6e329694553dd688a5f Mon Sep 17 00:00:00 2001 From: AUTOMATIC1111 <16777216c@gmail.com> Date: Sun, 27 Aug 2023 09:19:02 +0300 Subject: fix for Reload UI function: if you reload UI on one tab, other opened tabs will no longer stop working --- CHANGELOG.md | 1 + modules/generation_parameters_copypaste.py | 1 + 2 files changed, 2 insertions(+) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/CHANGELOG.md b/CHANGELOG.md index 5e78b3d2..1bbde234 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -130,6 +130,7 @@ * fix error that causes some extra networks to be disabled if both and are present in the prompt * fix defaults settings page breaking when any of main UI tabs are hidden * fix incorrect save/display of new values in Defaults page in settings + * fix for Reload UI function: if you reload UI on one tab, other opened tabs will no longer stop working ## 1.5.2 diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 386517ac..2ca16055 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -32,6 +32,7 @@ class ParamBinding: def reset(): paste_fields.clear() + registered_param_bindings.clear() def quote(text): -- cgit v1.2.3