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https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2026-03-14 09:28:12 +00:00
split shared.py into multiple files; should resolve all circular reference import errors related to shared.py
This commit is contained in:
AUTOMATIC1111
@@ -1,40 +1,12 @@
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import datetime
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import json
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import os
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import re
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import sys
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import threading
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import time
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import logging
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import gradio as gr
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import torch
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import tqdm
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import launch
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import modules.interrogate
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import modules.memmon
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import modules.styles
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import modules.devices as devices
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from modules import localization, script_loading, errors, ui_components, shared_items, cmd_args, rng # noqa: F401
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from modules import localization, ui_components, shared_items, shared, interrogate, shared_gradio_themes
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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
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from ldm.models.diffusion.ddpm import LatentDiffusion
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from typing import Optional
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log = logging.getLogger(__name__)
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demo = None
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parser = cmd_args.parser
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script_loading.preload_extensions(extensions_dir, parser, extension_list=launch.list_extensions(launch.args.ui_settings_file))
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script_loading.preload_extensions(extensions_builtin_dir, parser)
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if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None:
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cmd_opts = parser.parse_args()
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else:
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cmd_opts, _ = parser.parse_known_args()
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from modules.shared_cmd_options import cmd_opts
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from modules.options import options_section, OptionInfo, OptionHTML
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options_templates = {}
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hide_dirs = shared.hide_dirs
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restricted_opts = {
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"samples_filename_pattern",
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@@ -49,302 +21,6 @@ restricted_opts = {
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"outdir_init_images"
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}
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# https://huggingface.co/datasets/freddyaboulton/gradio-theme-subdomains/resolve/main/subdomains.json
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gradio_hf_hub_themes = [
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"gradio/base",
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"gradio/glass",
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"gradio/monochrome",
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"gradio/seafoam",
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"gradio/soft",
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"gradio/dracula_test",
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"abidlabs/dracula_test",
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"abidlabs/Lime",
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"abidlabs/pakistan",
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"Ama434/neutral-barlow",
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"dawood/microsoft_windows",
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"finlaymacklon/smooth_slate",
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"Franklisi/darkmode",
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"freddyaboulton/dracula_revamped",
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"freddyaboulton/test-blue",
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"gstaff/xkcd",
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"Insuz/Mocha",
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"Insuz/SimpleIndigo",
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"JohnSmith9982/small_and_pretty",
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"nota-ai/theme",
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"nuttea/Softblue",
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"ParityError/Anime",
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"reilnuud/polite",
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"remilia/Ghostly",
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"rottenlittlecreature/Moon_Goblin",
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"step-3-profit/Midnight-Deep",
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"Taithrah/Minimal",
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"ysharma/huggingface",
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"ysharma/steampunk"
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]
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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
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devices.device, devices.device_interrogate, devices.device_gfpgan, devices.device_esrgan, devices.device_codeformer = \
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(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'])
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devices.dtype = torch.float32 if cmd_opts.no_half else torch.float16
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devices.dtype_vae = torch.float32 if cmd_opts.no_half or cmd_opts.no_half_vae else torch.float16
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device = devices.device
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weight_load_location = None if cmd_opts.lowram else "cpu"
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batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram or cmd_opts.medvram)
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parallel_processing_allowed = not cmd_opts.lowvram and not cmd_opts.medvram
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xformers_available = False
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config_filename = cmd_opts.ui_settings_file
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os.makedirs(cmd_opts.hypernetwork_dir, exist_ok=True)
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hypernetworks = {}
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loaded_hypernetworks = []
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def reload_hypernetworks():
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from modules.hypernetworks import hypernetwork
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global hypernetworks
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hypernetworks = hypernetwork.list_hypernetworks(cmd_opts.hypernetwork_dir)
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class State:
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skipped = False
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interrupted = False
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job = ""
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job_no = 0
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job_count = 0
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processing_has_refined_job_count = False
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job_timestamp = '0'
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sampling_step = 0
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sampling_steps = 0
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current_latent = None
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current_image = None
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current_image_sampling_step = 0
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id_live_preview = 0
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textinfo = None
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time_start = None
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server_start = None
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_server_command_signal = threading.Event()
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_server_command: Optional[str] = None
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@property
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def need_restart(self) -> bool:
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# Compatibility getter for need_restart.
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return self.server_command == "restart"
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@need_restart.setter
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def need_restart(self, value: bool) -> None:
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# Compatibility setter for need_restart.
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if value:
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self.server_command = "restart"
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@property
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def server_command(self):
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return self._server_command
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@server_command.setter
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def server_command(self, value: Optional[str]) -> None:
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"""
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Set the server command to `value` and signal that it's been set.
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"""
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self._server_command = value
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self._server_command_signal.set()
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def wait_for_server_command(self, timeout: Optional[float] = None) -> Optional[str]:
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"""
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Wait for server command to get set; return and clear the value and signal.
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"""
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if self._server_command_signal.wait(timeout):
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self._server_command_signal.clear()
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req = self._server_command
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self._server_command = None
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return req
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return None
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def request_restart(self) -> None:
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self.interrupt()
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self.server_command = "restart"
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log.info("Received restart request")
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def skip(self):
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self.skipped = True
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log.info("Received skip request")
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def interrupt(self):
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self.interrupted = True
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log.info("Received interrupt request")
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def nextjob(self):
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if opts.live_previews_enable and opts.show_progress_every_n_steps == -1:
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self.do_set_current_image()
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self.job_no += 1
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self.sampling_step = 0
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self.current_image_sampling_step = 0
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def dict(self):
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obj = {
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"skipped": self.skipped,
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"interrupted": self.interrupted,
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"job": self.job,
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"job_count": self.job_count,
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"job_timestamp": self.job_timestamp,
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"job_no": self.job_no,
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"sampling_step": self.sampling_step,
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"sampling_steps": self.sampling_steps,
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}
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return obj
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def begin(self, job: str = "(unknown)"):
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self.sampling_step = 0
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self.job_count = -1
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self.processing_has_refined_job_count = False
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self.job_no = 0
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self.job_timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
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self.current_latent = None
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self.current_image = None
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self.current_image_sampling_step = 0
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self.id_live_preview = 0
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self.skipped = False
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self.interrupted = False
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self.textinfo = None
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self.time_start = time.time()
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self.job = job
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devices.torch_gc()
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log.info("Starting job %s", job)
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def end(self):
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duration = time.time() - self.time_start
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log.info("Ending job %s (%.2f seconds)", self.job, duration)
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self.job = ""
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self.job_count = 0
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devices.torch_gc()
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def set_current_image(self):
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"""sets self.current_image from self.current_latent if enough sampling steps have been made after the last call to this"""
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if not parallel_processing_allowed:
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return
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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:
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self.do_set_current_image()
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def do_set_current_image(self):
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if self.current_latent is None:
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return
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import modules.sd_samplers
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try:
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if opts.show_progress_grid:
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self.assign_current_image(modules.sd_samplers.samples_to_image_grid(self.current_latent))
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else:
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self.assign_current_image(modules.sd_samplers.sample_to_image(self.current_latent))
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self.current_image_sampling_step = self.sampling_step
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except Exception:
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# when switching models during genration, VAE would be on CPU, so creating an image will fail.
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# we silently ignore this error
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errors.record_exception()
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def assign_current_image(self, image):
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self.current_image = image
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self.id_live_preview += 1
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state = State()
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state.server_start = time.time()
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styles_filename = cmd_opts.styles_file
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prompt_styles = modules.styles.StyleDatabase(styles_filename)
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interrogator = modules.interrogate.InterrogateModels("interrogate")
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face_restorers = []
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class OptionInfo:
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def __init__(self, default=None, label="", component=None, component_args=None, onchange=None, section=None, refresh=None, comment_before='', comment_after=''):
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self.default = default
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self.label = label
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self.component = component
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self.component_args = component_args
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self.onchange = onchange
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self.section = section
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self.refresh = refresh
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self.do_not_save = False
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self.comment_before = comment_before
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"""HTML text that will be added after label in UI"""
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self.comment_after = comment_after
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"""HTML text that will be added before label in UI"""
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def link(self, label, url):
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self.comment_before += f"[<a href='{url}' target='_blank'>{label}</a>]"
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return self
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def js(self, label, js_func):
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self.comment_before += f"[<a onclick='{js_func}(); return false'>{label}</a>]"
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return self
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def info(self, info):
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self.comment_after += f"<span class='info'>({info})</span>"
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return self
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def html(self, html):
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self.comment_after += html
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return self
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def needs_restart(self):
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self.comment_after += " <span class='info'>(requires restart)</span>"
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return self
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def needs_reload_ui(self):
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self.comment_after += " <span class='info'>(requires Reload UI)</span>"
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return self
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class OptionHTML(OptionInfo):
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def __init__(self, text):
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super().__init__(str(text).strip(), label='', component=lambda **kwargs: gr.HTML(elem_classes="settings-info", **kwargs))
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self.do_not_save = True
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def options_section(section_identifier, options_dict):
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for v in options_dict.values():
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v.section = section_identifier
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return options_dict
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def list_checkpoint_tiles():
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import modules.sd_models
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return modules.sd_models.checkpoint_tiles()
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def refresh_checkpoints():
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import modules.sd_models
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return modules.sd_models.list_models()
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def list_samplers():
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import modules.sd_samplers
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return modules.sd_samplers.all_samplers
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hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config}
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tab_names = []
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options_templates = {}
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options_templates.update(options_section(('saving-images', "Saving images/grids"), {
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"samples_save": OptionInfo(True, "Always save all generated images"),
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"samples_format": OptionInfo('png', 'File format for images'),
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@@ -412,11 +88,11 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
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"ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}).info("0 = no tiling"),
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"ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap for ESRGAN upscalers.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}).info("Low values = visible seam"),
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"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()}),
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"upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
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"upscaler_for_img2img": OptionInfo(None, "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in shared.sd_upscalers]}),
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}))
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options_templates.update(options_section(('face-restoration', "Face restoration"), {
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"face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in face_restorers]}),
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"face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in shared.face_restorers]}),
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"code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"),
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"face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
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}))
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@@ -450,7 +126,7 @@ options_templates.update(options_section(('training', "Training"), {
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}))
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options_templates.update(options_section(('sd', "Stable Diffusion"), {
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"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
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"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints),
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"sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}),
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"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"),
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"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"),
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@@ -526,7 +202,7 @@ options_templates.update(options_section(('interrogate', "Interrogate"), {
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"interrogate_clip_min_length": OptionInfo(24, "BLIP: minimum description length", gr.Slider, {"minimum": 1, "maximum": 128, "step": 1}),
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"interrogate_clip_max_length": OptionInfo(48, "BLIP: maximum description length", gr.Slider, {"minimum": 1, "maximum": 256, "step": 1}),
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"interrogate_clip_dict_limit": OptionInfo(1500, "CLIP: maximum number of lines in text file").info("0 = No limit"),
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"interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": modules.interrogate.category_types()}, refresh=modules.interrogate.category_types),
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"interrogate_clip_skip_categories": OptionInfo([], "CLIP: skip inquire categories", gr.CheckboxGroup, lambda: {"choices": interrogate.category_types()}, refresh=interrogate.category_types),
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"interrogate_deepbooru_score_threshold": OptionInfo(0.5, "deepbooru: score threshold", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}),
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"deepbooru_sort_alpha": OptionInfo(True, "deepbooru: sort tags alphabetically").info("if not: sort by score"),
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"deepbooru_use_spaces": OptionInfo(True, "deepbooru: use spaces in tags").info("if not: use underscores"),
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@@ -546,12 +222,12 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
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"ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_reload_ui(),
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"textual_inversion_print_at_load": OptionInfo(False, "Print a list of Textual Inversion embeddings when loading model"),
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"textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"),
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"sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks),
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"sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *shared.hypernetworks]}, refresh=shared_items.reload_hypernetworks),
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}))
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options_templates.update(options_section(('ui', "User interface"), {
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"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(),
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"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 <a href='https://huggingface.co/spaces/gradio/theme-gallery'>gallery</a>.").needs_reload_ui(),
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"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 <a href='https://huggingface.co/spaces/gradio/theme-gallery'>gallery</a>.").needs_reload_ui(),
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"gradio_themes_cache": OptionInfo(True, "Cache gradio themes locally").info("disable to update the selected Gradio theme"),
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"return_grid": OptionInfo(True, "Show grid in results for web"),
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"do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
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@@ -568,9 +244,9 @@ options_templates.update(options_section(('ui', "User interface"), {
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"keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", 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)
|
||||
|
||||
Reference in New Issue
Block a user