jumbo patch

TODO.md

@@ -63,3 +63,5 @@ Tech that can be integrated as part of the core workflow...
 
 - ability to view/add/edit model description shown in extra networks cards
 - add option to specify fallback sampler if primary sampler is not compatible with desired operation
+- make clip skip a local parameter
+- remove obsolete items from settings

javascript/ui.js

@@ -338,6 +338,28 @@ function reconnect_ui() {
     const atEnd = () => showSubmitButtons('txt2img', true)
     requestProgress(task_id, el1, el2, atEnd, null, true)
   }
+
+  sd_model = gradioApp().getElementById("setting_sd_model_checkpoint")
+  let loadingStarted = 0;
+  let loadingMonitor = 0;
+  const sd_model_callback = () => {
+    loading = sd_model.querySelector(".eta-bar")
+    if (!loading) {
+      loadingStarted = 0
+      clearInterval(loadingMonitor)
+    } else {
+      if (loadingStarted === 0) {
+        loadingStarted = Date.now();
+        loadingMonitor = setInterval(() => {
+          elapsed = Date.now() - loadingStarted;
+          console.log('Loading', elapsed)
+          if (elapsed > 3000 && loading) loading.style.display = 'none';
+        }, 5000);
+      }
+    }
+  };
+  const sd_model_observer = new MutationObserver(sd_model_callback);
+  sd_model_observer.observe(sd_model, { attributes: true, childList: true, subtree: true });
 }
 
-var start_check = setInterval(reconnect_ui, 50)
+var start_check = setInterval(reconnect_ui, 50);

modules/generation_parameters_copypaste.py

@@ -11,7 +11,7 @@ from modules import shared, ui_tempdir, script_callbacks
 re_param_code = r'\s*([\w ]+):\s*("(?:\\"[^,]|\\"|\\|[^\"])+"|[^,]*)(?:,|$)'
 re_param = re.compile(re_param_code)
 re_imagesize = re.compile(r"^(\d+)x(\d+)$")
-re_hypernet_hash = re.compile("\(([0-9a-f]+)\)$")
+re_hypernet_hash = re.compile("\(([0-9a-f]+)\)$") # pylint: disable=anomalous-backslash-in-string
 type_of_gr_update = type(gr.update())
 
 paste_fields = {}
@@ -102,7 +102,6 @@ def bind_buttons(buttons, send_image, send_generate_info):
     for tabname, button in buttons.items():
         source_text_component = send_generate_info if isinstance(send_generate_info, gr.components.Component) else None
         source_tabname = send_generate_info if isinstance(send_generate_info, str) else None
-
         register_paste_params_button(ParamBinding(paste_button=button, tabname=tabname, source_text_component=source_text_component, source_image_component=send_image, source_tabname=source_tabname))
 
 
@@ -116,7 +115,6 @@ def connect_paste_params_buttons():
         destination_image_component = paste_fields[binding.tabname]["init_img"]
         fields = paste_fields[binding.tabname]["fields"]
         override_settings_component = binding.override_settings_component or paste_fields[binding.tabname]["override_settings_component"]
-
         destination_width_component = next(iter([field for field, name in fields if name == "Size-1"] if fields else []), None)
         destination_height_component = next(iter([field for field, name in fields if name == "Size-2"] if fields else []), None)
 
@@ -127,17 +125,14 @@ def connect_paste_params_buttons():
             else:
                 func = send_image_and_dimensions if destination_width_component else lambda x: x
                 jsfunc = None
-
             binding.paste_button.click(
                 fn=func,
                 _js=jsfunc,
                 inputs=[binding.source_image_component],
                 outputs=[destination_image_component, destination_width_component, destination_height_component] if destination_width_component else [destination_image_component],
             )
-
         if binding.source_text_component is not None and fields is not None:
             connect_paste(binding.paste_button, fields, binding.source_text_component, override_settings_component, binding.tabname)
-
         if binding.source_tabname is not None and fields is not None:
             paste_field_names = ['Prompt', 'Negative prompt', 'Steps', 'Face restoration'] + (["Seed"] if shared.opts.send_seed else []) + binding.paste_field_names
             binding.paste_button.click(
@@ -145,7 +140,6 @@ def connect_paste_params_buttons():
                 inputs=[field for field, name in paste_fields[binding.source_tabname]["fields"] if name in paste_field_names],
                 outputs=[field for field, name in fields if name in paste_field_names],
             )
-
         binding.paste_button.click(
             fn=None,
             _js=f"switch_to_{binding.tabname}",
@@ -159,14 +153,12 @@ def send_image_and_dimensions(x):
         img = x
     else:
         img = image_from_url_text(x)
-
     if shared.opts.send_size and isinstance(img, Image.Image):
         w = img.width
         h = img.height
     else:
         w = gr.update()
         h = gr.update()
-
     return img, w, h
 
 
@@ -238,33 +230,25 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
 
     returns a dict with field values
     """
-
     res = {}
-
     prompt = ""
     negative_prompt = ""
-
     done_with_prompt = False
-
     *lines, lastline = x.strip().split("\n")
     if len(re_param.findall(lastline)) < 3:
         lines.append(lastline)
         lastline = ''
-
     for _i, line in enumerate(lines):
         line = line.strip()
         if line.startswith("Negative prompt:"):
             done_with_prompt = True
             line = line[16:].strip()
-
         if done_with_prompt:
             negative_prompt += ("" if negative_prompt == "" else "\n") + line
         else:
             prompt += ("" if prompt == "" else "\n") + line
-
     res["Prompt"] = prompt
     res["Negative prompt"] = negative_prompt
-
     for k, v in re_param.findall(lastline):
         v = v[1:-1] if v[0] == '"' and v[-1] == '"' else v
         m = re_imagesize.match(v)
@@ -273,31 +257,24 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
             res[k+"-2"] = m.group(2)
         else:
             res[k] = v
-
     # Missing CLIP skip means it was set to 1 (the default)
     if "Clip skip" not in res:
         res["Clip skip"] = "1"
-
     hypernet = res.get("Hypernet", None)
     if hypernet is not None:
         res["Prompt"] += f"""<hypernet:{hypernet}:{res.get("Hypernet strength", "1.0")}>"""
-
     if "Hires resize-1" not in res:
         res["Hires resize-1"] = 0
         res["Hires resize-2"] = 0
-
     # Infer additional override settings for token merging
     token_merging_ratio = res.get("Token merging ratio", None)
     token_merging_ratio_hr = res.get("Token merging ratio hr", None)
-
     if token_merging_ratio is not None or token_merging_ratio_hr is not None:
         res["Token merging"] = 'True'
-
         if token_merging_ratio is None:
             res["Token merging hr only"] = 'True'
         else:
             res["Token merging hr only"] = 'False'
-
         if res.get("Token merging random", None) is None:
             res["Token merging random"] = 'False'
         if res.get("Token merging merge attention", None) is None:
@@ -312,14 +289,12 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
             res["Token merging stride y"] = '2'
 
     restore_old_hires_fix_params(res)
-
     return res
 
 
 settings_map = {}
 
 
-
 infotext_to_setting_name_mapping = [
     ('Clip skip', 'CLIP_stop_at_last_layers', ),
     ('Conditional mask weight', 'inpainting_mask_weight'),
@@ -349,34 +324,29 @@ infotext_to_setting_name_mapping = [
 
 def create_override_settings_dict(text_pairs):
     """creates processing's override_settings parameters from gradio's multiselect
-
     Example input:
         ['Clip skip: 2', 'Model hash: e6e99610c4', 'ENSD: 31337']
 
     Example output:
         {'CLIP_stop_at_last_layers': 2, 'sd_model_checkpoint': 'e6e99610c4', 'eta_noise_seed_delta': 31337}
     """
-
     res = {}
     params = {}
     for pair in text_pairs:
         k, v = pair.split(":", maxsplit=1)
-
         params[k] = v.strip()
-
     for param_name, setting_name in infotext_to_setting_name_mapping:
         value = params.get(param_name, None)
-
         if value is None:
             continue
-
         res[setting_name] = shared.opts.cast_value(setting_name, value)
-
     return res
 
 
-def connect_paste(button, paste_fields, input_comp, override_settings_component, tabname):
+def connect_paste(button, paste_fields, input_comp, override_settings_component, tabname): # pylint: disable=redefined-outer-name
     def paste_func(prompt):
+        if 'Negative prompt' not in prompt and 'Steps' not in prompt:
+            prompt = None
         if not prompt and not shared.cmd_opts.hide_ui_dir_config:
             filename = os.path.join(data_path, "params.txt")
             if os.path.exists(filename):
@@ -384,17 +354,14 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
                     prompt = file.read()
             else:
                 prompt = ''
-
         params = parse_generation_parameters(prompt)
         script_callbacks.infotext_pasted_callback(prompt, params)
         res = []
-
         for output, key in paste_fields:
             if callable(key):
                 v = key(params)
             else:
                 v = params.get(key, None)
-
             if v is None:
                 res.append(gr.update())
             elif isinstance(v, type_of_gr_update):
@@ -402,42 +369,31 @@ def connect_paste(button, paste_fields, input_comp, override_settings_component,
             else:
                 try:
                     valtype = type(output.value)
-
                     if valtype == bool and v == "False":
                         val = False
                     else:
                         val = valtype(v)
-
                     res.append(gr.update(value=val))
                 except Exception:
                     res.append(gr.update())
-
         return res
 
     if override_settings_component is not None:
         def paste_settings(params):
             vals = {}
-
             for param_name, setting_name in infotext_to_setting_name_mapping:
                 v = params.get(param_name, None)
                 if v is None:
                     continue
-
                 if setting_name == "sd_model_checkpoint" and shared.opts.disable_weights_auto_swap:
                     continue
-
                 v = shared.opts.cast_value(setting_name, v)
                 current_value = getattr(shared.opts, setting_name, None)
-
                 if v == current_value:
                     continue
-
                 vals[param_name] = v
-
             vals_pairs = [f"{k}: {v}" for k, v in vals.items()]
-
             return gr.Dropdown.update(value=vals_pairs, choices=vals_pairs, visible=len(vals_pairs) > 0)
-
         paste_fields = paste_fields + [(override_settings_component, paste_settings)]
 
     button.click(

modules/processing.py

@@ -111,7 +111,7 @@ class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
-    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_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
+    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 = 20, cfg_scale: float = 6.0, 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_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
         if sampler_index is not None:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -165,6 +165,7 @@ class StableDiffusionProcessing:
         self.all_negative_prompts = None
         self.all_seeds = None
         self.all_subseeds = None
+        self.clip_skip = opts.CLIP_stop_at_last_layers
         self.iteration = 0
 
     @property
@@ -302,8 +303,7 @@ class Processed:
         self.index_of_first_image = index_of_first_image
         self.styles = p.styles
         self.job_timestamp = state.job_timestamp
-        self.clip_skip = opts.CLIP_stop_at_last_layers
-
+        self.clip_skip = p.clip_skip
         self.eta = p.eta
         self.ddim_discretize = p.ddim_discretize
         self.s_churn = p.s_churn
@@ -457,11 +457,9 @@ def fix_seed(p):
     p.subseed = get_fixed_seed(p.subseed)
 
 
-def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0): # pylint: disable=unused-argument
+def create_infotext(p: StableDiffusionProcessing, all_prompts, all_seeds, all_subseeds, comments=None, iteration=0, position_in_batch=0): # pylint: disable=unused-argument
     index = position_in_batch + iteration * p.batch_size
 
-    clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
-
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
@@ -478,7 +476,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "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}"),
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
-        "Clip skip": None if clip_skip <= 1 else clip_skip,
+        "Clip skip": p.clip_skip,
         "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
         "Token merging ratio": None if not (opts.token_merging or cmd_opts.token_merging) or opts.token_merging_hr_only else opts.token_merging_ratio,
         "Token merging ratio hr": None if not (opts.token_merging or cmd_opts.token_merging) else opts.token_merging_ratio_hr,

modules/sd_hijack_clip.py

@@ -205,7 +205,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
         is when you do prompt editing: "a picture of a [cat:dog:0.4] eating ice cream"
         """
 
-        batch_chunks, token_count = self.process_texts(texts)
+        batch_chunks, _token_count = self.process_texts(texts)
 
         used_embeddings = {}
         chunk_count = max([len(x) for x in batch_chunks])
@@ -219,7 +219,7 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
             self.hijack.fixes = [x.fixes for x in batch_chunk]
 
             for fixes in self.hijack.fixes:
-                for position, embedding in fixes:
+                for _position, embedding in fixes:
                     used_embeddings[embedding.name] = embedding
 
             z = self.process_tokens(tokens, multipliers)

modules/shared.py

@@ -3,10 +3,8 @@ import sys
 import time
 import json
 import datetime
-
 import gradio as gr
 import tqdm
-
 import modules.interrogate
 import modules.memmon
 import modules.styles
@@ -21,7 +19,6 @@ demo: gr.Blocks = None
 log = setup_log
 parser = cmd_args.parser
 url = 'https://github.com/vladmandic/automatic'
-
 if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None:
     cmd_opts = parser.parse_args()
 else:
@@ -53,10 +50,7 @@ ui_reorder_categories = [
 ]
 
 cmd_opts.disable_extension_access = (cmd_opts.share or cmd_opts.listen or cmd_opts.server_name) and not cmd_opts.enable_insecure
-
-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.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'])
 device = devices.device
 sd_upscalers = []
 sd_model = None
@@ -97,7 +91,6 @@ class State:
     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
@@ -129,13 +122,11 @@ class State:
         self.interrupted = False
         self.textinfo = None
         self.time_start = time.time()
-
         devices.torch_gc()
 
     def end(self):
         self.job = ""
         self.job_count = 0
-
         devices.torch_gc()
 
     def set_current_image(self):
@@ -162,9 +153,7 @@ class State:
 
 state = State()
 state.server_start = time.time()
-
 interrogator = modules.interrogate.InterrogateModels("interrogate")
-
 face_restorers = []
 
 class OptionInfo:
@@ -181,7 +170,6 @@ class OptionInfo:
 def options_section(section_identifier, options_dict):
     for _k, v in options_dict.items():
         v.section = section_identifier
-
     return options_dict
 
 
@@ -227,26 +215,25 @@ def refresh_themes():
 
 hide_dirs = {"visible": not cmd_opts.hide_ui_dir_config}
 tab_names = []
-
 options_templates = {}
 default_checkpoint = list_checkpoint_tiles()[0] if len(list_checkpoint_tiles()) > 0 else "model.ckpt"
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sd_model_checkpoint": OptionInfo(default_checkpoint, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
-    "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
-    "sd_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),
-    "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them"),
+    "sd_checkpoint_cache": OptionInfo(0, "Model checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
+    "sd_vae_checkpoint_cache": OptionInfo(0, "VAE checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
+    "sd_vae": OptionInfo("Automatic", "Select VAE", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list),
+    "sd_vae_as_default": OptionInfo(True, "Ignore selected VAE for stable diffusion checkpoints that have their own .vae.pt next to them", gr.Checkbox, {"visible": False}),
     "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 (normally you'd do less with less denoising)."),
+    "img2img_fix_steps": OptionInfo(False, "For image processing do exactly the amount of steps as specified."),
     "img2img_background_color": OptionInfo("#ffffff", "With img2img, fill image's transparent parts with this color.", ui_components.FormColorPicker, {}),
     "enable_quantization": OptionInfo(True, "Enable quantization in K samplers for sharper and cleaner results. This may change existing seeds."),
-    "enable_emphasis": OptionInfo(True, "Emphasis: 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"),
+    "enable_emphasis": OptionInfo(True, "Emphasis: use (text) to make model pay more attention to text and [text] to make it pay less attention", gr.Checkbox, {"visible": False}),
+    "enable_batch_seeds": OptionInfo(True, "Make K-diffusion samplers produce same images in a batch as when making a single image", gr.Checkbox, {"visible": False}),
     "comma_padding_backtrack": OptionInfo(20, "Increase coherency by padding from the last comma within n tokens when using more than 75 tokens", gr.Slider, {"minimum": 0, "maximum": 74, "step": 1 }),
-    "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}),
+    "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1, "visible": False}),
     "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
     "cross_attention_optimization": OptionInfo("Scaled-Dot-Product", "Cross-attention optimization method", gr.Radio, lambda: {"choices": shared_items.list_crossattention() }),
     "cross_attention_options": OptionInfo([], "Cross-attention advanced options", gr.CheckboxGroup, lambda: {"choices": ['xFormers enable flash Attention', 'SDP disable memory attention']}),
@@ -254,6 +241,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "sub_quad_kv_chunk_size": OptionInfo(512, "Sub-quadratic cross-attentionkv chunk size for the sub-quadratic cross-attention layer optimization to use", gr.Slider, {"minimum": 0, "maximum": 8192, "step": 8}),
     "sub_quad_chunk_threshold": OptionInfo(80, "Sub-quadratic cross-attention percentage of VRAM chunking threshold", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1}),
     "always_batch_cond_uncond": OptionInfo(False, "Disables cond/uncond batching that is enabled to save memory with --medvram or --lowvram"),
+    "multiple_tqdm": OptionInfo(False, "Add a second progress bar to the console that shows progress for an entire job.", gr.Checkbox, {"visible": False}),
+    "print_hypernet_extra": OptionInfo(False, "Print extra hypernetwork information to console.", gr.Checkbox, {"visible": False}),
 }))
 
 options_templates.update(options_section(('system-paths', "System Paths"), {
@@ -322,6 +311,7 @@ options_templates.update(options_section(('saving-paths', "Image Paths"), {
 }))
 
 options_templates.update(options_section(('cuda', "CUDA Settings"), {
+    "memmon_poll_rate": OptionInfo(2, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
     "precision": OptionInfo("Autocast", "Precision type", gr.Radio, lambda: {"choices": ["Autocast", "Full"]}),
     "cuda_dtype": OptionInfo("FP32" if sys.platform == "darwin" else "FP16", "Device precision type", gr.Radio, lambda: {"choices": ["FP32", "FP16", "BF16"]}),
     "no_half": OptionInfo(False, "Use full precision for model (--no-half)"),
@@ -341,7 +331,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
     "ESRGAN_tile": OptionInfo(192, "Tile size for ESRGAN upscalers. 0 = no tiling.", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}),
     "ESRGAN_tile_overlap": OptionInfo(8, "Tile overlap, in pixels for ESRGAN upscalers. Low values = visible seam.", gr.Slider, {"minimum": 0, "maximum": 48, "step": 1}),
     "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("SwinIR_4x", "Upscaler for img2img", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
+    "upscaler_for_img2img": OptionInfo("None", "Default upscaler for image resize operations", gr.Dropdown, lambda: {"choices": [x.name for x in sd_upscalers]}),
     "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."),
 }))
@@ -352,12 +342,6 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
     "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
 }))
 
-options_templates.update(options_section(('system', "System"), {
-    "memmon_poll_rate": OptionInfo(2, "VRAM usage polls per second during generation. Set to 0 to disable.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}),
-    "multiple_tqdm": OptionInfo(False, "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."),
-}))
-
 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(True, "Turn on pin_memory for DataLoader. Makes training slightly faster but can increase memory usage."),
@@ -404,13 +388,13 @@ options_templates.update(options_section(('ui', "User interface"), {
     "do_not_show_images": OptionInfo(False, "Do not show any images in results for web"),
     "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"),
-    "disable_weights_auto_swap": OptionInfo(True, "When reading generation parameters from text into UI (from PNG info or pasted text), do not change the selected model/checkpoint."),
+    "disable_weights_auto_swap": OptionInfo(True, "Do not change the selected model when reading generation parameters."),
     "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"),
     "font": OptionInfo("", "Font for image grids that have text"),
-    "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"),
-    "show_progress_in_title": OptionInfo(False, "Show generation progress in window title."),
+    "js_modal_lightbox": OptionInfo(True, "Enable full page image viewer", gr.Checkbox, {"visible": False}),
+    "js_modal_lightbox_initially_zoomed": OptionInfo(True, "Show images zoomed in by default in full page image viewer", gr.Checkbox, {"visible": False}),
+    "show_progress_in_title": OptionInfo(False, "Show generation progress in window title.", gr.Checkbox, {"visible": False}),
     "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 <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
     "quicksettings": OptionInfo("sd_model_checkpoint", "Quicksettings list"),
@@ -486,17 +470,14 @@ class Options:
     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)
-                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.freeze_settings:
+                    print(f'Settings are frozen: {key}')
+                    return
                 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
+                    print(f'Settings key is restricted: {key}')
+                    return
+                else:
+                    self.data[key] = value
                 return
 
         return super(Options, self).__setattr__(key, value)
@@ -505,24 +486,19 @@ class Options:
         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
-
         try:
             setattr(self, key, value)
         except RuntimeError:
             return False
-
         if self.data_labels[key].onchange is not None:
             try:
                 self.data_labels[key].onchange()
@@ -530,37 +506,30 @@ class Options:
                 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)
-
         bad_settings = 0
         for k, v in self.data.items():
             info = self.data_labels.get(k, None)
@@ -574,7 +543,6 @@ class Options:
     def onchange(self, key, func, call=True):
         item = self.data_labels.get(key)
         item.onchange = func
-
         if call:
             func()
 
@@ -587,13 +555,11 @@ class Options:
 
     def reorder(self):
         """reorder settings so that all items related to section always go together"""
-
         section_ids = {}
         settings_items = self.data_labels.items()
         for k, item in settings_items:
             if item.section not in section_ids:
                 section_ids[item.section] = len(section_ids)
-
         self.data_labels = {k: v for k, v in sorted(settings_items, key=lambda x: section_ids[x[1].section])}
 
     def cast_value(self, key, value):
@@ -619,27 +585,20 @@ class Options:
         return value
 
 
-
 opts = Options()
-
 batch_cond_uncond = 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(opts.hypernetwork_dir, exist_ok=True)
 hypernetworks = {}
 loaded_hypernetworks = []
-
 if os.path.exists(config_filename):
     opts.load(config_filename)
-
 cmd_opts = cmd_args.compatibility_args(opts, cmd_opts)
 prompt_styles = modules.styles.StyleDatabase(opts.styles_dir)
-
 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},
@@ -649,11 +608,10 @@ latent_upscale_modes = {
     "Latent (nearest)": {"mode": "nearest", "antialias": False},
     "Latent (nearest-exact)": {"mode": "nearest-exact", "antialias": False},
 }
-
 progress_print_out = sys.stdout
-
 gradio_theme = gr.themes.Base()
 
+
 def reload_gradio_theme(theme_name=None):
     global gradio_theme # pylint: disable=global-statement
     if not theme_name:
@@ -714,7 +672,6 @@ class TotalTQDM:
 
 
 total_tqdm = TotalTQDM()
-
 mem_mon = modules.memmon.MemUsageMonitor("MemMon", device, opts)
 mem_mon.start()
 

modules/txt2img.py

@@ -7,8 +7,8 @@ import modules.shared as shared
 from modules.ui import plaintext_to_html
 
 
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args):
-    override_settings = create_override_settings_dict(override_settings_texts) # pylint: disable=unused-argument
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_index: int, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, height: int, width: int, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, override_settings_texts, *args): # pylint: disable=unused-argument
+    override_settings = create_override_settings_dict(override_settings_texts)
     p = StableDiffusionProcessingTxt2Img(
         sd_model=shared.sd_model,
         outpath_samples=opts.outdir_samples or opts.outdir_txt2img_samples,

modules/ui.py

@@ -81,34 +81,25 @@ def visit(x, func, path=""):
 def add_style(name: str, prompt: str, negative_prompt: str):
     if name is None:
         return [gr_show() for x in range(4)]
-
     style = modules.styles.PromptStyle(name, prompt, negative_prompt)
     shared.prompt_styles.styles[style.name] = style
-    # Save all loaded prompt styles: this allows us to update the storage format in the future more easily, because we
-    # reserialize all styles every time we save them
     shared.prompt_styles.save_styles(shared.opts.styles_dir)
-
     return [gr.Dropdown.update(visible=True, choices=list(shared.prompt_styles.styles)) for _ in range(2)]
 
 
 def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resize_y):
     from modules import processing, devices
-
     if not enable:
         return ""
-
     p = processing.StableDiffusionProcessingTxt2Img(width=width, height=height, enable_hr=True, hr_scale=hr_scale, hr_resize_x=hr_resize_x, hr_resize_y=hr_resize_y)
-
     with devices.autocast():
         p.init([""], [0], [0])
-
     return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
 
 
 def apply_styles(prompt, prompt_neg, styles):
     prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles)
     prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles)
-
     return [gr.Textbox.update(value=prompt), gr.Textbox.update(value=prompt_neg), gr.Dropdown.update(value=[])]
 
 
@@ -125,7 +116,6 @@ def process_interrogate(interrogation_function, mode, ii_input_dir, ii_output_di
             os.makedirs(ii_output_dir, exist_ok=True)
         else:
             ii_output_dir = ii_input_dir
-
         for image in images:
             img = Image.open(image)
             filename = os.path.basename(image)
@@ -144,44 +134,35 @@ def interrogate_deepbooru(image):
     prompt = deepbooru.model.tag(image)
     return gr.update() if prompt is None else prompt
 
+
 def change_clip_skip(val):
     shared.opts.CLIP_stop_at_last_layers = val
 
+
 def create_seed_inputs(target_interface):
     with FormRow(elem_id=target_interface + '_seed_row', variant="compact"):
         seed = gr.Number(label='Seed', value=-1, elem_id=target_interface + '_seed')
         seed.style(container=False)
         random_seed = ToolButton(random_symbol, elem_id=target_interface + '_random_seed')
         reuse_seed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_seed')
-
         seed_checkbox = gr.Checkbox(label='Extra', elem_id=target_interface + '_subseed_show', value=False, visible=False)  # Ghost checkbox, so it still gets sent. For compatibility with extensions that call txt2img or img2img manually
-
     with FormRow(visible=True, elem_id=target_interface + '_subseed_row'):
         subseed = gr.Number(label='Variation seed', value=-1, elem_id=target_interface + '_subseed')
         subseed.style(container=False)
         random_subseed = ToolButton(random_symbol, elem_id=target_interface + '_random_subseed')
         reuse_subseed = ToolButton(reuse_symbol, elem_id=target_interface + '_reuse_subseed')
         subseed_strength = gr.Slider(label='Strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=target_interface + '_subseed_strength')
-
     with FormRow(visible=False):
         seed_resize_from_w = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from width", value=0, elem_id=target_interface + '_seed_resize_from_w')
         seed_resize_from_h = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize seed from height", value=0, elem_id=target_interface + '_seed_resize_from_h')
-
     random_seed.click(fn=lambda: [-1, -1], show_progress=False, inputs=[], outputs=[seed, subseed])
     random_subseed.click(fn=lambda: -1, show_progress=False, inputs=[], outputs=[subseed])
-
     return seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox
 
 
-
 def connect_clear_prompt(button):
     """Given clear button, prompt, and token_counter objects, setup clear prompt button click event"""
-    button.click(
-        _js="clear_prompt",
-        fn=None,
-        inputs=[],
-        outputs=[],
-    )
+    button.click(_js="clear_prompt", fn=None, inputs=[], outputs=[])
 
 
 def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, dummy_component, is_subseed):
@@ -190,7 +171,6 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
         was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
     def copy_seed(gen_info_string: str, index):
         res = -1
-
         try:
             gen_info = json.loads(gen_info_string)
             index -= gen_info.get('index_of_first_image', 0)
@@ -201,35 +181,24 @@ def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info:
             else:
                 all_seeds = gen_info.get('all_seeds', [-1])
                 res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
-
         except json.decoder.JSONDecodeError:
             if gen_info_string != '':
                 print("Error parsing JSON generation info:", file=sys.stderr)
                 print(gen_info_string, file=sys.stderr)
-
         return [res, gr_show(False)]
 
-    reuse_seed.click(
-        fn=copy_seed,
-        _js="(x, y) => [x, selected_gallery_index()]",
-        show_progress=False,
-        inputs=[generation_info, dummy_component],
-        outputs=[seed, dummy_component]
-    )
+    reuse_seed.click(fn=copy_seed, _js="(x, y) => [x, selected_gallery_index()]", show_progress=False, inputs=[generation_info, dummy_component], outputs=[seed, dummy_component])
 
 
 def update_token_counter(text, steps):
     try:
         text, _ = extra_networks.parse_prompt(text)
-
         _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
         prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)
-
     except Exception:
         # a parsing error can happen here during typing, and we don't want to bother the user with
         # messages related to it in console
         prompt_schedules = [[[steps, text]]]
-
     flat_prompts = reduce(lambda list1, list2: list1+list2, prompt_schedules)
     prompts = [prompt_text for step, prompt_text in flat_prompts]
     token_count, max_length = max([model_hijack.get_prompt_lengths(prompt) for prompt in prompts], key=lambda args: args[0])
@@ -238,67 +207,43 @@ def update_token_counter(text, steps):
 
 def create_toprow(is_img2img):
     id_part = "img2img" if is_img2img else "txt2img"
-
     with gr.Row(elem_id=f"{id_part}_toprow", variant="compact"):
         with gr.Column(elem_id=f"{id_part}_prompt_container", scale=6):
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
                         prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=3, placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)")
-
             with gr.Row():
                 with gr.Column(scale=80):
                     with gr.Row():
                         negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=3, placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)")
-
         button_interrogate = None
         button_deepbooru = None
         if is_img2img:
             with gr.Column(scale=1, elem_classes="interrogate-col"):
                 button_interrogate = gr.Button('Interrogate\nCLIP', elem_id="interrogate")
                 button_deepbooru = gr.Button('Interrogate\nDeepBooru', elem_id="deepbooru")
-
         with gr.Column(scale=1, elem_id=f"{id_part}_actions_column"):
             with gr.Row(elem_id=f"{id_part}_generate_box", elem_classes="generate-box"):
                 interrupt = gr.Button('Stop', elem_id=f"{id_part}_interrupt", elem_classes="generate-box-interrupt")
                 skip = gr.Button('Skip', elem_id=f"{id_part}_skip", elem_classes="generate-box-skip")
                 submit = gr.Button('Generate', elem_id=f"{id_part}_generate", variant='primary')
-
-                skip.click(
-                    fn=lambda: shared.state.skip(),
-                    inputs=[],
-                    outputs=[],
-                )
-
-                interrupt.click(
-                    fn=lambda: shared.state.interrupt(),
-                    inputs=[],
-                    outputs=[],
-                )
-
+                skip.click(fn=lambda: shared.state.skip(), inputs=[], outputs=[])
+                interrupt.click(fn=lambda: shared.state.interrupt(), inputs=[], outputs=[])
             with gr.Row(elem_id=f"{id_part}_tools"):
                 paste = ToolButton(value=paste_symbol, elem_id="paste")
                 clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
                 extra_networks_button = ToolButton(value=extra_networks_symbol, elem_id=f"{id_part}_extra_networks")
                 prompt_style_apply = ToolButton(value=apply_style_symbol, elem_id=f"{id_part}_style_apply")
                 save_style = ToolButton(value=save_style_symbol, elem_id=f"{id_part}_style_create")
-
                 token_counter = gr.HTML(value="<span>0/75</span>", elem_id=f"{id_part}_token_counter", elem_classes=["token-counter"])
                 token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
                 negative_token_counter = gr.HTML(value="<span>0/75</span>", elem_id=f"{id_part}_negative_token_counter", elem_classes=["token-counter"])
                 negative_token_button = gr.Button(visible=False, elem_id=f"{id_part}_negative_token_button")
-
-                clear_prompt_button.click(
-                    fn=lambda *x: x,
-                    _js="confirm_clear_prompt",
-                    inputs=[prompt, negative_prompt],
-                    outputs=[prompt, negative_prompt],
-                )
-
+                clear_prompt_button.click(fn=lambda *x: x, _js="confirm_clear_prompt", inputs=[prompt, negative_prompt], outputs=[prompt, negative_prompt])
             with gr.Row(elem_id=f"{id_part}_styles_row"):
                 prompt_styles = gr.Dropdown(label="Styles", elem_id=f"{id_part}_styles", choices=[k for k, v in shared.prompt_styles.styles.items()], value=[], multiselect=True)
                 create_refresh_button(prompt_styles, shared.prompt_styles.reload, lambda: {"choices": [k for k, v in shared.prompt_styles.styles.items()]}, f"refresh_{id_part}_styles")
-
     return prompt, prompt_styles, negative_prompt, submit, button_interrogate, button_deepbooru, prompt_style_apply, save_style, paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button
 
 
@@ -309,32 +254,25 @@ def setup_progressbar(*args, **kwargs): # pylint: disable=unused-argument
 def apply_setting(key, value):
     if value is None:
         return gr.update()
-
     if shared.cmd_opts.freeze_settings:
         return gr.update()
-
     # dont allow model to be swapped when model hash exists in prompt
     if key == "sd_model_checkpoint" and opts.disable_weights_auto_swap:
         return gr.update()
-
     if key == "sd_model_checkpoint":
         ckpt_info = sd_models.get_closet_checkpoint_match(value)
-
         if ckpt_info is not None:
             value = ckpt_info.title
         else:
             return gr.update()
-
     comp_args = opts.data_labels[key].component_args
     if comp_args and isinstance(comp_args, dict) and comp_args.get('visible') is False:
         return
-
     valtype = type(opts.data_labels[key].default)
     oldval = opts.data.get(key, None)
     opts.data[key] = valtype(value) if valtype != type(None) else value
     if oldval != value and opts.data_labels[key].onchange is not None:
         opts.data_labels[key].onchange()
-
     opts.save(shared.config_filename)
     return getattr(opts, key)
 
@@ -343,18 +281,12 @@ def create_refresh_button(refresh_component, refresh_method, refreshed_args, ele
     def refresh():
         refresh_method()
         args = refreshed_args() if callable(refreshed_args) else refreshed_args
-
         for k, v in args.items():
             setattr(refresh_component, k, v)
-
         return gr.update(**(args or {}))
 
     refresh_button = ToolButton(value=refresh_symbol, elem_id=elem_id)
-    refresh_button.click(
-        fn=refresh,
-        inputs=[],
-        outputs=[refresh_component]
-    )
+    refresh_button.click(fn=refresh, inputs=[], outputs=[refresh_component])
     return refresh_button
 
 
@@ -366,117 +298,89 @@ def create_sampler_and_steps_selection(choices, tabname):
     with FormRow(elem_id=f"sampler_selection_{tabname}"):
         sampler_index = gr.Dropdown(label='Sampling method', elem_id=f"{tabname}_sampling", choices=[x.name for x in choices], value="UniPC" if tabname == 'txt2img' else "Euler a", type="index")
         steps = gr.Slider(minimum=1, maximum=150, step=1, elem_id=f"{tabname}_steps", label="Sampling steps", value=10 if tabname == 'txt2img' else 20)
-
     return steps, sampler_index
 
 
 def ordered_ui_categories():
     user_order = {x.strip(): i * 2 + 1 for i, x in enumerate(shared.opts.ui_reorder.split(","))}
-
     for i, category in sorted(enumerate(shared.ui_reorder_categories), key=lambda x: user_order.get(x[1], x[0] * 2 + 0)):
         yield category
 
 
 def get_value_for_setting(key):
     value = getattr(opts, key)
-
     info = opts.data_labels[key]
     args = info.component_args() if callable(info.component_args) else info.component_args or {}
     args = {k: v for k, v in args.items() if k not in {'precision'}}
-
     return gr.update(value=value, **args)
 
 
 def create_override_settings_dropdown(tabname, row): # pylint: disable=unused-argument
     dropdown = gr.Dropdown([], label="Override settings", visible=False, elem_id=f"{tabname}_override_settings", multiselect=True)
-
-    dropdown.change(
-        fn=lambda x: gr.Dropdown.update(visible=len(x) > 0),
-        inputs=[dropdown],
-        outputs=[dropdown],
-    )
-
+    dropdown.change(fn=lambda x: gr.Dropdown.update(visible=len(x) > 0), inputs=[dropdown], outputs=[dropdown])
     return dropdown
 
 
 def create_ui():
     import modules.img2img # pylint: disable=redefined-outer-name
     import modules.txt2img # pylint: disable=redefined-outer-name
-
     reload_javascript()
-
     parameters_copypaste.reset()
-
     modules.scripts.scripts_current = modules.scripts.scripts_txt2img
     modules.scripts.scripts_txt2img.initialize_scripts(is_img2img=False)
-
     with gr.Blocks(analytics_enabled=False) as txt2img_interface:
         txt2img_prompt, txt2img_prompt_styles, txt2img_negative_prompt, submit, _, _, txt2img_prompt_style_apply, txt2img_save_style, txt2img_paste, extra_networks_button, token_counter, token_button, negative_token_counter, negative_token_button = create_toprow(is_img2img=False)
-
         dummy_component = gr.Label(visible=False)
         txt_prompt_img = gr.File(label="", elem_id="txt2img_prompt_image", file_count="single", type="binary", visible=False)
-
         with FormRow(variant='compact', elem_id="txt2img_extra_networks", visible=False) as extra_networks_ui:
             from modules import ui_extra_networks
             extra_networks_ui = ui_extra_networks.create_ui(extra_networks_ui, extra_networks_button, 'txt2img')
-
         with gr.Row().style(equal_height=False):
             with gr.Column(variant='compact', elem_id="txt2img_settings"):
                 for category in ordered_ui_categories():
                     if category == "sampler":
                         steps, sampler_index = create_sampler_and_steps_selection(samplers, "txt2img")
-
                     elif category == "dimensions":
                         with FormRow():
                             with gr.Column(elem_id="txt2img_column_size", scale=4):
                                 with FormRow(elem_id="txt2img_row_dimension"):
                                     width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="txt2img_width")
                                     height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="txt2img_height")
-
                             with gr.Column(elem_id="txt2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
                                 res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn")
-
                             with gr.Column(elem_id="txt2img_column_batch"):
                                 with FormRow(elem_id="txt2img_row_batch"):
                                     batch_count = gr.Slider(minimum=1, step=1, label='Batch count', value=1, elem_id="txt2img_batch_count")
                                     batch_size = gr.Slider(minimum=1, maximum=32, step=1, label='Batch size', value=1, elem_id="txt2img_batch_size")
-
                     elif category == "cfg":
                         with FormRow():
                             cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="txt2img_cfg_scale")
                             clip_skip = gr.Slider(label='CLIP Skip', value=1, minimum=1, maximum=4, step=1, elem_id='txt2img_clip_skip', interactive=True)
                             clip_skip.change(fn=change_clip_skip, show_progress=False, inputs=clip_skip)
-
                     elif category == "seed":
                         seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('txt2img')
-
                     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")
                             enable_hr = gr.Checkbox(label='Hires fix', value=False, elem_id="txt2img_enable_hr")
                             hr_final_resolution = FormHTML(value="", elem_id="txtimg_hr_finalres", label="Upscaled resolution", interactive=False)
-
                     elif category == "hires_fix":
                         with FormGroup(visible=False, elem_id="txt2img_hires_fix") as hr_options:
                             with FormRow(elem_id="txt2img_hires_fix_row1", variant="compact"):
                                 hr_upscaler = gr.Dropdown(label="Upscaler", elem_id="txt2img_hr_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
                                 hr_second_pass_steps = gr.Slider(minimum=0, maximum=150, step=1, label='Hires steps', value=0, elem_id="txt2img_hires_steps")
                                 denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.7, elem_id="txt2img_denoising_strength")
-
                             with FormRow(elem_id="txt2img_hires_fix_row2", variant="compact"):
                                 hr_scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=2.0, elem_id="txt2img_hr_scale")
                                 hr_resize_x = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize width to", value=0, elem_id="txt2img_hr_resize_x")
                                 hr_resize_y = gr.Slider(minimum=0, maximum=2048, step=8, label="Resize height to", value=0, elem_id="txt2img_hr_resize_y")
-
                     elif category == "override_settings":
                         with FormRow(elem_id="txt2img_override_settings_row") as row:
                             override_settings = create_override_settings_dropdown('txt2img', row)
-
                     elif category == "scripts":
                         with FormGroup(elem_id="txt2img_script_container"):
                             custom_inputs = modules.scripts.scripts_txt2img.setup_ui()
-
             hr_resolution_preview_inputs = [enable_hr, width, height, hr_scale, hr_resize_x, hr_resize_y]
             for preview_input in hr_resolution_preview_inputs:
                 preview_input.change(
@@ -494,7 +398,6 @@ def create_ui():
                 )
 
             txt2img_gallery, generation_info, html_info, html_log = create_output_panel("txt2img", opts.outdir_txt2img_samples)
-
             connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
             connect_reuse_seed(subseed, reuse_subseed, generation_info, dummy_component, is_subseed=True)
 
@@ -1297,9 +1200,7 @@ def create_ui():
 
         info = opts.data_labels[key]
         t = type(info.default)
-
         args = info.component_args() if callable(info.component_args) else info.component_args
-
         if info.component is not None:
             comp = info.component
         elif t == str:
@@ -1310,9 +1211,7 @@ def create_ui():
             comp = gr.Checkbox
         else:
             raise ValueError(f'bad options item type: {str(t)} for key {key}')
-
         elem_id = "setting_"+key
-
         if info.refresh is not None:
             if is_quicksettings:
                 res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
@@ -1323,7 +1222,6 @@ def create_ui():
                     create_refresh_button(res, info.refresh, info.component_args, "refresh_" + key)
         else:
             res = comp(label=info.label, value=fun(), elem_id=elem_id, **(args or {}))
-
         return res
 
     components = []

script.js

@@ -1,7 +1,6 @@
 function gradioApp() {
     const elems = document.getElementsByTagName('gradio-app')
     const elem = elems.length == 0 ? document : elems[0]
-
     if (elem !== document) elem.getElementById = function(id){ return document.getElementById(id) }
     return elem.shadowRoot ? elem.shadowRoot : elem
 }
@@ -34,12 +33,10 @@ function onOptionsChanged(callback){
 }
 
 function runCallback(x, m){
-    try {
-        x(m)
-    } catch (e) {
-        (console.error || console.log).call(console, e.message, e);
-    }
+    try { x(m)
+    } catch (e) { (console.error || console.log).call(console, e.message, e); }
 }
+
 function executeCallbacks(queue, m) {
     queue.forEach(function(x){runCallback(x, m)})
 }
@@ -52,7 +49,6 @@ document.addEventListener("DOMContentLoaded", function() {
             executedOnLoaded = true;
             executeCallbacks(uiLoadedCallbacks);
         }
-
         executeCallbacks(uiUpdateCallbacks, m);
         const newTab = get_uiCurrentTab();
         if ( newTab && ( newTab !== uiCurrentTab ) ) {
@@ -75,9 +71,7 @@ document.addEventListener('keydown', function(e) {
     }
     if (handled) {
         button = get_uiCurrentTabContent().querySelector('button[id$=_generate]');
-        if (button) {
-            button.click();
-        }
+        if (button) button.click();
         e.preventDefault();
     }
 })
@@ -87,18 +81,11 @@ document.addEventListener('keydown', function(e) {
  */
 function uiElementIsVisible(el) {
     let isVisible = !el.closest('.\\!hidden');
-    if ( ! isVisible ) {
-        return false;
-    }
-
+    if (!isVisible) return false;
     while( isVisible = el.closest('.tabitem')?.style.display !== 'none' ) {
-        if ( ! isVisible ) {
-            return false;
-        } else if ( el.parentElement ) {
-            el = el.parentElement
-        } else {
-            break;
-        }
+        if ( ! isVisible ) return false;
+        else if ( el.parentElement ) el = el.parentElement
+        else break;
     }
     return isVisible;
 }

webui.bat

@@ -2,10 +2,7 @@
 
 if not defined PYTHON (set PYTHON=python)
 if not defined VENV_DIR (set "VENV_DIR=%~dp0%venv")
-
-
 set ERROR_REPORTING=FALSE
-
 mkdir tmp 2>NUL
 
 %PYTHON% -c "" >tmp/stdout.txt 2>tmp/stderr.txt
@@ -38,14 +35,14 @@ goto :show_stdout_stderr
 
 :activate_venv
 set PYTHON="%VENV_DIR%\Scripts\Python.exe"
-echo venv %PYTHON%
+echo Using VENV: %VENV_DIR%
 
 :skip_venv
 if [%ACCELERATE%] == ["True"] goto :accelerate
 goto :launch
 
 :accelerate
-echo Checking for accelerate
+echo Checking for accelerate: %ACCELERATE%
 set ACCELERATE="%VENV_DIR%\Scripts\accelerate.exe"
 if EXIST %ACCELERATE% goto :accelerate_launch
 
@@ -56,7 +53,7 @@ exit /b
 
 :accelerate_launch
 echo Accelerating
-%ACCELERATE% launch --num_cpu_threads_per_process=6 launch.py
+%ACCELERATE% launch --num_cpu_threads_per_process=6 launch.py %*
 pause
 exit /b
 

webui.sh

@@ -4,34 +4,16 @@
 # change the variables in webui-user.sh instead #
 #################################################
 
-# If run from macOS, load defaults from webui-macos-env.sh
-if [[ "$OSTYPE" == "darwin"* ]]; then
-    if [[ -f webui-macos-env.sh ]]
-        then
-        source ./webui-macos-env.sh
-    fi
-fi
+can_run_as_root=0
+export ERROR_REPORTING=FALSE
+export PIP_IGNORE_INSTALLED=0
 
 # Read variables from webui-user.sh
-# shellcheck source=/dev/null
 if [[ -f webui-user.sh ]]
 then
     source ./webui-user.sh
 fi
 
-# Set defaults
-# Install directory without trailing slash
-if [[ -z "${install_dir}" ]]
-then
-    install_dir="${HOME}"
-fi
-
-# Name of the subdirectory (defaults to stable-diffusion-webui)
-if [[ -z "${clone_dir}" ]]
-then
-    clone_dir="stable-diffusion-webui"
-fi
-
 # python3 executable
 if [[ -z "${python_cmd}" ]]
 then
@@ -44,19 +26,11 @@ then
     export GIT="git"
 fi
 
-# python3 venv without trailing slash (defaults to ${install_dir}/${clone_dir}/venv)
 if [[ -z "${venv_dir}" ]]
 then
     venv_dir="venv"
 fi
 
-if [[ -z "${LAUNCH_SCRIPT}" ]]
-then
-    LAUNCH_SCRIPT="launch.py"
-fi
-
-# this script cannot be run as root by default
-can_run_as_root=0
 
 # read any command line flags to the webui.sh script
 while getopts "f" flag > /dev/null 2>&1
@@ -67,102 +41,48 @@ do
     esac
 done
 
-# Disable sentry logging
-export ERROR_REPORTING=FALSE
-
-# Do not reinstall existing pip packages on Debian/Ubuntu
-export PIP_IGNORE_INSTALLED=0
-
-# Pretty print
-delimiter="################################################################"
-
-printf "\n%s\n" "${delimiter}"
-printf "\e[1m\e[32mInstall script for stable-diffusion + Web UI\n"
-printf "\e[1m\e[34mTested on Debian 11 (Bullseye)\e[0m"
-printf "\n%s\n" "${delimiter}"
-
 # Do not run as root
 if [[ $(id -u) -eq 0 && can_run_as_root -eq 0 ]]
 then
-    printf "\n%s\n" "${delimiter}"
-    printf "\e[1m\e[31mERROR: This script must not be launched as root, aborting...\e[0m"
-    printf "\n%s\n" "${delimiter}"
+    echo "Cannot run as root"
     exit 1
-else
-    printf "\n%s\n" "${delimiter}"
-    printf "Running on \e[1m\e[32m%s\e[0m user" "$(whoami)"
-    printf "\n%s\n" "${delimiter}"
-fi
-
-if [[ -d .git ]]
-then
-    printf "\n%s\n" "${delimiter}"
-    printf "Repo already cloned, using it as install directory"
-    printf "\n%s\n" "${delimiter}"
-    install_dir="${PWD}/../"
-    clone_dir="${PWD##*/}"
 fi
 
 for preq in "${GIT}" "${python_cmd}"
 do
     if ! hash "${preq}" &>/dev/null
     then
-        printf "\n%s\n" "${delimiter}"
-        printf "\e[1m\e[31mERROR: %s is not installed, aborting...\e[0m" "${preq}"
-        printf "\n%s\n" "${delimiter}"
+        printf "Error: %s is not installed, aborting...\n" "${preq}"
         exit 1
     fi
 done
 
 if ! "${python_cmd}" -c "import venv" &>/dev/null
 then
-    printf "\n%s\n" "${delimiter}"
-    printf "\e[1m\e[31mERROR: python3-venv is not installed, aborting...\e[0m"
-    printf "\n%s\n" "${delimiter}"
+    echo "Error: python3-venv is not installed"
     exit 1
 fi
 
-cd "${install_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/, aborting...\e[0m" "${install_dir}"; exit 1; }
-if [[ -d "${clone_dir}" ]]
-then
-    cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
-else
-    printf "\n%s\n" "${delimiter}"
-    printf "Clone stable-diffusion-webui"
-    printf "\n%s\n" "${delimiter}"
-    "${GIT}" clone https://github.com/vladmandic/automatic.git "${clone_dir}"
-    cd "${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
-fi
-
-printf "\n%s\n" "${delimiter}"
-printf "Create and activate python venv"
-printf "\n%s\n" "${delimiter}"
-cd "${install_dir}"/"${clone_dir}"/ || { printf "\e[1m\e[31mERROR: Can't cd to %s/%s/, aborting...\e[0m" "${install_dir}" "${clone_dir}"; exit 1; }
+echo "Create and activate python venv"
 if [[ ! -d "${venv_dir}" ]]
 then
     "${python_cmd}" -m venv "${venv_dir}"
     first_launch=1
 fi
-# shellcheck source=/dev/null
+
 if [[ -f "${venv_dir}"/bin/activate ]]
 then
     source "${venv_dir}"/bin/activate
 else
-    printf "\n%s\n" "${delimiter}"
-    printf "\e[1m\e[31mERROR: Cannot activate python venv, aborting...\e[0m"
-    printf "\n%s\n" "${delimiter}"
+    echo "Error: Cannot activate python venv"
     exit 1
 fi
 
 if [[ ! -z "${ACCELERATE}" ]] && [ ${ACCELERATE}="True" ] && [ -x "$(command -v accelerate)" ]
 then
-    printf "\n%s\n" "${delimiter}"
-    printf "Accelerating launch.py..."
-    printf "\n%s\n" "${delimiter}"
-    exec accelerate launch --num_cpu_threads_per_process=6 "${LAUNCH_SCRIPT}" "$@"
+    echo "Accelerating launch.py..."
+    exec accelerate launch --num_cpu_threads_per_process=6 launch.py "$@"
 else
-    printf "\n%s\n" "${delimiter}"
-    printf "Launching launch.py..."
-    printf "\n%s\n" "${delimiter}"      
-    exec "${python_cmd}" "${LAUNCH_SCRIPT}" "$@"
+    echo "Launching launch.py..."
+    exec "${python_cmd}" launch.py "$@"
 fi