add changelog entry

requirements_versions httpx==0.24.1

.eslintrc.js

@@ -74,7 +74,6 @@ module.exports = {
         create_submit_args: "readonly",
         restart_reload: "readonly",
         updateInput: "readonly",
-        onEdit: "readonly",
         //extraNetworks.js
         requestGet: "readonly",
         popup: "readonly",

CHANGELOG.md

@@ -1,3 +1,8 @@
+## 1.6.1
+
+### Bug Fixes:
+ * fix an error causing the webui to fail to start ([#13839](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/13839))
+
 ## 1.6.0
 
 ### Features:

README.md

@@ -88,7 +88,7 @@ A browser interface based on Gradio library for Stable Diffusion.
 - [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions
 - Now without any bad letters!
 - Load checkpoints in safetensors format
-- Eased resolution restriction: generated image's dimensions must be a multiple of 8 rather than 64
+- Eased resolution restriction: generated image's dimension must be a multiple of 8 rather than 64
 - Now with a license!
 - Reorder elements in the UI from settings screen
 
@@ -103,7 +103,7 @@ Alternatively, use online services (like Google Colab):
 - [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)
 
 ### Installation on Windows 10/11 with NVidia-GPUs using release package
-1. Download `sd.webui.zip` from [v1.0.0-pre](https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases/tag/v1.0.0-pre) and extract its contents.
+1. Download `sd.webui.zip` from [v1.0.0-pre](https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases/tag/v1.0.0-pre) and extract it's contents.
 2. Run `update.bat`.
 3. Run `run.bat`.
 > For more details see [Install-and-Run-on-NVidia-GPUs](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs)

extensions-builtin/Lora/lora_logger.py

@@ -1,33 +0,0 @@
-import sys
-import copy
-import logging
-
-
-class ColoredFormatter(logging.Formatter):
-    COLORS = {
-        "DEBUG": "\033[0;36m",  # CYAN
-        "INFO": "\033[0;32m",  # GREEN
-        "WARNING": "\033[0;33m",  # YELLOW
-        "ERROR": "\033[0;31m",  # RED
-        "CRITICAL": "\033[0;37;41m",  # WHITE ON RED
-        "RESET": "\033[0m",  # RESET COLOR
-    }
-
-    def format(self, record):
-        colored_record = copy.copy(record)
-        levelname = colored_record.levelname
-        seq = self.COLORS.get(levelname, self.COLORS["RESET"])
-        colored_record.levelname = f"{seq}{levelname}{self.COLORS['RESET']}"
-        return super().format(colored_record)
-
-
-logger = logging.getLogger("lora")
-logger.propagate = False
-
-
-if not logger.handlers:
-    handler = logging.StreamHandler(sys.stdout)
-    handler.setFormatter(
-        ColoredFormatter("[%(name)s]-%(levelname)s: %(message)s")
-    )
-    logger.addHandler(handler)

extensions-builtin/Lora/network.py

@@ -93,7 +93,6 @@ class Network:  # LoraModule
         self.unet_multiplier = 1.0
         self.dyn_dim = None
         self.modules = {}
-        self.bundle_embeddings = {}
         self.mtime = None
 
         self.mentioned_name = None

extensions-builtin/Lora/networks.py

@@ -15,9 +15,6 @@ import torch
 from typing import Union
 
 from modules import shared, devices, sd_models, errors, scripts, sd_hijack
-from modules.textual_inversion.textual_inversion import Embedding
-
-from lora_logger import logger
 
 module_types = [
     network_lora.ModuleTypeLora(),
@@ -152,19 +149,9 @@ def load_network(name, network_on_disk):
     is_sd2 = 'model_transformer_resblocks' in shared.sd_model.network_layer_mapping
 
     matched_networks = {}
-    bundle_embeddings = {}
 
     for key_network, weight in sd.items():
         key_network_without_network_parts, network_part = key_network.split(".", 1)
-        if key_network_without_network_parts == "bundle_emb":
-            emb_name, vec_name = network_part.split(".", 1)
-            emb_dict = bundle_embeddings.get(emb_name, {})
-            if vec_name.split('.')[0] == 'string_to_param':
-                _, k2 = vec_name.split('.', 1)
-                emb_dict['string_to_param'] = {k2: weight}
-            else:
-                emb_dict[vec_name] = weight
-            bundle_embeddings[emb_name] = emb_dict
 
         key = convert_diffusers_name_to_compvis(key_network_without_network_parts, is_sd2)
         sd_module = shared.sd_model.network_layer_mapping.get(key, None)
@@ -208,41 +195,6 @@ def load_network(name, network_on_disk):
 
         net.modules[key] = net_module
 
-    embeddings = {}
-    for emb_name, data in bundle_embeddings.items():
-        # textual inversion embeddings
-        if 'string_to_param' in data:
-            param_dict = data['string_to_param']
-            param_dict = getattr(param_dict, '_parameters', param_dict)  # fix for torch 1.12.1 loading saved file from torch 1.11
-            assert len(param_dict) == 1, 'embedding file has multiple terms in it'
-            emb = next(iter(param_dict.items()))[1]
-            vec = emb.detach().to(devices.device, dtype=torch.float32)
-            shape = vec.shape[-1]
-            vectors = vec.shape[0]
-        elif type(data) == dict and 'clip_g' in data and 'clip_l' in data:  # SDXL embedding
-            vec = {k: v.detach().to(devices.device, dtype=torch.float32) for k, v in data.items()}
-            shape = data['clip_g'].shape[-1] + data['clip_l'].shape[-1]
-            vectors = data['clip_g'].shape[0]
-        elif type(data) == dict and type(next(iter(data.values()))) == torch.Tensor: # diffuser concepts
-            assert len(data.keys()) == 1, 'embedding file has multiple terms in it'
-
-            emb = next(iter(data.values()))
-            if len(emb.shape) == 1:
-                emb = emb.unsqueeze(0)
-            vec = emb.detach().to(devices.device, dtype=torch.float32)
-            shape = vec.shape[-1]
-            vectors = vec.shape[0]
-        else:
-            raise Exception(f"Couldn't identify {emb_name} in lora: {name} as neither textual inversion embedding nor diffuser concept.")
-
-        embedding = Embedding(vec, emb_name)
-        embedding.vectors = vectors
-        embedding.shape = shape
-        embedding.loaded = None
-        embeddings[emb_name] = embedding
-
-    net.bundle_embeddings = embeddings
-
     if keys_failed_to_match:
         logging.debug(f"Network {network_on_disk.filename} didn't match keys: {keys_failed_to_match}")
 
@@ -258,16 +210,11 @@ def purge_networks_from_memory():
 
 
 def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=None):
-    emb_db = sd_hijack.model_hijack.embedding_db
     already_loaded = {}
 
     for net in loaded_networks:
         if net.name in names:
             already_loaded[net.name] = net
-        for emb_name, embedding in net.bundle_embeddings.items():
-            if embedding.loaded:
-                embedding.loaded = None
-                emb_db.register_embedding_by_name(None, shared.sd_model, emb_name)
 
     loaded_networks.clear()
 
@@ -310,21 +257,6 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
         net.dyn_dim = dyn_dims[i] if dyn_dims else 1.0
         loaded_networks.append(net)
 
-        for emb_name, embedding in net.bundle_embeddings.items():
-            if embedding.loaded is None and emb_name in emb_db.word_embeddings:
-                logger.warning(
-                    f'Skip bundle embedding: "{emb_name}"'
-                    ' as it was already loaded from embeddings folder'
-                )
-                continue
-
-            embedding.loaded = False
-            if emb_db.expected_shape == -1 or emb_db.expected_shape == embedding.shape:
-                embedding.loaded = True
-                emb_db.register_embedding(embedding, shared.sd_model)
-            else:
-                emb_db.skipped_embeddings[name] = embedding
-
     if failed_to_load_networks:
         sd_hijack.model_hijack.comments.append("Networks not found: " + ", ".join(failed_to_load_networks))
 
@@ -486,7 +418,6 @@ def network_forward(module, input, original_forward):
 def network_reset_cached_weight(self: Union[torch.nn.Conv2d, torch.nn.Linear]):
     self.network_current_names = ()
     self.network_weights_backup = None
-    self.network_bias_backup = None
 
 
 def network_Linear_forward(self, input):
@@ -633,7 +564,6 @@ extra_network_lora = None
 available_networks = {}
 available_network_aliases = {}
 loaded_networks = []
-loaded_bundle_embeddings = {}
 networks_in_memory = {}
 available_network_hash_lookup = {}
 forbidden_network_aliases = {}

javascript/dragdrop.js

@@ -119,7 +119,7 @@ window.addEventListener('paste', e => {
     }
 
     const firstFreeImageField = visibleImageFields
-        .filter(el => !el.querySelector('img'))?.[0];
+        .filter(el => el.querySelector('input[type=file]'))?.[0];
 
     dropReplaceImage(
         firstFreeImageField ?

javascript/edit-attention.js

@@ -18,11 +18,22 @@ function keyupEditAttention(event) {
         const before = text.substring(0, selectionStart);
         let beforeParen = before.lastIndexOf(OPEN);
         if (beforeParen == -1) return false;
+        let beforeParenClose = before.lastIndexOf(CLOSE);
+        while (beforeParenClose !== -1 && beforeParenClose > beforeParen) {
+            beforeParen = before.lastIndexOf(OPEN, beforeParen - 1);
+            beforeParenClose = before.lastIndexOf(CLOSE, beforeParenClose - 1);
+        }
 
         // Find closing parenthesis around current cursor
         const after = text.substring(selectionStart);
         let afterParen = after.indexOf(CLOSE);
         if (afterParen == -1) return false;
+        let afterParenOpen = after.indexOf(OPEN);
+        while (afterParenOpen !== -1 && afterParen > afterParenOpen) {
+            afterParen = after.indexOf(CLOSE, afterParen + 1);
+            afterParenOpen = after.indexOf(OPEN, afterParenOpen + 1);
+        }
+        if (beforeParen === -1 || afterParen === -1) return false;
 
         // Set the selection to the text between the parenthesis
         const parenContent = text.substring(beforeParen + 1, selectionStart + afterParen);
@@ -35,14 +46,9 @@ function keyupEditAttention(event) {
 
     function selectCurrentWord() {
         if (selectionStart !== selectionEnd) return false;
-        const whitespace_delimiters = {"Tab": "\t", "Carriage Return": "\r", "Line Feed": "\n"};
-        let delimiters = opts.keyedit_delimiters;
+        const delimiters = opts.keyedit_delimiters + " \r\n\t";
 
-        for (let i of opts.keyedit_delimiters_whitespace) {
-            delimiters += whitespace_delimiters[i];
-        }
-
-        // seek backward to find beginning
+        // seek backward until to find beggining
         while (!delimiters.includes(text[selectionStart - 1]) && selectionStart > 0) {
             selectionStart--;
         }
@@ -86,7 +92,7 @@ function keyupEditAttention(event) {
     }
 
     var end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1;
-    var weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + end));
+    var weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end));
     if (isNaN(weight)) return;
 
     weight += isPlus ? delta : -delta;

javascript/extraNetworks.js

@@ -140,15 +140,14 @@ function setupExtraNetworks() {
 
 onUiLoaded(setupExtraNetworks);
 
-var re_extranet = /<([^:^>]+:[^:]+):[\d.]+>(.*)/;
-var re_extranet_g = /<([^:^>]+:[^:]+):[\d.]+>/g;
+var re_extranet = /<([^:]+:[^:]+):[\d.]+>(.*)/;
+var re_extranet_g = /\s+<([^:]+:[^:]+):[\d.]+>/g;
 
 function tryToRemoveExtraNetworkFromPrompt(textarea, text) {
     var m = text.match(re_extranet);
     var replaced = false;
     var newTextareaText;
     if (m) {
-        var extraTextBeforeNet = opts.extra_networks_add_text_separator;
         var extraTextAfterNet = m[2];
         var partToSearch = m[1];
         var foundAtPosition = -1;
@@ -162,13 +161,8 @@ function tryToRemoveExtraNetworkFromPrompt(textarea, text) {
             return found;
         });
 
-        if (foundAtPosition >= 0) {
-            if (newTextareaText.substr(foundAtPosition, extraTextAfterNet.length) == extraTextAfterNet) {
-                newTextareaText = newTextareaText.substr(0, foundAtPosition) + newTextareaText.substr(foundAtPosition + extraTextAfterNet.length);
-            }
-            if (newTextareaText.substr(foundAtPosition - extraTextBeforeNet.length, extraTextBeforeNet.length) == extraTextBeforeNet) {
-                newTextareaText = newTextareaText.substr(0, foundAtPosition - extraTextBeforeNet.length) + newTextareaText.substr(foundAtPosition);
-            }
+        if (foundAtPosition >= 0 && newTextareaText.substr(foundAtPosition, extraTextAfterNet.length) == extraTextAfterNet) {
+            newTextareaText = newTextareaText.substr(0, foundAtPosition) + newTextareaText.substr(foundAtPosition + extraTextAfterNet.length);
         }
     } else {
         newTextareaText = textarea.value.replaceAll(new RegExp(text, "g"), function(found) {
@@ -222,24 +216,27 @@ function extraNetworksSearchButton(tabs_id, event) {
 
 var globalPopup = null;
 var globalPopupInner = null;
-
 function closePopup() {
     if (!globalPopup) return;
+
     globalPopup.style.display = "none";
 }
-
 function popup(contents) {
     if (!globalPopup) {
         globalPopup = document.createElement('div');
+        globalPopup.onclick = closePopup;
         globalPopup.classList.add('global-popup');
 
         var close = document.createElement('div');
         close.classList.add('global-popup-close');
-        close.addEventListener("click", closePopup);
+        close.onclick = closePopup;
         close.title = "Close";
         globalPopup.appendChild(close);
 
         globalPopupInner = document.createElement('div');
+        globalPopupInner.onclick = function(event) {
+            event.stopPropagation(); return false;
+        };
         globalPopupInner.classList.add('global-popup-inner');
         globalPopup.appendChild(globalPopupInner);
 
@@ -338,7 +335,7 @@ function extraNetworksEditUserMetadata(event, tabname, extraPage, cardName) {
 function extraNetworksRefreshSingleCard(page, tabname, name) {
     requestGet("./sd_extra_networks/get-single-card", {page: page, tabname: tabname, name: name}, function(data) {
         if (data && data.html) {
-            var card = gradioApp().querySelector(`#${tabname}_${page.replace(" ", "_")}_cards > .card[data-name="${name}"]`);
+            var card = gradioApp().querySelector('.card[data-name=' + JSON.stringify(name) + ']'); // likely using the wrong stringify function
 
             var newDiv = document.createElement('DIV');
             newDiv.innerHTML = data.html;

javascript/settings.js

@@ -1,46 +0,0 @@
-let settingsExcludeTabsFromShowAll = {
-    settings_tab_defaults: 1,
-    settings_tab_sysinfo: 1,
-    settings_tab_actions: 1,
-    settings_tab_licenses: 1,
-};
-
-function settingsShowAllTabs() {
-    gradioApp().querySelectorAll('#settings > div').forEach(function(elem) {
-        if (settingsExcludeTabsFromShowAll[elem.id]) return;
-
-        elem.style.display = "block";
-    });
-}
-
-function settingsShowOneTab() {
-    gradioApp().querySelector('#settings_show_one_page').click();
-}
-
-onUiLoaded(function() {
-    var edit = gradioApp().querySelector('#settings_search');
-    var editTextarea = gradioApp().querySelector('#settings_search > label > input');
-    var buttonShowAllPages = gradioApp().getElementById('settings_show_all_pages');
-    var settings_tabs = gradioApp().querySelector('#settings div');
-
-    onEdit('settingsSearch', editTextarea, 250, function() {
-        var searchText = (editTextarea.value || "").trim().toLowerCase();
-
-        gradioApp().querySelectorAll('#settings > div[id^=settings_] div[id^=column_settings_] > *').forEach(function(elem) {
-            var visible = elem.textContent.trim().toLowerCase().indexOf(searchText) != -1;
-            elem.style.display = visible ? "" : "none";
-        });
-
-        if (searchText != "") {
-            settingsShowAllTabs();
-        } else {
-            settingsShowOneTab();
-        }
-    });
-
-    settings_tabs.insertBefore(edit, settings_tabs.firstChild);
-    settings_tabs.appendChild(buttonShowAllPages);
-
-
-    buttonShowAllPages.addEventListener("click", settingsShowAllTabs);
-});

javascript/token-counters.js

@@ -1,9 +1,10 @@
-let promptTokenCountUpdateFunctions = {};
+let promptTokenCountDebounceTime = 800;
+let promptTokenCountTimeouts = {};
+var promptTokenCountUpdateFunctions = {};
 
 function update_txt2img_tokens(...args) {
     // Called from Gradio
     update_token_counter("txt2img_token_button");
-    update_token_counter("txt2img_negative_token_button");
     if (args.length == 2) {
         return args[0];
     }
@@ -13,7 +14,6 @@ function update_txt2img_tokens(...args) {
 function update_img2img_tokens(...args) {
     // Called from Gradio
     update_token_counter("img2img_token_button");
-    update_token_counter("img2img_negative_token_button");
     if (args.length == 2) {
         return args[0];
     }
@@ -21,7 +21,16 @@ function update_img2img_tokens(...args) {
 }
 
 function update_token_counter(button_id) {
-    promptTokenCountUpdateFunctions[button_id]?.();
+    if (opts.disable_token_counters) {
+        return;
+    }
+    if (promptTokenCountTimeouts[button_id]) {
+        clearTimeout(promptTokenCountTimeouts[button_id]);
+    }
+    promptTokenCountTimeouts[button_id] = setTimeout(
+        () => gradioApp().getElementById(button_id)?.click(),
+        promptTokenCountDebounceTime,
+    );
 }
 
 
@@ -60,11 +69,10 @@ function setupTokenCounting(id, id_counter, id_button) {
     prompt.parentElement.insertBefore(counter, prompt);
     prompt.parentElement.style.position = "relative";
 
-    var func = onEdit(id, textarea, 800, function() {
-        gradioApp().getElementById(id_button)?.click();
-    });
-    promptTokenCountUpdateFunctions[id] = func;
-    promptTokenCountUpdateFunctions[id_button] = func;
+    promptTokenCountUpdateFunctions[id] = function() {
+        update_token_counter(id_button);
+    };
+    textarea.addEventListener("input", promptTokenCountUpdateFunctions[id]);
 }
 
 function setupTokenCounters() {

javascript/ui.js

@@ -263,6 +263,21 @@ onAfterUiUpdate(function() {
     json_elem.parentElement.style.display = "none";
 
     setupTokenCounters();
+
+    var show_all_pages = gradioApp().getElementById('settings_show_all_pages');
+    var settings_tabs = gradioApp().querySelector('#settings div');
+    if (show_all_pages && settings_tabs) {
+        settings_tabs.appendChild(show_all_pages);
+        show_all_pages.onclick = function() {
+            gradioApp().querySelectorAll('#settings > div').forEach(function(elem) {
+                if (elem.id == "settings_tab_licenses") {
+                    return;
+                }
+
+                elem.style.display = "block";
+            });
+        };
+    }
 });
 
 onOptionsChanged(function() {
@@ -351,20 +366,3 @@ function switchWidthHeight(tabname) {
     updateInput(height);
     return [];
 }
-
-
-var onEditTimers = {};
-
-// calls func after afterMs milliseconds has passed since the input elem has beed enited by user
-function onEdit(editId, elem, afterMs, func) {
-    var edited = function() {
-        var existingTimer = onEditTimers[editId];
-        if (existingTimer) clearTimeout(existingTimer);
-
-        onEditTimers[editId] = setTimeout(func, afterMs);
-    };
-
-    elem.addEventListener("input", edited);
-
-    return edited;
-}

modules/api/api.py

@@ -17,7 +17,7 @@ from fastapi.encoders import jsonable_encoder
 from secrets import compare_digest
 
 import modules.shared as shared
-from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items, script_callbacks, generation_parameters_copypaste
+from modules import sd_samplers, deepbooru, sd_hijack, images, scripts, ui, postprocessing, errors, restart, shared_items
 from modules.api import models
 from modules.shared import opts
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
@@ -29,7 +29,7 @@ from modules.sd_models import unload_model_weights, reload_model_weights, checkp
 from modules.sd_models_config import find_checkpoint_config_near_filename
 from modules.realesrgan_model import get_realesrgan_models
 from modules import devices
-from typing import Any
+from typing import Dict, List, Any
 import piexif
 import piexif.helper
 from contextlib import closing
@@ -221,15 +221,15 @@ class Api:
         self.add_api_route("/sdapi/v1/options", self.get_config, methods=["GET"], response_model=models.OptionsModel)
         self.add_api_route("/sdapi/v1/options", self.set_config, methods=["POST"])
         self.add_api_route("/sdapi/v1/cmd-flags", self.get_cmd_flags, methods=["GET"], response_model=models.FlagsModel)
-        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=list[models.SamplerItem])
-        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=list[models.UpscalerItem])
-        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=list[models.LatentUpscalerModeItem])
-        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=list[models.SDModelItem])
-        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=list[models.SDVaeItem])
-        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=list[models.HypernetworkItem])
-        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=list[models.FaceRestorerItem])
-        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=list[models.RealesrganItem])
-        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=list[models.PromptStyleItem])
+        self.add_api_route("/sdapi/v1/samplers", self.get_samplers, methods=["GET"], response_model=List[models.SamplerItem])
+        self.add_api_route("/sdapi/v1/upscalers", self.get_upscalers, methods=["GET"], response_model=List[models.UpscalerItem])
+        self.add_api_route("/sdapi/v1/latent-upscale-modes", self.get_latent_upscale_modes, methods=["GET"], response_model=List[models.LatentUpscalerModeItem])
+        self.add_api_route("/sdapi/v1/sd-models", self.get_sd_models, methods=["GET"], response_model=List[models.SDModelItem])
+        self.add_api_route("/sdapi/v1/sd-vae", self.get_sd_vaes, methods=["GET"], response_model=List[models.SDVaeItem])
+        self.add_api_route("/sdapi/v1/hypernetworks", self.get_hypernetworks, methods=["GET"], response_model=List[models.HypernetworkItem])
+        self.add_api_route("/sdapi/v1/face-restorers", self.get_face_restorers, methods=["GET"], response_model=List[models.FaceRestorerItem])
+        self.add_api_route("/sdapi/v1/realesrgan-models", self.get_realesrgan_models, methods=["GET"], response_model=List[models.RealesrganItem])
+        self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[models.PromptStyleItem])
         self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=models.EmbeddingsResponse)
         self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
         self.add_api_route("/sdapi/v1/refresh-vae", self.refresh_vae, methods=["POST"])
@@ -242,8 +242,7 @@ class Api:
         self.add_api_route("/sdapi/v1/unload-checkpoint", self.unloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/reload-checkpoint", self.reloadapi, methods=["POST"])
         self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=models.ScriptsList)
-        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=list[models.ScriptInfo])
-        self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=list[models.ExtensionItem])
+        self.add_api_route("/sdapi/v1/script-info", self.get_script_info, methods=["GET"], response_model=List[models.ScriptInfo])
 
         if shared.cmd_opts.api_server_stop:
             self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
@@ -474,6 +473,9 @@ class Api:
         return models.ExtrasBatchImagesResponse(images=list(map(encode_pil_to_base64, result[0])), html_info=result[1])
 
     def pnginfoapi(self, req: models.PNGInfoRequest):
+        if(not req.image.strip()):
+            return models.PNGInfoResponse(info="")
+
         image = decode_base64_to_image(req.image.strip())
         if image is None:
             return models.PNGInfoResponse(info="")
@@ -482,10 +484,9 @@ class Api:
         if geninfo is None:
             geninfo = ""
 
-        params = generation_parameters_copypaste.parse_generation_parameters(geninfo)
-        script_callbacks.infotext_pasted_callback(geninfo, params)
+        items = {**{'parameters': geninfo}, **items}
 
-        return models.PNGInfoResponse(info=geninfo, items=items, parameters=params)
+        return models.PNGInfoResponse(info=geninfo, items=items)
 
     def progressapi(self, req: models.ProgressRequest = Depends()):
         # copy from check_progress_call of ui.py
@@ -563,7 +564,7 @@ class Api:
 
         return options
 
-    def set_config(self, req: dict[str, Any]):
+    def set_config(self, req: Dict[str, Any]):
         checkpoint_name = req.get("sd_model_checkpoint", None)
         if checkpoint_name is not None and checkpoint_name not in checkpoint_aliases:
             raise RuntimeError(f"model {checkpoint_name!r} not found")
@@ -769,25 +770,6 @@ class Api:
             cuda = {'error': f'{err}'}
         return models.MemoryResponse(ram=ram, cuda=cuda)
 
-    def get_extensions_list(self):
-        from modules import extensions
-        extensions.list_extensions()
-        ext_list = []
-        for ext in extensions.extensions:
-            ext: extensions.Extension
-            ext.read_info_from_repo()
-            if ext.remote is not None:
-                ext_list.append({
-                    "name": ext.name,
-                    "remote": ext.remote,
-                    "branch": ext.branch,
-                    "commit_hash":ext.commit_hash,
-                    "commit_date":ext.commit_date,
-                    "version":ext.version,
-                    "enabled":ext.enabled
-                })
-        return ext_list
-
     def launch(self, server_name, port, root_path):
         self.app.include_router(self.router)
         uvicorn.run(self.app, host=server_name, port=port, timeout_keep_alive=shared.cmd_opts.timeout_keep_alive, root_path=root_path)

modules/api/models.py

@@ -1,10 +1,12 @@
 import inspect
 
 from pydantic import BaseModel, Field, create_model
-from typing import Any, Optional, Literal
+from typing import Any, Optional
+from typing_extensions import Literal
 from inflection import underscore
 from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img
 from modules.shared import sd_upscalers, opts, parser
+from typing import Dict, List
 
 API_NOT_ALLOWED = [
     "self",
@@ -128,12 +130,12 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
 ).generate_model()
 
 class TextToImageResponse(BaseModel):
-    images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
+    images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
     parameters: dict
     info: str
 
 class ImageToImageResponse(BaseModel):
-    images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
+    images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
     parameters: dict
     info: str
 
@@ -166,18 +168,17 @@ class FileData(BaseModel):
     name: str = Field(title="File name")
 
 class ExtrasBatchImagesRequest(ExtrasBaseRequest):
-    imageList: list[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings")
+    imageList: List[FileData] = Field(title="Images", description="List of images to work on. Must be Base64 strings")
 
 class ExtrasBatchImagesResponse(ExtraBaseResponse):
-    images: list[str] = Field(title="Images", description="The generated images in base64 format.")
+    images: List[str] = Field(title="Images", description="The generated images in base64 format.")
 
 class PNGInfoRequest(BaseModel):
     image: str = Field(title="Image", description="The base64 encoded PNG image")
 
 class PNGInfoResponse(BaseModel):
     info: str = Field(title="Image info", description="A string with the parameters used to generate the image")
-    items: dict = Field(title="Items", description="A dictionary containing all the other fields the image had")
-    parameters: dict = Field(title="Parameters", description="A dictionary with parsed generation info fields")
+    items: dict = Field(title="Items", description="An object containing all the info the image had")
 
 class ProgressRequest(BaseModel):
     skip_current_image: bool = Field(default=False, title="Skip current image", description="Skip current image serialization")
@@ -231,8 +232,8 @@ FlagsModel = create_model("Flags", **flags)
 
 class SamplerItem(BaseModel):
     name: str = Field(title="Name")
-    aliases: list[str] = Field(title="Aliases")
-    options: dict[str, str] = Field(title="Options")
+    aliases: List[str] = Field(title="Aliases")
+    options: Dict[str, str] = Field(title="Options")
 
 class UpscalerItem(BaseModel):
     name: str = Field(title="Name")
@@ -283,8 +284,8 @@ class EmbeddingItem(BaseModel):
     vectors: int = Field(title="Vectors", description="The number of vectors in the embedding")
 
 class EmbeddingsResponse(BaseModel):
-    loaded: dict[str, EmbeddingItem] = Field(title="Loaded", description="Embeddings loaded for the current model")
-    skipped: dict[str, EmbeddingItem] = Field(title="Skipped", description="Embeddings skipped for the current model (likely due to architecture incompatibility)")
+    loaded: Dict[str, EmbeddingItem] = Field(title="Loaded", description="Embeddings loaded for the current model")
+    skipped: Dict[str, EmbeddingItem] = Field(title="Skipped", description="Embeddings skipped for the current model (likely due to architecture incompatibility)")
 
 class MemoryResponse(BaseModel):
     ram: dict = Field(title="RAM", description="System memory stats")
@@ -302,20 +303,11 @@ class ScriptArg(BaseModel):
     minimum: Optional[Any] = Field(default=None, title="Minimum", description="Minimum allowed value for the argumentin UI")
     maximum: Optional[Any] = Field(default=None, title="Minimum", description="Maximum allowed value for the argumentin UI")
     step: Optional[Any] = Field(default=None, title="Minimum", description="Step for changing value of the argumentin UI")
-    choices: Optional[list[str]] = Field(default=None, title="Choices", description="Possible values for the argument")
+    choices: Optional[List[str]] = Field(default=None, title="Choices", description="Possible values for the argument")
 
 
 class ScriptInfo(BaseModel):
     name: str = Field(default=None, title="Name", description="Script name")
     is_alwayson: bool = Field(default=None, title="IsAlwayson", description="Flag specifying whether this script is an alwayson script")
     is_img2img: bool = Field(default=None, title="IsImg2img", description="Flag specifying whether this script is an img2img script")
-    args: list[ScriptArg] = Field(title="Arguments", description="List of script's arguments")
-
-class ExtensionItem(BaseModel):
-    name: str = Field(title="Name", description="Extension name")
-    remote: str = Field(title="Remote", description="Extension Repository URL")
-    branch: str = Field(title="Branch", description="Extension Repository Branch")
-    commit_hash: str = Field(title="Commit Hash", description="Extension Repository Commit Hash")
-    version: str = Field(title="Version", description="Extension Version")
-    commit_date: str = Field(title="Commit Date", description="Extension Repository Commit Date")
-    enabled: bool = Field(title="Enabled", description="Flag specifying whether this extension is enabled")
+    args: List[ScriptArg] = Field(title="Arguments", description="List of script's arguments")

modules/cmd_args.py

@@ -90,7 +90,7 @@ parser.add_argument("--autolaunch", action='store_true', help="open the webui UR
 parser.add_argument("--theme", type=str, help="launches the UI with light or dark theme", default=None)
 parser.add_argument("--use-textbox-seed", action='store_true', help="use textbox for seeds in UI (no up/down, but possible to input long seeds)", default=False)
 parser.add_argument("--disable-console-progressbars", action='store_true', help="do not output progressbars to console", default=False)
-parser.add_argument("--enable-console-prompts", action='store_true', help="does not do anything", default=False)  # Legacy compatibility, use as default value shared.opts.enable_console_prompts
+parser.add_argument("--enable-console-prompts", action='store_true', help="print prompts to console when generating with txt2img and img2img", default=False)
 parser.add_argument('--vae-path', type=str, help='Checkpoint to use as VAE; setting this argument disables all settings related to VAE', default=None)
 parser.add_argument("--disable-safe-unpickle", action='store_true', help="disable checking pytorch models for malicious code", default=False)
 parser.add_argument("--api", action='store_true', help="use api=True to launch the API together with the webui (use --nowebui instead for only the API)")
@@ -112,9 +112,8 @@ parser.add_argument("--skip-version-check", action='store_true', help="Do not ch
 parser.add_argument("--no-hashing", action='store_true', help="disable sha256 hashing of checkpoints to help loading performance", default=False)
 parser.add_argument("--no-download-sd-model", action='store_true', help="don't download SD1.5 model even if no model is found in --ckpt-dir", default=False)
 parser.add_argument('--subpath', type=str, help='customize the subpath for gradio, use with reverse proxy')
-parser.add_argument('--add-stop-route', action='store_true', help='does not do anything')
+parser.add_argument('--add-stop-route', action='store_true', help='add /_stop route to stop server')
 parser.add_argument('--api-server-stop', action='store_true', help='enable server stop/restart/kill via api')
 parser.add_argument('--timeout-keep-alive', type=int, default=30, help='set timeout_keep_alive for uvicorn')
 parser.add_argument("--disable-all-extensions", action='store_true', help="prevent all extensions from running regardless of any other settings", default=False)
-parser.add_argument("--disable-extra-extensions", action='store_true', help="prevent all extensions except built-in from running regardless of any other settings", default=False)
-parser.add_argument("--skip-load-model-at-start", action='store_true', help="if load a model at web start, only take effect when --nowebui", )
+parser.add_argument("--disable-extra-extensions", action='store_true', help=" prevent all extensions except built-in from running regardless of any other settings", default=False)

modules/config_states.py

@@ -4,6 +4,7 @@ Supports saving and restoring webui and extensions from a known working set of c
 
 import os
 import json
+import time
 import tqdm
 
 from datetime import datetime
@@ -37,7 +38,7 @@ def list_config_states():
     config_states = sorted(config_states, key=lambda cs: cs["created_at"], reverse=True)
 
     for cs in config_states:
-        timestamp = datetime.fromtimestamp(cs["created_at"]).strftime('%Y-%m-%d %H:%M:%S')
+        timestamp = time.asctime(time.gmtime(cs["created_at"]))
         name = cs.get("name", "Config")
         full_name = f"{name}: {timestamp}"
         all_config_states[full_name] = cs

modules/devices.py

@@ -60,8 +60,7 @@ def enable_tf32():
 
         # enabling benchmark option seems to enable a range of cards to do fp16 when they otherwise can't
         # see https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/4407
-        device_id = (int(shared.cmd_opts.device_id) if shared.cmd_opts.device_id is not None and shared.cmd_opts.device_id.isdigit() else 0) or torch.cuda.current_device()
-        if torch.cuda.get_device_capability(device_id) == (7, 5) and torch.cuda.get_device_name(device_id).startswith("NVIDIA GeForce GTX 16"):
+        if any(torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())):
             torch.backends.cudnn.benchmark = True
 
         torch.backends.cuda.matmul.allow_tf32 = True

modules/generation_parameters_copypaste.py

@@ -9,7 +9,7 @@ from modules.paths import data_path
 from modules import shared, ui_tempdir, script_callbacks, processing
 from PIL import Image
 
-re_param_code = r'\s*(\w[\w \-/]+):\s*("(?:\\.|[^\\"])+"|[^,]*)(?:,|$)'
+re_param_code = r'\s*([\w ]+):\s*("(?:\\.|[^\\"])+"|[^,]*)(?:,|$)'
 re_param = re.compile(re_param_code)
 re_imagesize = re.compile(r"^(\d+)x(\d+)$")
 re_hypernet_hash = re.compile("\(([0-9a-f]+)\)$")

modules/gitpython_hack.py

@@ -23,7 +23,7 @@ class Git(git.Git):
         )
         return self._parse_object_header(ret)
 
-    def stream_object_data(self, ref: str) -> tuple[str, str, int, Git.CatFileContentStream]:
+    def stream_object_data(self, ref: str) -> tuple[str, str, int, "Git.CatFileContentStream"]:
         # Not really streaming, per se; this buffers the entire object in memory.
         # Shouldn't be a problem for our use case, since we're only using this for
         # object headers (commit objects).

modules/hypernetworks/hypernetwork.py

@@ -468,7 +468,7 @@ def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None,
     shared.reload_hypernetworks()
 
 
-def train_hypernetwork(id_task, hypernetwork_name: str, learn_rate: float, batch_size: int, gradient_step: int, data_root: str, log_directory: str, training_width: int, training_height: int, varsize: bool, steps: int, clip_grad_mode: str, clip_grad_value: float, shuffle_tags: bool, tag_drop_out: bool, latent_sampling_method: str, use_weight: bool, create_image_every: int, save_hypernetwork_every: int, template_filename: str, preview_from_txt2img: bool, preview_prompt: str, preview_negative_prompt: str, preview_steps: int, preview_sampler_name: str, preview_cfg_scale: float, preview_seed: int, preview_width: int, preview_height: int):
+def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, use_weight, create_image_every, save_hypernetwork_every, template_filename, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     from modules import images, processing
 
     save_hypernetwork_every = save_hypernetwork_every or 0
@@ -698,7 +698,7 @@ def train_hypernetwork(id_task, hypernetwork_name: str, learn_rate: float, batch
                         p.prompt = preview_prompt
                         p.negative_prompt = preview_negative_prompt
                         p.steps = preview_steps
-                        p.sampler_name = sd_samplers.samplers_map[preview_sampler_name.lower()]
+                        p.sampler_name = sd_samplers.samplers[preview_sampler_index].name
                         p.cfg_scale = preview_cfg_scale
                         p.seed = preview_seed
                         p.width = preview_width

modules/images.py

@@ -561,8 +561,6 @@ def save_image_with_geninfo(image, geninfo, filename, extension=None, existing_p
             })
 
             piexif.insert(exif_bytes, filename)
-    elif extension.lower() == ".gif":
-        image.save(filename, format=image_format, comment=geninfo)
     else:
         image.save(filename, format=image_format, quality=opts.jpeg_quality)
 
@@ -663,13 +661,7 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i
 
         save_image_with_geninfo(image_to_save, info, temp_file_path, extension, existing_pnginfo=params.pnginfo, pnginfo_section_name=pnginfo_section_name)
 
-        filename = filename_without_extension + extension
-        if shared.opts.save_images_replace_action != "Replace":
-            n = 0
-            while os.path.exists(filename):
-                n += 1
-                filename = f"{filename_without_extension}-{n}{extension}"
-        os.replace(temp_file_path, filename)
+        os.replace(temp_file_path, filename_without_extension + extension)
 
     fullfn_without_extension, extension = os.path.splitext(params.filename)
     if hasattr(os, 'statvfs'):
@@ -726,12 +718,7 @@ def read_info_from_image(image: Image.Image) -> tuple[str | None, dict]:
     geninfo = items.pop('parameters', None)
 
     if "exif" in items:
-        exif_data = items["exif"]
-        try:
-            exif = piexif.load(exif_data)
-        except OSError:
-            # memory / exif was not valid so piexif tried to read from a file
-            exif = None
+        exif = piexif.load(items["exif"])
         exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')
         try:
             exif_comment = piexif.helper.UserComment.load(exif_comment)
@@ -741,8 +728,6 @@ def read_info_from_image(image: Image.Image) -> tuple[str | None, dict]:
         if exif_comment:
             items['exif comment'] = exif_comment
             geninfo = exif_comment
-    elif "comment" in items: # for gif
-        geninfo = items["comment"].decode('utf8', errors="ignore")
 
     for field in IGNORED_INFO_KEYS:
         items.pop(field, None)

modules/img2img.py

@@ -10,7 +10,6 @@ from modules import images as imgutil
 from modules.generation_parameters_copypaste import create_override_settings_dict, parse_generation_parameters
 from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
 from modules.shared import opts, state
-from modules.sd_models import get_closet_checkpoint_match
 import modules.shared as shared
 import modules.processing as processing
 from modules.ui import plaintext_to_html
@@ -42,8 +41,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
     cfg_scale = p.cfg_scale
     sampler_name = p.sampler_name
     steps = p.steps
-    override_settings = p.override_settings
-    sd_model_checkpoint_override = get_closet_checkpoint_match(override_settings.get("sd_model_checkpoint", None))
+
     for i, image in enumerate(images):
         state.job = f"{i+1} out of {len(images)}"
         if state.skipped:
@@ -106,27 +104,15 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
             p.sampler_name = parsed_parameters.get("Sampler", sampler_name)
             p.steps = int(parsed_parameters.get("Steps", steps))
 
-            model_info = get_closet_checkpoint_match(parsed_parameters.get("Model hash", None))
-            if model_info is not None:
-                p.override_settings['sd_model_checkpoint'] = model_info.name
-            elif sd_model_checkpoint_override:
-                p.override_settings['sd_model_checkpoint'] = sd_model_checkpoint_override
-            else:
-                p.override_settings.pop("sd_model_checkpoint", None)
-
-        if output_dir:
-            p.outpath_samples = output_dir
-            p.override_settings['save_to_dirs'] = False
-            p.override_settings['save_images_replace_action'] = "Add number suffix"
-            if p.n_iter > 1 or p.batch_size > 1:
-                p.override_settings['samples_filename_pattern'] = f'{image_path.stem}-[generation_number]'
-            else:
-                p.override_settings['samples_filename_pattern'] = f'{image_path.stem}'
-
         proc = modules.scripts.scripts_img2img.run(p, *args)
-
         if proc is None:
-            p.override_settings.pop('save_images_replace_action', None)
+            if output_dir:
+                p.outpath_samples = output_dir
+                p.override_settings['save_to_dirs'] = False
+                if p.n_iter > 1 or p.batch_size > 1:
+                    p.override_settings['samples_filename_pattern'] = f'{image_path.stem}-[generation_number]'
+                else:
+                    p.override_settings['samples_filename_pattern'] = f'{image_path.stem}'
             process_images(p)
 
 
@@ -203,7 +189,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
 
     p.user = request.username
 
-    if shared.opts.enable_console_prompts:
+    if shared.cmd_opts.enable_console_prompts:
         print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
 
     if mask:

modules/initialize.py

@@ -151,8 +151,8 @@ def initialize_rest(*, reload_script_modules=False):
 
         from modules import devices
         devices.first_time_calculation()
-    if not shared.cmd_opts.skip_load_model_at_start:
-        Thread(target=load_model).start()
+
+    Thread(target=load_model).start()
 
     from modules import shared_items
     shared_items.reload_hypernetworks()

modules/launch_utils.py

@@ -64,7 +64,7 @@ Use --skip-python-version-check to suppress this warning.
 @lru_cache()
 def commit_hash():
     try:
-        return subprocess.check_output([git, "-C", script_path, "rev-parse", "HEAD"], shell=False, encoding='utf8').strip()
+        return subprocess.check_output([git, "rev-parse", "HEAD"], shell=False, encoding='utf8').strip()
     except Exception:
         return "<none>"
 
@@ -72,7 +72,7 @@ def commit_hash():
 @lru_cache()
 def git_tag():
     try:
-        return subprocess.check_output([git, "-C", script_path, "describe", "--tags"], shell=False, encoding='utf8').strip()
+        return subprocess.check_output([git, "describe", "--tags"], shell=False, encoding='utf8').strip()
     except Exception:
         try:
 

modules/localization.py

@@ -14,24 +14,21 @@ def list_localizations(dirname):
         if ext.lower() != ".json":
             continue
 
-        localizations[fn] = [os.path.join(dirname, file)]
+        localizations[fn] = os.path.join(dirname, file)
 
     for file in scripts.list_scripts("localizations", ".json"):
         fn, ext = os.path.splitext(file.filename)
-        if fn not in localizations:
-            localizations[fn] = []
-        localizations[fn].append(file.path)
+        localizations[fn] = file.path
 
 
 def localization_js(current_localization_name: str) -> str:
-    fns = localizations.get(current_localization_name, None)
+    fn = localizations.get(current_localization_name, None)
     data = {}
-    if fns is not None:
-        for fn in fns:
-            try:
-                with open(fn, "r", encoding="utf8") as file:
-                    data.update(json.load(file))
-            except Exception:
-                errors.report(f"Error loading localization from {fn}", exc_info=True)
+    if fn is not None:
+        try:
+            with open(fn, "r", encoding="utf8") as file:
+                data = json.load(file)
+        except Exception:
+            errors.report(f"Error loading localization from {fn}", exc_info=True)
 
     return f"window.localization = {json.dumps(data)}"

modules/options.py

@@ -210,8 +210,6 @@ class Options:
 
     def add_option(self, key, info):
         self.data_labels[key] = info
-        if key not in self.data:
-            self.data[key] = info.default
 
     def reorder(self):
         """reorder settings so that all items related to section always go together"""

modules/paths.py

@@ -1,6 +1,6 @@
 import os
 import sys
-from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, cwd  # noqa: F401
+from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir  # noqa: F401
 
 import modules.safe  # noqa: F401
 

modules/paths_internal.py

@@ -8,7 +8,6 @@ import shlex
 commandline_args = os.environ.get('COMMANDLINE_ARGS', "")
 sys.argv += shlex.split(commandline_args)
 
-cwd = os.getcwd()
 modules_path = os.path.dirname(os.path.realpath(__file__))
 script_path = os.path.dirname(modules_path)
 

modules/processing.py

@@ -142,7 +142,7 @@ class StableDiffusionProcessing:
     overlay_images: list = None
     eta: float = None
     do_not_reload_embeddings: bool = False
-    denoising_strength: float = None
+    denoising_strength: float = 0
     ddim_discretize: str = None
     s_min_uncond: float = None
     s_churn: float = None
@@ -533,7 +533,6 @@ class Processed:
         self.all_seeds = all_seeds or p.all_seeds or [self.seed]
         self.all_subseeds = all_subseeds or p.all_subseeds or [self.subseed]
         self.infotexts = infotexts or [info]
-        self.version = program_version()
 
     def js(self):
         obj = {
@@ -568,7 +567,6 @@ class Processed:
             "job_timestamp": self.job_timestamp,
             "clip_skip": self.clip_skip,
             "is_using_inpainting_conditioning": self.is_using_inpainting_conditioning,
-            "version": self.version,
         }
 
         return json.dumps(obj)
@@ -711,7 +709,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     if p.scripts is not None:
         p.scripts.before_process(p)
 
-    stored_opts = {k: opts.data[k] for k in p.override_settings.keys() if k in opts.data}
+    stored_opts = {k: opts.data[k] for k in p.override_settings.keys()}
 
     try:
         # if no checkpoint override or the override checkpoint can't be found, remove override entry and load opts checkpoint

modules/processing_scripts/seed.py

@@ -29,8 +29,8 @@ class ScriptSeed(scripts.ScriptBuiltinUI):
             else:
                 self.seed = gr.Number(label='Seed', value=-1, elem_id=self.elem_id("seed"), min_width=100, precision=0)
 
-            random_seed = ToolButton(ui.random_symbol, elem_id=self.elem_id("random_seed"), tooltip="Set seed to -1, which will cause a new random number to be used every time")
-            reuse_seed = ToolButton(ui.reuse_symbol, elem_id=self.elem_id("reuse_seed"), tooltip="Reuse seed from last generation, mostly useful if it was randomized")
+            random_seed = ToolButton(ui.random_symbol, elem_id=self.elem_id("random_seed"), label='Random seed')
+            reuse_seed = ToolButton(ui.reuse_symbol, elem_id=self.elem_id("reuse_seed"), label='Reuse seed')
 
             seed_checkbox = gr.Checkbox(label='Extra', elem_id=self.elem_id("subseed_show"), value=False)
 

modules/prompt_parser.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import re
 from collections import namedtuple
+from typing import List
 import lark
 
 # a prompt like this: "fantasy landscape with a [mountain:lake:0.25] and [an oak:a christmas tree:0.75][ in foreground::0.6][ in background:0.25] [shoddy:masterful:0.5]"
@@ -239,14 +240,14 @@ def get_multicond_prompt_list(prompts: SdConditioning | list[str]):
 
 class ComposableScheduledPromptConditioning:
     def __init__(self, schedules, weight=1.0):
-        self.schedules: list[ScheduledPromptConditioning] = schedules
+        self.schedules: List[ScheduledPromptConditioning] = schedules
         self.weight: float = weight
 
 
 class MulticondLearnedConditioning:
     def __init__(self, shape, batch):
         self.shape: tuple = shape  # the shape field is needed to send this object to DDIM/PLMS
-        self.batch: list[list[ComposableScheduledPromptConditioning]] = batch
+        self.batch: List[List[ComposableScheduledPromptConditioning]] = batch
 
 
 def get_multicond_learned_conditioning(model, prompts, steps, hires_steps=None, use_old_scheduling=False) -> MulticondLearnedConditioning:
@@ -277,7 +278,7 @@ class DictWithShape(dict):
         return self["crossattn"].shape
 
 
-def reconstruct_cond_batch(c: list[list[ScheduledPromptConditioning]], current_step):
+def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], current_step):
     param = c[0][0].cond
     is_dict = isinstance(param, dict)
 

modules/restart.py

@@ -14,9 +14,7 @@ def is_restartable() -> bool:
 def restart_program() -> None:
     """creates file tmp/restart and immediately stops the process, which webui.bat/webui.sh interpret as a command to start webui again"""
 
-    tmpdir = Path(script_path) / "tmp"
-    tmpdir.mkdir(parents=True, exist_ok=True)
-    (tmpdir / "restart").touch()
+    (Path(script_path) / "tmp" / "restart").touch()
 
     stop_program()
 

modules/script_callbacks.py

@@ -1,7 +1,7 @@
 import inspect
 import os
 from collections import namedtuple
-from typing import Optional, Any
+from typing import Optional, Dict, Any
 
 from fastapi import FastAPI
 from gradio import Blocks
@@ -258,7 +258,7 @@ def image_grid_callback(params: ImageGridLoopParams):
             report_exception(c, 'image_grid')
 
 
-def infotext_pasted_callback(infotext: str, params: dict[str, Any]):
+def infotext_pasted_callback(infotext: str, params: Dict[str, Any]):
     for c in callback_map['callbacks_infotext_pasted']:
         try:
             c.callback(infotext, params)
@@ -449,7 +449,7 @@ def on_infotext_pasted(callback):
     """register a function to be called before applying an infotext.
     The callback is called with two arguments:
        - infotext: str - raw infotext.
-       - result: dict[str, any] - parsed infotext parameters.
+       - result: Dict[str, any] - parsed infotext parameters.
     """
     add_callback(callback_map['callbacks_infotext_pasted'], callback)
 

modules/scripts.py

@@ -491,15 +491,11 @@ class ScriptRunner:
 
             arg_info = api_models.ScriptArg(label=control.label or "")
 
-            for field in ("value", "minimum", "maximum", "step"):
+            for field in ("value", "minimum", "maximum", "step", "choices"):
                 v = getattr(control, field, None)
                 if v is not None:
                     setattr(arg_info, field, v)
 
-            choices = getattr(control, 'choices', None)  # as of gradio 3.41, some items in choices are strings, and some are tuples where the first elem is the string
-            if choices is not None:
-                arg_info.choices = [x[0] if isinstance(x, tuple) else x for x in choices]
-
             api_args.append(arg_info)
 
         script.api_info = api_models.ScriptInfo(

modules/sd_hijack.py

@@ -2,7 +2,7 @@ import torch
 from torch.nn.functional import silu
 from types import MethodType
 
-from modules import devices, sd_hijack_optimizations, shared, script_callbacks, errors, sd_unet, patches
+from modules import devices, sd_hijack_optimizations, shared, script_callbacks, errors, sd_unet
 from modules.hypernetworks import hypernetwork
 from modules.shared import cmd_opts
 from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr
@@ -10,7 +10,6 @@ from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hija
 import ldm.modules.attention
 import ldm.modules.diffusionmodules.model
 import ldm.modules.diffusionmodules.openaimodel
-import ldm.models.diffusion.ddpm
 import ldm.models.diffusion.ddim
 import ldm.models.diffusion.plms
 import ldm.modules.encoders.modules
@@ -38,8 +37,6 @@ ldm.models.diffusion.ddpm.print = shared.ldm_print
 optimizers = []
 current_optimizer: sd_hijack_optimizations.SdOptimization = None
 
-ldm_original_forward = patches.patch(__file__, ldm.modules.diffusionmodules.openaimodel.UNetModel, "forward", sd_unet.UNetModel_forward)
-sgm_original_forward = patches.patch(__file__, sgm.modules.diffusionmodules.openaimodel.UNetModel, "forward", sd_unet.UNetModel_forward)
 
 def list_optimizers():
     new_optimizers = script_callbacks.list_optimizers_callback()
@@ -242,13 +239,10 @@ class StableDiffusionModelHijack:
 
         self.layers = flatten(m)
 
-        if isinstance(m, ldm.models.diffusion.ddpm.LatentDiffusion):
-            sd_unet.original_forward = ldm_original_forward
-        elif isinstance(m, sgm.models.diffusion.DiffusionEngine):
-            sd_unet.original_forward = sgm_original_forward
-        else:
-            sd_unet.original_forward = None
+        if not hasattr(ldm.modules.diffusionmodules.openaimodel, 'copy_of_UNetModel_forward_for_webui'):
+            ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui = ldm.modules.diffusionmodules.openaimodel.UNetModel.forward
 
+        ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = sd_unet.UNetModel_forward
 
     def undo_hijack(self, m):
         conditioner = getattr(m, 'conditioner', None)
@@ -285,8 +279,7 @@ class StableDiffusionModelHijack:
         self.layers = None
         self.clip = None
 
-        sd_unet.original_forward = None
-
+        ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui
 
     def apply_circular(self, enable):
         if self.circular_enabled == enable:

modules/sd_models.py

@@ -7,17 +7,16 @@ import threading
 import torch
 import re
 import safetensors.torch
-from omegaconf import OmegaConf, ListConfig
+from omegaconf import OmegaConf
 from os import mkdir
 from urllib import request
 import ldm.modules.midas as midas
 
 from ldm.util import instantiate_from_config
 
-from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache, extra_networks, processing, lowvram, sd_hijack, patches
+from modules import paths, shared, modelloader, devices, script_callbacks, sd_vae, sd_disable_initialization, errors, hashes, sd_models_config, sd_unet, sd_models_xl, cache, extra_networks, processing, lowvram, sd_hijack
 from modules.timer import Timer
 import tomesd
-import numpy as np
 
 model_dir = "Stable-diffusion"
 model_path = os.path.abspath(os.path.join(paths.models_path, model_dir))
@@ -50,12 +49,11 @@ class CheckpointInfo:
     def __init__(self, filename):
         self.filename = filename
         abspath = os.path.abspath(filename)
-        abs_ckpt_dir = os.path.abspath(shared.cmd_opts.ckpt_dir) if shared.cmd_opts.ckpt_dir is not None else None
 
         self.is_safetensors = os.path.splitext(filename)[1].lower() == ".safetensors"
 
-        if abs_ckpt_dir and abspath.startswith(abs_ckpt_dir):
-            name = abspath.replace(abs_ckpt_dir, '')
+        if shared.cmd_opts.ckpt_dir is not None and abspath.startswith(shared.cmd_opts.ckpt_dir):
+            name = abspath.replace(shared.cmd_opts.ckpt_dir, '')
         elif abspath.startswith(model_path):
             name = abspath.replace(model_path, '')
         else:
@@ -131,12 +129,9 @@ except Exception:
 
 
 def setup_model():
-    """called once at startup to do various one-time tasks related to SD models"""
-
     os.makedirs(model_path, exist_ok=True)
 
     enable_midas_autodownload()
-    patch_given_betas()
 
 
 def checkpoint_tiles(use_short=False):
@@ -314,8 +309,6 @@ def get_checkpoint_state_dict(checkpoint_info: CheckpointInfo, timer):
     if checkpoint_info in checkpoints_loaded:
         # use checkpoint cache
         print(f"Loading weights [{sd_model_hash}] from cache")
-        # move to end as latest
-        checkpoints_loaded.move_to_end(checkpoint_info)
         return checkpoints_loaded[checkpoint_info]
 
     print(f"Loading weights [{sd_model_hash}] from {checkpoint_info.filename}")
@@ -460,20 +453,6 @@ def enable_midas_autodownload():
     midas.api.load_model = load_model_wrapper
 
 
-def patch_given_betas():
-    import ldm.models.diffusion.ddpm
-
-    def patched_register_schedule(*args, **kwargs):
-        """a modified version of register_schedule function that converts plain list from Omegaconf into numpy"""
-
-        if isinstance(args[1], ListConfig):
-            args = (args[0], np.array(args[1]), *args[2:])
-
-        original_register_schedule(*args, **kwargs)
-
-    original_register_schedule = patches.patch(__name__, ldm.models.diffusion.ddpm.DDPM, 'register_schedule', patched_register_schedule)
-
-
 def repair_config(sd_config):
 
     if not hasattr(sd_config.model.params, "use_ema"):

modules/sd_unet.py

@@ -1,11 +1,11 @@
 import torch.nn
+import ldm.modules.diffusionmodules.openaimodel
 
 from modules import script_callbacks, shared, devices
 
 unet_options = []
 current_unet_option = None
 current_unet = None
-original_forward = None
 
 
 def list_unets():
@@ -88,5 +88,5 @@ def UNetModel_forward(self, x, timesteps=None, context=None, *args, **kwargs):
     if current_unet is not None:
         return current_unet.forward(x, timesteps, context, *args, **kwargs)
 
-    return original_forward(self, x, timesteps, context, *args, **kwargs)
+    return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
 

modules/shared_cmd_options.py

@@ -14,5 +14,5 @@ if os.environ.get('IGNORE_CMD_ARGS_ERRORS', None) is None:
 else:
     cmd_opts, _ = parser.parse_known_args()
 
-cmd_opts.webui_is_non_local = any([cmd_opts.share, cmd_opts.listen, cmd_opts.ngrok, cmd_opts.server_name])
-cmd_opts.disable_extension_access = cmd_opts.webui_is_non_local and not cmd_opts.enable_insecure_extension_access
+
+cmd_opts.disable_extension_access = any([cmd_opts.share, cmd_opts.listen, cmd_opts.ngrok, cmd_opts.server_name]) and not cmd_opts.enable_insecure_extension_access

modules/shared_items.py

@@ -44,9 +44,9 @@ def refresh_unet_list():
     modules.sd_unet.list_unets()
 
 
-def list_checkpoint_tiles(use_short=False):
+def list_checkpoint_tiles():
     import modules.sd_models
-    return modules.sd_models.checkpoint_tiles(use_short)
+    return modules.sd_models.checkpoint_tiles()
 
 
 def refresh_checkpoints():

modules/shared_options.py

@@ -26,7 +26,7 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "samples_format": OptionInfo('png', 'File format for images'),
     "samples_filename_pattern": OptionInfo("", "Images filename pattern", component_args=hide_dirs).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Images-Filename-Name-and-Subdirectory"),
     "save_images_add_number": OptionInfo(True, "Add number to filename when saving", component_args=hide_dirs),
-    "save_images_replace_action": OptionInfo("Replace", "Saving the image to an existing file", gr.Radio, {"choices": ["Replace", "Add number suffix"], **hide_dirs}),
+
     "grid_save": OptionInfo(True, "Always save all generated image grids"),
     "grid_format": OptionInfo('png', 'File format for grids'),
     "grid_extended_filename": OptionInfo(False, "Add extended info (seed, prompt) to filename when saving grid"),
@@ -100,7 +100,6 @@ options_templates.update(options_section(('face-restoration', "Face restoration"
 
 options_templates.update(options_section(('system', "System"), {
     "auto_launch_browser": OptionInfo("Local", "Automatically open webui in browser on startup", gr.Radio, lambda: {"choices": ["Disable", "Local", "Remote"]}),
-    "enable_console_prompts": OptionInfo(shared.cmd_opts.enable_console_prompts, "Print prompts to console when generating with txt2img and img2img."),
     "show_warnings": OptionInfo(False, "Show warnings in console.").needs_reload_ui(),
     "show_gradio_deprecation_warnings": OptionInfo(True, "Show gradio deprecation warnings in console.").needs_reload_ui(),
     "memmon_poll_rate": OptionInfo(8, "VRAM usage polls per second during generation.", gr.Slider, {"minimum": 0, "maximum": 40, "step": 1}).info("0 = disable"),
@@ -134,7 +133,7 @@ options_templates.update(options_section(('training', "Training"), {
 }))
 
 options_templates.update(options_section(('sd', "Stable Diffusion"), {
-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles(shared.opts.sd_checkpoint_dropdown_use_short)}, refresh=shared_items.refresh_checkpoints, infotext='Model hash'),
+    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext='Model hash'),
     "sd_checkpoints_limit": OptionInfo(1, "Maximum number of checkpoints loaded at the same time", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}),
     "sd_checkpoints_keep_in_cpu": OptionInfo(True, "Only keep one model on device").info("will keep models other than the currently used one in RAM rather than VRAM"),
     "sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}).info("obsolete; set to 0 and use the two settings above instead"),
@@ -256,14 +255,12 @@ options_templates.update(options_section(('ui', "User interface"), {
     "dimensions_and_batch_together": OptionInfo(True, "Show Width/Height and Batch sliders in same row").needs_reload_ui(),
     "keyedit_precision_attention": OptionInfo(0.1, "Ctrl+up/down precision when editing (attention:1.1)", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
     "keyedit_precision_extra": OptionInfo(0.05, "Ctrl+up/down precision when editing <extra networks:0.9>", gr.Slider, {"minimum": 0.01, "maximum": 0.2, "step": 0.001}),
-    "keyedit_delimiters": OptionInfo(r".,\/!?%^*;:{}=`~() ", "Ctrl+up/down word delimiters"),
-    "keyedit_delimiters_whitespace": OptionInfo(["Tab", "Carriage Return", "Line Feed"], "Ctrl+up/down whitespace delimiters", gr.CheckboxGroup, lambda: {"choices": ["Tab", "Carriage Return", "Line Feed"]}),
+    "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(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(),
-    "sd_checkpoint_dropdown_use_short": OptionInfo(False, "Checkpoint dropdown: use filenames without paths").info("models in subdirectories like photo/sd15.ckpt will be listed as just sd15.ckpt"),
     "hires_fix_show_sampler": OptionInfo(False, "Hires fix: show hires checkpoint and sampler selection").needs_reload_ui(),
     "hires_fix_show_prompts": OptionInfo(False, "Hires fix: show hires prompt and negative prompt").needs_reload_ui(),
     "disable_token_counters": OptionInfo(False, "Disable prompt token counters").needs_reload_ui(),
@@ -308,8 +305,8 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
     's_tmax':  OptionInfo(0.0, "sigma tmax",  gr.Slider, {"minimum": 0.0, "maximum": 999.0, "step": 0.01}, infotext='Sigma tmax').info("0 = inf; end value of the sigma range; only applies to Euler, Heun, and DPM2"),
     's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.1, "step": 0.001}, infotext='Sigma noise').info('amount of additional noise to counteract loss of detail during sampling'),
     'k_sched_type':  OptionInfo("Automatic", "Scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}, infotext='Schedule type').info("lets you override the noise schedule for k-diffusion samplers; choosing Automatic disables the three parameters below"),
-    'sigma_min': OptionInfo(0.0, "sigma min", gr.Number, infotext='Schedule min sigma').info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"),
-    'sigma_max': OptionInfo(0.0, "sigma max", gr.Number, infotext='Schedule max sigma').info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"),
+    'sigma_min': OptionInfo(0.0, "sigma min", gr.Number, infotext='Schedule max sigma').info("0 = default (~0.03); minimum noise strength for k-diffusion noise scheduler"),
+    'sigma_max': OptionInfo(0.0, "sigma max", gr.Number, infotext='Schedule min sigma').info("0 = default (~14.6); maximum noise strength for k-diffusion noise scheduler"),
     'rho':  OptionInfo(0.0, "rho", gr.Number, infotext='Schedule rho').info("0 = default (7 for karras, 1 for polyexponential); higher values result in a steeper noise schedule (decreases faster)"),
     'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}, infotext='ENSD').info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"),
     'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma", infotext='Discard penultimate sigma').link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"),

modules/shared_state.py

@@ -103,7 +103,6 @@ class State:
 
     def begin(self, job: str = "(unknown)"):
         self.sampling_step = 0
-        self.time_start = time.time()
         self.job_count = -1
         self.processing_has_refined_job_count = False
         self.job_no = 0
@@ -115,6 +114,7 @@ class State:
         self.skipped = False
         self.interrupted = False
         self.textinfo = None
+        self.time_start = time.time()
         self.job = job
         devices.torch_gc()
         log.info("Starting job %s", job)

modules/sub_quadratic_attention.py

@@ -15,7 +15,7 @@ import torch
 from torch import Tensor
 from torch.utils.checkpoint import checkpoint
 import math
-from typing import Optional, NamedTuple
+from typing import Optional, NamedTuple, List
 
 
 def narrow_trunc(
@@ -97,7 +97,7 @@ def _query_chunk_attention(
         )
         return summarize_chunk(query, key_chunk, value_chunk)
 
-    chunks: list[AttnChunk] = [
+    chunks: List[AttnChunk] = [
         chunk_scanner(chunk) for chunk in torch.arange(0, k_tokens, kv_chunk_size)
     ]
     acc_chunk = AttnChunk(*map(torch.stack, zip(*chunks)))

modules/textual_inversion/textual_inversion.py

@@ -386,7 +386,7 @@ def validate_train_inputs(model_name, learn_rate, batch_size, gradient_step, dat
         assert log_directory, "Log directory is empty"
 
 
-def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, use_weight, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_name, preview_cfg_scale, preview_seed, preview_width, preview_height):
+def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, varsize, steps, clip_grad_mode, clip_grad_value, shuffle_tags, tag_drop_out, latent_sampling_method, use_weight, create_image_every, save_embedding_every, template_filename, save_image_with_stored_embedding, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):
     from modules import processing
 
     save_embedding_every = save_embedding_every or 0
@@ -590,7 +590,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
                         p.prompt = preview_prompt
                         p.negative_prompt = preview_negative_prompt
                         p.steps = preview_steps
-                        p.sampler_name = sd_samplers.samplers_map[preview_sampler_name.lower()]
+                        p.sampler_name = sd_samplers.samplers[preview_sampler_index].name
                         p.cfg_scale = preview_cfg_scale
                         p.seed = preview_seed
                         p.width = preview_width

modules/txt2img.py

@@ -3,7 +3,7 @@ from contextlib import closing
 import modules.scripts
 from modules import processing
 from modules.generation_parameters_copypaste import create_override_settings_dict
-from modules.shared import opts
+from modules.shared import opts, cmd_opts
 import modules.shared as shared
 from modules.ui import plaintext_to_html
 import gradio as gr
@@ -45,7 +45,7 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
 
     p.user = request.username
 
-    if shared.opts.enable_console_prompts:
+    if cmd_opts.enable_console_prompts:
         print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)
 
     with closing(p):

modules/ui.py

@@ -151,15 +151,11 @@ def connect_clear_prompt(button):
     )
 
 
-def update_token_counter(text, steps, *, is_positive=True):
+def update_token_counter(text, steps):
     try:
         text, _ = extra_networks.parse_prompt(text)
 
-        if is_positive:
-            _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])
-        else:
-            prompt_flat_list = [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:
@@ -173,10 +169,6 @@ def update_token_counter(text, steps, *, is_positive=True):
     return f"<span class='gr-box gr-text-input'>{token_count}/{max_length}</span>"
 
 
-def update_negative_prompt_token_counter(text, steps):
-    return update_token_counter(text, steps, is_positive=False)
-
-
 class Toprow:
     """Creates a top row UI with prompts, generate button, styles, extra little buttons for things, and enables some functionality related to their operation"""
 
@@ -223,10 +215,9 @@ class Toprow:
                     )
 
                 with gr.Row(elem_id=f"{id_part}_tools"):
-                    self.paste = ToolButton(value=paste_symbol, elem_id="paste", tooltip="Read generation parameters from prompt or last generation if prompt is empty into user interface.")
-                    self.clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt", tooltip="Clear prompt")
-                    self.apply_styles = ToolButton(value=ui_prompt_styles.styles_materialize_symbol, elem_id=f"{id_part}_style_apply", tooltip="Apply all selected styles to prompts.")
-                    self.restore_progress_button = ToolButton(value=restore_progress_symbol, elem_id=f"{id_part}_restore_progress", visible=False, tooltip="Restore progress")
+                    self.paste = ToolButton(value=paste_symbol, elem_id="paste")
+                    self.clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")
+                    self.restore_progress_button = ToolButton(value=restore_progress_symbol, elem_id=f"{id_part}_restore_progress", visible=False)
 
                     self.token_counter = gr.HTML(value="<span>0/75</span>", elem_id=f"{id_part}_token_counter", elem_classes=["token-counter"])
                     self.token_button = gr.Button(visible=False, elem_id=f"{id_part}_token_button")
@@ -241,7 +232,6 @@ class Toprow:
                     )
 
                 self.ui_styles = ui_prompt_styles.UiPromptStyles(id_part, self.prompt, self.negative_prompt)
-                self.ui_styles.setup_apply_button(self.apply_styles)
 
         self.prompt_img.change(
             fn=modules.images.image_data,
@@ -358,7 +348,7 @@ def create_ui():
                                 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", tooltip="Switch width/height")
+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn", label="Switch dims")
 
                             if opts.dimensions_and_batch_together:
                                 with gr.Column(elem_id="txt2img_column_batch"):
@@ -543,7 +533,7 @@ def create_ui():
             ]
 
             toprow.token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.prompt, steps], outputs=[toprow.token_counter])
-            toprow.negative_token_button.click(fn=wrap_queued_call(update_negative_prompt_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_token_counter])
+            toprow.negative_token_button.click(fn=wrap_queued_call(update_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_token_counter])
 
         extra_networks_ui = ui_extra_networks.create_ui(txt2img_interface, [txt2img_generation_tab], 'txt2img')
         ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)
@@ -624,7 +614,7 @@ def create_ui():
                         with gr.Accordion("PNG info", open=False):
                             img2img_batch_use_png_info = gr.Checkbox(label="Append png info to prompts", **shared.hide_dirs, elem_id="img2img_batch_use_png_info")
                             img2img_batch_png_info_dir = gr.Textbox(label="PNG info directory", **shared.hide_dirs, placeholder="Leave empty to use input directory", elem_id="img2img_batch_png_info_dir")
-                            img2img_batch_png_info_props = gr.CheckboxGroup(["Prompt", "Negative prompt", "Seed", "CFG scale", "Sampler", "Steps", "Model hash"], label="Parameters to take from png info", info="Prompts from png info will be appended to prompts set in ui.")
+                            img2img_batch_png_info_props = gr.CheckboxGroup(["Prompt", "Negative prompt", "Seed", "CFG scale", "Sampler", "Steps"], label="Parameters to take from png info", info="Prompts from png info will be appended to prompts set in ui.")
 
                     img2img_tabs = [tab_img2img, tab_sketch, tab_inpaint, tab_inpaint_color, tab_inpaint_upload, tab_batch]
 
@@ -671,8 +661,8 @@ def create_ui():
                                                 width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
                                                 height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
                                             with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
-                                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn", tooltip="Switch width/height")
-                                                detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn", tooltip="Auto detect size from img2img")
+                                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
+                                                detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")
 
                                     with gr.Tab(label="Resize by", elem_id="img2img_tab_resize_by") as tab_scale_by:
                                         scale_by = gr.Slider(minimum=0.05, maximum=4.0, step=0.05, label="Scale", value=1.0, elem_id="img2img_scale")
@@ -1348,6 +1338,7 @@ checkpoint: <a id="sd_checkpoint_hash">N/A</a>
 
 def setup_ui_api(app):
     from pydantic import BaseModel, Field
+    from typing import List
 
     class QuicksettingsHint(BaseModel):
         name: str = Field(title="Name of the quicksettings field")
@@ -1356,7 +1347,7 @@ def setup_ui_api(app):
     def quicksettings_hint():
         return [QuicksettingsHint(name=k, label=v.label) for k, v in opts.data_labels.items()]
 
-    app.add_api_route("/internal/quicksettings-hint", quicksettings_hint, methods=["GET"], response_model=list[QuicksettingsHint])
+    app.add_api_route("/internal/quicksettings-hint", quicksettings_hint, methods=["GET"], response_model=List[QuicksettingsHint])
 
     app.add_api_route("/internal/ping", lambda: {}, methods=["GET"])
 

modules/ui_extensions.py

@@ -197,7 +197,7 @@ def update_config_states_table(state_name):
         config_state = config_states.all_config_states[state_name]
 
     config_name = config_state.get("name", "Config")
-    created_date = datetime.fromtimestamp(config_state["created_at"]).strftime('%Y-%m-%d %H:%M:%S')
+    created_date = time.asctime(time.gmtime(config_state["created_at"]))
     filepath = config_state.get("filepath", "<unknown>")
 
     try:

modules/ui_extra_networks.py

@@ -1,4 +1,3 @@
-import functools
 import os.path
 import urllib.parse
 from pathlib import Path
@@ -16,17 +15,6 @@ from modules.ui_components import ToolButton
 extra_pages = []
 allowed_dirs = set()
 
-default_allowed_preview_extensions = ["png", "jpg", "jpeg", "webp", "gif"]
-
-
-@functools.cache
-def allowed_preview_extensions_with_extra(extra_extensions=None):
-    return set(default_allowed_preview_extensions) | set(extra_extensions or [])
-
-
-def allowed_preview_extensions():
-    return allowed_preview_extensions_with_extra((shared.opts.samples_format, ))
-
 
 def register_page(page):
     """registers extra networks page for the UI; recommend doing it in on_before_ui() callback for extensions"""
@@ -45,9 +33,9 @@ def fetch_file(filename: str = ""):
     if not any(Path(x).absolute() in Path(filename).absolute().parents for x in allowed_dirs):
         raise ValueError(f"File cannot be fetched: {filename}. Must be in one of directories registered by extra pages.")
 
-    ext = os.path.splitext(filename)[1].lower()[1:]
-    if ext not in allowed_preview_extensions():
-        raise ValueError(f"File cannot be fetched: {filename}. Extensions allowed: {allowed_preview_extensions()}.")
+    ext = os.path.splitext(filename)[1].lower()
+    if ext not in (".png", ".jpg", ".jpeg", ".webp", ".gif"):
+        raise ValueError(f"File cannot be fetched: {filename}. Only png, jpg, webp, and gif.")
 
     # would profit from returning 304
     return FileResponse(filename, headers={"Accept-Ranges": "bytes"})
@@ -225,9 +213,9 @@ class ExtraNetworksPage:
         metadata_button = ""
         metadata = item.get("metadata")
         if metadata:
-            metadata_button = f"<div class='metadata-button card-button' title='Show internal metadata' onclick='extraNetworksRequestMetadata(event, {quote_js(self.name)}, {quote_js(html.escape(item['name']))})'></div>"
+            metadata_button = f"<div class='metadata-button card-button' title='Show internal metadata' onclick='extraNetworksRequestMetadata(event, {quote_js(self.name)}, {quote_js(item['name'])})'></div>"
 
-        edit_button = f"<div class='edit-button card-button' title='Edit metadata' onclick='extraNetworksEditUserMetadata(event, {quote_js(tabname)}, {quote_js(self.id_page)}, {quote_js(html.escape(item['name']))})'></div>"
+        edit_button = f"<div class='edit-button card-button' title='Edit metadata' onclick='extraNetworksEditUserMetadata(event, {quote_js(tabname)}, {quote_js(self.id_page)}, {quote_js(item['name'])})'></div>"
 
         local_path = ""
         filename = item.get("filename", "")
@@ -247,7 +235,7 @@ class ExtraNetworksPage:
         if search_only and shared.opts.extra_networks_hidden_models == "Never":
             return ""
 
-        sort_keys = " ".join([f'data-sort-{k}="{html.escape(str(v))}"' for k, v in item.get("sort_keys", {}).items()]).strip()
+        sort_keys = " ".join([html.escape(f'data-sort-{k}={v}') for k, v in item.get("sort_keys", {}).items()]).strip()
 
         args = {
             "background_image": background_image,
@@ -285,7 +273,11 @@ class ExtraNetworksPage:
         Find a preview PNG for a given path (without extension) and call link_preview on it.
         """
 
-        potential_files = sum([[path + "." + ext, path + ".preview." + ext] for ext in allowed_preview_extensions()], [])
+        preview_extensions = ["png", "jpg", "jpeg", "webp"]
+        if shared.opts.samples_format not in preview_extensions:
+            preview_extensions.append(shared.opts.samples_format)
+
+        potential_files = sum([[path + "." + ext, path + ".preview." + ext] for ext in preview_extensions], [])
 
         for file in potential_files:
             if os.path.isfile(file):
@@ -382,7 +374,7 @@ def create_ui(interface: gr.Blocks, unrelated_tabs, tabname):
 
     edit_search = gr.Textbox('', show_label=False, elem_id=tabname+"_extra_search", elem_classes="search", placeholder="Search...", visible=False, interactive=True)
     dropdown_sort = gr.Dropdown(choices=['Default Sort', 'Date Created', 'Date Modified', 'Name'], value='Default Sort', elem_id=tabname+"_extra_sort", elem_classes="sort", multiselect=False, visible=False, show_label=False, interactive=True, label=tabname+"_extra_sort_order")
-    button_sortorder = ToolButton(switch_values_symbol, elem_id=tabname+"_extra_sortorder", elem_classes="sortorder", visible=False, tooltip="Invert sort order")
+    button_sortorder = ToolButton(switch_values_symbol, elem_id=tabname+"_extra_sortorder", elem_classes="sortorder", visible=False)
     button_refresh = gr.Button('Refresh', elem_id=tabname+"_extra_refresh", visible=False)
     checkbox_show_dirs = gr.Checkbox(True, label='Show dirs', elem_id=tabname+"_extra_show_dirs", elem_classes="show-dirs", visible=False)
 

modules/ui_gradio_extensions.py

@@ -2,12 +2,12 @@ import os
 import gradio as gr
 
 from modules import localization, shared, scripts
-from modules.paths import script_path, data_path, cwd
+from modules.paths import script_path, data_path
 
 
 def webpath(fn):
-    if fn.startswith(cwd):
-        web_path = os.path.relpath(fn, cwd)
+    if fn.startswith(script_path):
+        web_path = os.path.relpath(fn, script_path).replace('\\', '/')
     else:
         web_path = os.path.abspath(fn)
 

modules/ui_loadsave.py

@@ -4,7 +4,7 @@ import os
 import gradio as gr
 
 from modules import errors
-from modules.ui_components import ToolButton, InputAccordion
+from modules.ui_components import ToolButton
 
 
 def radio_choices(comp):  # gradio 3.41 changes choices from list of values to list of pairs
@@ -32,6 +32,8 @@ class UiLoadsave:
             self.error_loading = True
             errors.display(e, "loading settings")
 
+
+
     def add_component(self, path, x):
         """adds component to the registry of tracked components"""
 
@@ -41,24 +43,20 @@ class UiLoadsave:
             key = f"{path}/{field}"
 
             if getattr(obj, 'custom_script_source', None) is not None:
-                key = f"customscript/{obj.custom_script_source}/{key}"
+              key = f"customscript/{obj.custom_script_source}/{key}"
 
             if getattr(obj, 'do_not_save_to_config', False):
                 return
 
             saved_value = self.ui_settings.get(key, None)
-
-            if isinstance(obj, gr.Accordion) and isinstance(x, InputAccordion) and field == 'value':
-                field = 'open'
-
             if saved_value is None:
                 self.ui_settings[key] = getattr(obj, field)
             elif condition and not condition(saved_value):
                 pass
             else:
-                if isinstance(obj, gr.Textbox) and field == 'value':  # due to an undesirable behavior of gr.Textbox, if you give it an int value instead of str, everything dies
+                if isinstance(x, gr.Textbox) and field == 'value':  # due to an undesirable behavior of gr.Textbox, if you give it an int value instead of str, everything dies
                     saved_value = str(saved_value)
-                elif isinstance(obj, gr.Number) and field == 'value':
+                elif isinstance(x, gr.Number) and field == 'value':
                     try:
                         saved_value = float(saved_value)
                     except ValueError:
@@ -69,7 +67,7 @@ class UiLoadsave:
                     init_field(saved_value)
 
             if field == 'value' and key not in self.component_mapping:
-                self.component_mapping[key] = obj
+                self.component_mapping[key] = x
 
         if type(x) in [gr.Slider, gr.Radio, gr.Checkbox, gr.Textbox, gr.Number, gr.Dropdown, ToolButton, gr.Button] and x.visible:
             apply_field(x, 'visible')
@@ -102,12 +100,6 @@ class UiLoadsave:
 
             apply_field(x, 'value', check_dropdown, getattr(x, 'init_field', None))
 
-        if type(x) == InputAccordion:
-            if x.accordion.visible:
-                apply_field(x.accordion, 'visible')
-            apply_field(x, 'value')
-            apply_field(x.accordion, 'value')
-
         def check_tab_id(tab_id):
             tab_items = list(filter(lambda e: isinstance(e, gr.TabItem), x.children))
             if type(tab_id) == str:

modules/ui_prompt_styles.py

@@ -4,7 +4,6 @@ from modules import shared, ui_common, ui_components, styles
 
 styles_edit_symbol = '\U0001f58c\uFE0F'  # 🖌️
 styles_materialize_symbol = '\U0001f4cb'  # 📋
-styles_copy_symbol = '\U0001f4dd'  # 📝
 
 
 def select_style(name):
@@ -53,8 +52,6 @@ def refresh_styles():
 class UiPromptStyles:
     def __init__(self, tabname, main_ui_prompt, main_ui_negative_prompt):
         self.tabname = tabname
-        self.main_ui_prompt = main_ui_prompt
-        self.main_ui_negative_prompt = main_ui_negative_prompt
 
         with gr.Row(elem_id=f"{tabname}_styles_row"):
             self.dropdown = gr.Dropdown(label="Styles", show_label=False, elem_id=f"{tabname}_styles", choices=list(shared.prompt_styles.styles), value=[], multiselect=True, tooltip="Styles")
@@ -64,8 +61,7 @@ class UiPromptStyles:
             with gr.Row():
                 self.selection = gr.Dropdown(label="Styles", elem_id=f"{tabname}_styles_edit_select", choices=list(shared.prompt_styles.styles), value=[], allow_custom_value=True, info="Styles allow you to add custom text to prompt. Use the {prompt} token in style text, and it will be replaced with user's prompt when applying style. Otherwise, style's text will be added to the end of the prompt.")
                 ui_common.create_refresh_button([self.dropdown, self.selection], shared.prompt_styles.reload, lambda: {"choices": list(shared.prompt_styles.styles)}, f"refresh_{tabname}_styles")
-                self.materialize = ui_components.ToolButton(value=styles_materialize_symbol, elem_id=f"{tabname}_style_apply_dialog", tooltip="Apply all selected styles from the style selction dropdown in main UI to the prompt.")
-                self.copy = ui_components.ToolButton(value=styles_copy_symbol, elem_id=f"{tabname}_style_copy", tooltip="Copy main UI prompt to style.")
+                self.materialize = ui_components.ToolButton(value=styles_materialize_symbol, elem_id=f"{tabname}_style_apply", tooltip="Apply all selected styles from the style selction dropdown in main UI to the prompt.")
 
             with gr.Row():
                 self.prompt = gr.Textbox(label="Prompt", show_label=True, elem_id=f"{tabname}_edit_style_prompt", lines=3)
@@ -100,21 +96,15 @@ class UiPromptStyles:
             show_progress=False,
         ).then(refresh_styles, outputs=[self.dropdown, self.selection], show_progress=False)
 
-        self.setup_apply_button(self.materialize)
-
-        self.copy.click(
-            fn=lambda p, n: (p, n),
-            inputs=[main_ui_prompt, main_ui_negative_prompt],
-            outputs=[self.prompt, self.neg_prompt],
+        self.materialize.click(
+            fn=materialize_styles,
+            inputs=[main_ui_prompt, main_ui_negative_prompt, self.dropdown],
+            outputs=[main_ui_prompt, main_ui_negative_prompt, self.dropdown],
             show_progress=False,
-        )
+        ).then(fn=None, _js="function(){update_"+tabname+"_tokens(); closePopup();}", show_progress=False)
 
         ui_common.setup_dialog(button_show=edit_button, dialog=styles_dialog, button_close=self.close)
 
-    def setup_apply_button(self, button):
-        button.click(
-            fn=materialize_styles,
-            inputs=[self.main_ui_prompt, self.main_ui_negative_prompt, self.dropdown],
-            outputs=[self.main_ui_prompt, self.main_ui_negative_prompt, self.dropdown],
-            show_progress=False,
-        ).then(fn=None, _js="function(){update_"+self.tabname+"_tokens(); closePopup();}", show_progress=False)
+
+
+

modules/ui_settings.py

@@ -5,7 +5,6 @@ from modules.call_queue import wrap_gradio_call
 from modules.shared import opts
 from modules.ui_components import FormRow
 from modules.ui_gradio_extensions import reload_javascript
-from concurrent.futures import ThreadPoolExecutor, as_completed
 
 
 def get_value_for_setting(key):
@@ -64,9 +63,6 @@ class UiSettings:
     quicksettings_list = None
     quicksettings_names = None
     text_settings = None
-    show_all_pages = None
-    show_one_page = None
-    search_input = None
 
     def run_settings(self, *args):
         changed = []
@@ -139,7 +135,7 @@ class UiSettings:
                         gr.Group()
                         current_tab = gr.TabItem(elem_id=f"settings_{elem_id}", label=text)
                         current_tab.__enter__()
-                        current_row = gr.Column(elem_id=f"column_settings_{elem_id}", variant='compact')
+                        current_row = gr.Column(variant='compact')
                         current_row.__enter__()
 
                         previous_section = item.section
@@ -179,18 +175,11 @@ class UiSettings:
                     with gr.Row():
                         unload_sd_model = gr.Button(value='Unload SD checkpoint to free VRAM', elem_id="sett_unload_sd_model")
                         reload_sd_model = gr.Button(value='Reload the last SD checkpoint back into VRAM', elem_id="sett_reload_sd_model")
-                    with gr.Row():
-                        calculate_all_checkpoint_hash = gr.Button(value='Calculate hash for all checkpoint', elem_id="calculate_all_checkpoint_hash")
-                        calculate_all_checkpoint_hash_threads = gr.Number(value=1, label="Number of parallel calculations", elem_id="calculate_all_checkpoint_hash_threads", precision=0, minimum=1)
 
                 with gr.TabItem("Licenses", id="licenses", elem_id="settings_tab_licenses"):
                     gr.HTML(shared.html("licenses.html"), elem_id="licenses")
 
-                self.show_all_pages = gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
-                self.show_one_page = gr.Button(value="Show only one page", elem_id="settings_show_one_page", visible=False)
-                self.show_one_page.click(lambda: None)
-
-                self.search_input = gr.Textbox(value="", elem_id="settings_search", max_lines=1, placeholder="Search...", show_label=False)
+                gr.Button(value="Show all pages", elem_id="settings_show_all_pages")
 
                 self.text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)
 
@@ -252,21 +241,6 @@ class UiSettings:
                 outputs=[sysinfo_check_output],
             )
 
-            def calculate_all_checkpoint_hash_fn(max_thread):
-                checkpoints_list = sd_models.checkpoints_list.values()
-                with ThreadPoolExecutor(max_workers=max_thread) as executor:
-                    futures = [executor.submit(checkpoint.calculate_shorthash) for checkpoint in checkpoints_list]
-                    completed = 0
-                    for _ in as_completed(futures):
-                        completed += 1
-                        print(f"{completed} / {len(checkpoints_list)} ")
-                    print("Finish calculating hash for all checkpoints")
-
-            calculate_all_checkpoint_hash.click(
-                fn=calculate_all_checkpoint_hash_fn,
-                inputs=[calculate_all_checkpoint_hash_threads],
-            )
-
         self.interface = settings_interface
 
     def add_quicksettings(self):
@@ -320,8 +294,3 @@ class UiSettings:
             outputs=[self.component_dict[k] for k in component_keys],
             queue=False,
         )
-
-    def search(self, text):
-        print(text)
-
-        return [gr.update(visible=text in (comp.label or "")) for comp in self.components]

requirements_versions.txt

@@ -27,5 +27,6 @@ timm==0.9.2
 tomesd==0.1.3
 torch
 torchdiffeq==0.2.3
-torchsde==0.2.6
+torchsde==0.2.5
 transformers==4.30.2
+httpx==0.24.1

scripts/postprocessing_upscale.py

@@ -29,7 +29,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing):
                                 upscaling_resize_w = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="extras_upscaling_resize_w")
                                 upscaling_resize_h = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="extras_upscaling_resize_h")
                             with gr.Column(elem_id="upscaling_dimensions_row", scale=1, elem_classes="dimensions-tools"):
-                                upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn", tooltip="Switch width/height")
+                                upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn")
                                 upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
 
             with FormRow():

scripts/prompts_from_file.py

@@ -5,17 +5,11 @@ import shlex
 import modules.scripts as scripts
 import gradio as gr
 
-from modules import sd_samplers, errors, sd_models
+from modules import sd_samplers, errors
 from modules.processing import Processed, process_images
 from modules.shared import state
 
 
-def process_model_tag(tag):
-    info = sd_models.get_closet_checkpoint_match(tag)
-    assert info is not None, f'Unknown checkpoint: {tag}'
-    return info.name
-
-
 def process_string_tag(tag):
     return tag
 
@@ -33,7 +27,7 @@ def process_boolean_tag(tag):
 
 
 prompt_tags = {
-    "sd_model": process_model_tag,
+    "sd_model": None,
     "outpath_samples": process_string_tag,
     "outpath_grids": process_string_tag,
     "prompt_for_display": process_string_tag,
@@ -162,10 +156,7 @@ class Script(scripts.Script):
 
             copy_p = copy.copy(p)
             for k, v in args.items():
-                if k == "sd_model":
-                    copy_p.override_settings['sd_model_checkpoint'] = v
-                else:
-                    setattr(copy_p, k, v)
+                setattr(copy_p, k, v)
 
             proc = process_images(copy_p)
             images += proc.images

scripts/xyz_grid.py

@@ -205,14 +205,13 @@ def csv_string_to_list_strip(data_str):
 
 
 class AxisOption:
-    def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None, prepare=None):
+    def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None):
         self.label = label
         self.type = type
         self.apply = apply
         self.format_value = format_value
         self.confirm = confirm
         self.cost = cost
-        self.prepare = prepare
         self.choices = choices
 
 
@@ -537,8 +536,6 @@ class Script(scripts.Script):
 
             if opt.choices is not None and not csv_mode:
                 valslist = vals_dropdown
-            elif opt.prepare is not None:
-                valslist = opt.prepare(vals)
             else:
                 valslist = csv_string_to_list_strip(vals)
 
@@ -776,8 +773,6 @@ class Script(scripts.Script):
                 # TODO: See previous comment about intentional data misalignment.
                 adj_g = g-1 if g > 0 else g
                 images.save_image(processed.images[g], p.outpath_grids, "xyz_grid", info=processed.infotexts[g], extension=opts.grid_format, prompt=processed.all_prompts[adj_g], seed=processed.all_seeds[adj_g], grid=True, p=processed)
-                if not include_sub_grids:  # if not include_sub_grids then skip saving after the first grid
-                    break
 
         if not include_sub_grids:
             # Done with sub-grids, drop all related information:

style.css

@@ -83,10 +83,8 @@ div.compact{
     white-space: nowrap;
 }
 
-@media (pointer:fine) {
-    .gradio-dropdown ul.options li.item {
-        padding: 0.05em 0;
-    }
+.gradio-dropdown ul.options li.item {
+    padding: 0.05em 0;
 }
 
 .gradio-dropdown ul.options li.item.selected {
@@ -423,7 +421,6 @@ div#extras_scale_to_tab div.form{
 #settings > div{
     border: none;
     margin-left: 10em;
-    padding: 0 var(--spacing-xl);
 }
 
 #settings > div.tab-nav{
@@ -438,7 +435,6 @@ div#extras_scale_to_tab div.form{
     border: none;
     text-align: left;
     white-space: initial;
-    padding: 4px;
 }
 
 #settings_result{
@@ -585,6 +581,7 @@ table.popup-table .link{
     width: 100%;
     height: 100%;
     overflow: auto;
+    background-color: rgba(20, 20, 20, 0.95);
 }
 
 .global-popup *{
@@ -593,6 +590,9 @@ table.popup-table .link{
 
 .global-popup-close:before {
     content: "×";
+}
+
+.global-popup-close{
     position: fixed;
     right: 0.25em;
     top: 0;
@@ -601,20 +601,10 @@ table.popup-table .link{
     font-size: 32pt;
 }
 
-.global-popup-close{
-    position: fixed;
-    left: 0;
-    top: 0;
-    width: 100%;
-    height: 100%;
-    background-color: rgba(20, 20, 20, 0.95);
-}
-
 .global-popup-inner{
     display: inline-block;
     margin: auto;
     padding: 2em;
-    z-index: 1001;
 }
 
 /* fullpage image viewer */

webui.bat

@@ -1,7 +1,6 @@
 @echo off
 
 if not defined PYTHON (set PYTHON=python)
-if defined GIT (set "GIT_PYTHON_GIT_EXECUTABLE=%GIT%")
 if not defined VENV_DIR (set "VENV_DIR=%~dp0%venv")
 
 set SD_WEBUI_RESTART=tmp/restart

webui.py

@@ -74,7 +74,7 @@ def webui():
             if shared.opts.auto_launch_browser == "Remote" or cmd_opts.autolaunch:
                 auto_launch_browser = True
             elif shared.opts.auto_launch_browser == "Local":
-                auto_launch_browser = not cmd_opts.webui_is_non_local
+                auto_launch_browser = not any([cmd_opts.listen, cmd_opts.share, cmd_opts.ngrok, cmd_opts.server_name])
 
         app, local_url, share_url = shared.demo.launch(
             share=cmd_opts.share,

webui.sh

@@ -4,6 +4,12 @@
 # change the variables in webui-user.sh instead #
 #################################################
 
+
+use_venv=1
+if [[ $venv_dir == "-" ]]; then
+  use_venv=0
+fi
+
 SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
 
 
@@ -22,12 +28,6 @@ then
     source "$SCRIPT_DIR"/webui-user.sh
 fi
 
-# If $venv_dir is "-", then disable venv support
-use_venv=1
-if [[ $venv_dir == "-" ]]; then
-  use_venv=0
-fi
-
 # Set defaults
 # Install directory without trailing slash
 if [[ -z "${install_dir}" ]]
@@ -51,8 +51,6 @@ fi
 if [[ -z "${GIT}" ]]
 then
     export GIT="git"
-else
-    export GIT_PYTHON_GIT_EXECUTABLE="${GIT}"
 fi
 
 # python3 venv without trailing slash (defaults to ${install_dir}/${clone_dir}/venv)
@@ -143,8 +141,9 @@ case "$gpu_info" in
     *"Navi 2"*) export HSA_OVERRIDE_GFX_VERSION=10.3.0
     ;;
     *"Navi 3"*) [[ -z "${TORCH_COMMAND}" ]] && \
-         export TORCH_COMMAND="pip install torch torchvision --index-url https://download.pytorch.org/whl/test/rocm5.6"
-        # Navi 3 needs at least 5.5 which is only on the torch 2.1.0 release candidates right now
+         export TORCH_COMMAND="pip install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/rocm5.6"
+        # Navi 3 needs at least 5.5 which is only on the nightly chain, previous versions are no longer online (torch==2.1.0.dev-20230614+rocm5.5 torchvision==0.16.0.dev-20230614+rocm5.5 torchaudio==2.1.0.dev-20230614+rocm5.5)
+        # so switch to nightly rocm5.6 without explicit versions this time
     ;;
     *"Renoir"*) export HSA_OVERRIDE_GFX_VERSION=9.0.0
         printf "\n%s\n" "${delimiter}"