58 files changed, 708 insertions, 232 deletions

diff --git a/.eslintrc.js b/.eslintrc.js
index 4777c276..cf839769 100644
--- a/.eslintrc.js
+++ b/.eslintrc.js
@@ -74,6 +74,7 @@ module.exports = {
         create_submit_args: "readonly",
         restart_reload: "readonly",
         updateInput: "readonly",
+        onEdit: "readonly",
         //extraNetworks.js
         requestGet: "readonly",
         popup: "readonly",
diff --git a/configs/alt-diffusion-m18-inference.yaml b/configs/alt-diffusion-m18-inference.yaml
new file mode 100644
index 00000000..41a031d5
--- /dev/null
+++ b/configs/alt-diffusion-m18-inference.yaml
@@ -0,0 +1,73 @@
+model:
+  base_learning_rate: 1.0e-04
+  target: ldm.models.diffusion.ddpm.LatentDiffusion
+  params:
+    linear_start: 0.00085
+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
+    first_stage_key: "jpg"
+    cond_stage_key: "txt"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    use_ema: False
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 10000 ]
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 4
+        out_channels: 4
+        model_channels: 320
+        attention_resolutions: [ 4, 2, 1 ]
+        num_res_blocks: 2
+        channel_mult: [ 1, 2, 4, 4 ]
+        num_head_channels: 64
+        use_spatial_transformer: True
+        use_linear_in_transformer: True
+        transformer_depth: 1
+        context_dim: 1024
+        use_checkpoint: True
+        legacy: False
+
+    first_stage_config:
+      target: ldm.models.autoencoder.AutoencoderKL
+      params:
+        embed_dim: 4
+        monitor: val/rec_loss
+        ddconfig:
+          double_z: true
+          z_channels: 4
+          resolution: 256
+          in_channels: 3
+          out_ch: 3
+          ch: 128
+          ch_mult:
+          - 1
+          - 2
+          - 4
+          - 4
+          num_res_blocks: 2
+          attn_resolutions: []
+          dropout: 0.0
+        lossconfig:
+          target: torch.nn.Identity
+
+    cond_stage_config:
+      target: modules.xlmr_m18.BertSeriesModelWithTransformation
+      params:
+        name: "XLMR-Large"
diff --git a/extensions-builtin/Lora/network_glora.py b/extensions-builtin/Lora/network_glora.py
new file mode 100644
index 00000000..492d4870
--- /dev/null
+++ b/extensions-builtin/Lora/network_glora.py
@@ -0,0 +1,33 @@
+
+import network
+
+class ModuleTypeGLora(network.ModuleType):
+    def create_module(self, net: network.Network, weights: network.NetworkWeights):
+        if all(x in weights.w for x in ["a1.weight", "a2.weight", "alpha", "b1.weight", "b2.weight"]):
+            return NetworkModuleGLora(net, weights)
+
+        return None
+
+# adapted from https://github.com/KohakuBlueleaf/LyCORIS
+class NetworkModuleGLora(network.NetworkModule):
+    def __init__(self,  net: network.Network, weights: network.NetworkWeights):
+        super().__init__(net, weights)
+
+        if hasattr(self.sd_module, 'weight'):
+            self.shape = self.sd_module.weight.shape
+
+        self.w1a = weights.w["a1.weight"]
+        self.w1b = weights.w["b1.weight"]
+        self.w2a = weights.w["a2.weight"]
+        self.w2b = weights.w["b2.weight"]
+
+    def calc_updown(self, orig_weight):
+        w1a = self.w1a.to(orig_weight.device, dtype=orig_weight.dtype)
+        w1b = self.w1b.to(orig_weight.device, dtype=orig_weight.dtype)
+        w2a = self.w2a.to(orig_weight.device, dtype=orig_weight.dtype)
+        w2b = self.w2b.to(orig_weight.device, dtype=orig_weight.dtype)
+
+        output_shape = [w1a.size(0), w1b.size(1)]
+        updown = ((w2b @ w1b) + ((orig_weight @ w2a) @ w1a))
+
+        return self.finalize_updown(updown, orig_weight, output_shape)
diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py
index 96f935b2..ddab3c55 100644
--- a/extensions-builtin/Lora/networks.py
+++ b/extensions-builtin/Lora/networks.py
@@ -5,6 +5,7 @@ import re
 import lora_patches

 import network

 import network_lora

+import network_glora

 import network_hada

 import network_ia3

 import network_lokr

@@ -23,6 +24,7 @@ module_types = [
     network_lokr.ModuleTypeLokr(),

     network_full.ModuleTypeFull(),

     network_norm.ModuleTypeNorm(),

+    network_glora.ModuleTypeGLora(),

 ]

 

 

@@ -418,6 +420,7 @@ 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):

diff --git a/javascript/dragdrop.js b/javascript/dragdrop.js
index 5803daea..d680daf5 100644
--- a/javascript/dragdrop.js
+++ b/javascript/dragdrop.js
@@ -119,7 +119,7 @@ window.addEventListener('paste', e => {
     }
 
     const firstFreeImageField = visibleImageFields
-        .filter(el => el.querySelector('input[type=file]'))?.[0];
+        .filter(el => !el.querySelector('img'))?.[0];
 
     dropReplaceImage(
         firstFreeImageField ?
diff --git a/javascript/edit-attention.js b/javascript/edit-attention.js
index 8906c892..794453bf 100644
--- a/javascript/edit-attention.js
+++ b/javascript/edit-attention.js
@@ -18,22 +18,11 @@ 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);
@@ -46,9 +35,14 @@ function keyupEditAttention(event) {
 
     function selectCurrentWord() {
         if (selectionStart !== selectionEnd) return false;
-        const delimiters = opts.keyedit_delimiters + " \r\n\t";
+        const whitespace_delimiters = {"Tab": "\t", "Carriage Return": "\r", "Line Feed": "\n"};
+        let delimiters = opts.keyedit_delimiters;
+
+        for (let i of opts.keyedit_delimiters_whitespace) {
+            delimiters += whitespace_delimiters[i];
+        }
 
-        // seek backward until to find beggining
+        // seek backward to find beginning
         while (!delimiters.includes(text[selectionStart - 1]) && selectionStart > 0) {
             selectionStart--;
         }
@@ -92,7 +86,7 @@ function keyupEditAttention(event) {
     }
 
     var end = text.slice(selectionEnd + 1).indexOf(closeCharacter) + 1;
-    var weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + 1 + end));
+    var weight = parseFloat(text.slice(selectionEnd + 1, selectionEnd + end));
     if (isNaN(weight)) return;
 
     weight += isPlus ? delta : -delta;
diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js
index 493f31af..ac26718f 100644
--- a/javascript/extraNetworks.js
+++ b/javascript/extraNetworks.js
@@ -140,14 +140,15 @@ function setupExtraNetworks() {
 
 onUiLoaded(setupExtraNetworks);
 
-var re_extranet = /<([^:]+:[^:]+):[\d.]+>(.*)/;
-var re_extranet_g = /\s+<([^:]+:[^:]+):[\d.]+>/g;
+var re_extranet = /<([^:^>]+:[^:]+):[\d.]+>(.*)/;
+var re_extranet_g = /<([^:^>]+:[^:]+):[\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;
@@ -161,8 +162,13 @@ function tryToRemoveExtraNetworkFromPrompt(textarea, text) {
             return found;
         });
 
-        if (foundAtPosition >= 0 && newTextareaText.substr(foundAtPosition, extraTextAfterNet.length) == extraTextAfterNet) {
-            newTextareaText = newTextareaText.substr(0, foundAtPosition) + newTextareaText.substr(foundAtPosition + extraTextAfterNet.length);
+        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);
+            }
         }
     } else {
         newTextareaText = textarea.value.replaceAll(new RegExp(text, "g"), function(found) {
@@ -216,27 +222,24 @@ 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.onclick = closePopup;
+        close.addEventListener("click", 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);
 
@@ -335,7 +338,7 @@ 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('.card[data-name=' + JSON.stringify(name) + ']'); // likely using the wrong stringify function
+            var card = gradioApp().querySelector(`#${tabname}_${page.replace(" ", "_")}_cards > .card[data-name="${name}"]`);
 
             var newDiv = document.createElement('DIV');
             newDiv.innerHTML = data.html;
diff --git a/javascript/imageviewer.js b/javascript/imageviewer.js
index c21d396e..e4dae91b 100644
--- a/javascript/imageviewer.js
+++ b/javascript/imageviewer.js
@@ -33,8 +33,11 @@ function updateOnBackgroundChange() {
     const modalImage = gradioApp().getElementById("modalImage");
     if (modalImage && modalImage.offsetParent) {
         let currentButton = selected_gallery_button();
-
-        if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
+        let preview = gradioApp().querySelectorAll('.livePreview > img');
+        if (preview.length > 0) {
+            // show preview image if available
+            modalImage.src = preview[preview.length - 1].src;
+        } else if (currentButton?.children?.length > 0 && modalImage.src != currentButton.children[0].src) {
             modalImage.src = currentButton.children[0].src;
             if (modalImage.style.display === 'none') {
                 const modal = gradioApp().getElementById("lightboxModal");
diff --git a/javascript/settings.js b/javascript/settings.js
new file mode 100644
index 00000000..4e79ec00
--- /dev/null
+++ b/javascript/settings.js
@@ -0,0 +1,46 @@
+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);
+});
diff --git a/javascript/token-counters.js b/javascript/token-counters.js
index 9d81a723..2ecc7d91 100644
--- a/javascript/token-counters.js
+++ b/javascript/token-counters.js
@@ -1,10 +1,9 @@
-let promptTokenCountDebounceTime = 800;
-let promptTokenCountTimeouts = {};
-var promptTokenCountUpdateFunctions = {};
+let 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];
     }
@@ -14,6 +13,7 @@ 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];
     }
@@ -21,16 +21,7 @@ function update_img2img_tokens(...args) {
 }
 
 function update_token_counter(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,
-    );
+    promptTokenCountUpdateFunctions[button_id]?.();
 }
 
 
@@ -69,10 +60,11 @@ function setupTokenCounting(id, id_counter, id_button) {
     prompt.parentElement.insertBefore(counter, prompt);
     prompt.parentElement.style.position = "relative";
 
-    promptTokenCountUpdateFunctions[id] = function() {
-        update_token_counter(id_button);
-    };
-    textarea.addEventListener("input", promptTokenCountUpdateFunctions[id]);
+    var func = onEdit(id, textarea, 800, function() {
+        gradioApp().getElementById(id_button)?.click();
+    });
+    promptTokenCountUpdateFunctions[id] = func;
+    promptTokenCountUpdateFunctions[id_button] = func;
 }
 
 function setupTokenCounters() {
diff --git a/javascript/ui.js b/javascript/ui.js
index bedcbf3e..2e262602 100644
--- a/javascript/ui.js
+++ b/javascript/ui.js
@@ -263,21 +263,6 @@ 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() {
@@ -366,3 +351,20 @@ 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;
+}
diff --git a/modules/api/api.py b/modules/api/api.py
index 844e31ee..905ef9c9 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -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 Dict, List, Any
+from typing import 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 +242,8 @@ 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])
+        self.add_api_route("/sdapi/v1/extensions", self.get_extensions_list, methods=["GET"], response_model=list[models.ExtensionItem])
 
         if shared.cmd_opts.api_server_stop:
             self.add_api_route("/sdapi/v1/server-kill", self.kill_webui, methods=["POST"])
@@ -563,7 +563,7 @@ 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")
diff --git a/modules/api/models.py b/modules/api/models.py
index 94eca97d..a0d80af8 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -1,12 +1,10 @@
 import inspect
 
 from pydantic import BaseModel, Field, create_model
-from typing import Any, Optional
-from typing_extensions import Literal
+from typing import Any, Optional, 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",
@@ -130,12 +128,12 @@ 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
 
@@ -168,10 +166,10 @@ 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")
@@ -233,8 +231,8 @@ 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")
@@ -285,8 +283,8 @@ 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")
@@ -304,14 +302,14 @@ 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")
+    args: list[ScriptArg] = Field(title="Arguments", description="List of script's arguments")
 
 class ExtensionItem(BaseModel):
     name: str = Field(title="Name", description="Extension name")
diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index aab62286..4e602a84 100644
--- a/modules/cmd_args.py
+++ b/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="print prompts to console when generating with txt2img and img2img", 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('--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)")

@@ -112,8 +112,9 @@ 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='add /_stop route to stop server')

+parser.add_argument('--add-stop-route', action='store_true', help='does not do anything')

 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("--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", )

diff --git a/modules/config_states.py b/modules/config_states.py
index b766aef1..651793c7 100644
--- a/modules/config_states.py
+++ b/modules/config_states.py
@@ -4,7 +4,6 @@ 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
@@ -38,7 +37,7 @@ def list_config_states():
     config_states = sorted(config_states, key=lambda cs: cs["created_at"], reverse=True)
 
     for cs in config_states:
-        timestamp = time.asctime(time.gmtime(cs["created_at"]))
+        timestamp = datetime.fromtimestamp(cs["created_at"]).strftime('%Y-%m-%d %H:%M:%S')
         name = cs.get("name", "Config")
         full_name = f"{name}: {timestamp}"
         all_config_states[full_name] = cs
diff --git a/modules/devices.py b/modules/devices.py
index c01f0602..1d4eb563 100644
--- a/modules/devices.py
+++ b/modules/devices.py
@@ -60,7 +60,8 @@ 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
-        if any(torch.cuda.get_device_capability(devid) == (7, 5) for devid in range(0, torch.cuda.device_count())):
+        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"):
             torch.backends.cudnn.benchmark = True
 
         torch.backends.cuda.matmul.allow_tf32 = True
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py
index d39f2eba..0a606515 100644
--- a/modules/generation_parameters_copypaste.py
+++ b/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 ]+):\s*("(?:\\.|[^\\"])+"|[^,]*)(?:,|$)'

+re_param_code = r'\s*(\w[\w \-/]+):\s*("(?:\\.|[^\\"])+"|[^,]*)(?:,|$)'

 re_param = re.compile(re_param_code)

 re_imagesize = re.compile(r"^(\d+)x(\d+)$")

 re_hypernet_hash = re.compile("\(([0-9a-f]+)\)$")

diff --git a/modules/gitpython_hack.py b/modules/gitpython_hack.py
index e537c1df..b55f0640 100644
--- a/modules/gitpython_hack.py
+++ b/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).
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index 70f1cbd2..be3e4648 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/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, 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):

+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):

     from modules import images, processing

 

     save_hypernetwork_every = save_hypernetwork_every or 0

@@ -698,7 +698,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
                         p.prompt = preview_prompt

                         p.negative_prompt = preview_negative_prompt

                         p.steps = preview_steps

-                        p.sampler_name = sd_samplers.samplers[preview_sampler_index].name

+                        p.sampler_name = sd_samplers.samplers_map[preview_sampler_name.lower()]

                         p.cfg_scale = preview_cfg_scale

                         p.seed = preview_seed

                         p.width = preview_width

diff --git a/modules/images.py b/modules/images.py
index eb644733..daf4eebe 100644
--- a/modules/images.py
+++ b/modules/images.py
@@ -561,6 +561,8 @@ 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)

 

@@ -661,7 +663,13 @@ 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)

 

-        os.replace(temp_file_path, filename_without_extension + extension)

+        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)

 

     fullfn_without_extension, extension = os.path.splitext(params.filename)

     if hasattr(os, 'statvfs'):

@@ -718,7 +726,12 @@ def read_info_from_image(image: Image.Image) -> tuple[str | None, dict]:
     geninfo = items.pop('parameters', None)

 

     if "exif" in items:

-        exif = piexif.load(items["exif"])

+        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_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'')

         try:

             exif_comment = piexif.helper.UserComment.load(exif_comment)

@@ -728,6 +741,8 @@ 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)

diff --git a/modules/img2img.py b/modules/img2img.py
index c81c7ab9..52cb577a 100644
--- a/modules/img2img.py
+++ b/modules/img2img.py
@@ -114,15 +114,19 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
             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:

-            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}'

+            p.override_settings.pop('save_images_replace_action', None)

             process_images(p)

 

 

@@ -199,7 +203,7 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
 

     p.user = request.username

 

-    if shared.cmd_opts.enable_console_prompts:

+    if shared.opts.enable_console_prompts:

         print(f"\nimg2img: {prompt}", file=shared.progress_print_out)

 

     if mask:

diff --git a/modules/initialize.py b/modules/initialize.py
index f24f7637..ac95fc6f 100644
--- a/modules/initialize.py
+++ b/modules/initialize.py
@@ -151,8 +151,8 @@ def initialize_rest(*, reload_script_modules=False):
 

         from modules import devices

         devices.first_time_calculation()

-

-    Thread(target=load_model).start()

+    if not shared.cmd_opts.skip_load_model_at_start:

+        Thread(target=load_model).start()

 

     from modules import shared_items

     shared_items.reload_hypernetworks()

diff --git a/modules/launch_utils.py b/modules/launch_utils.py
index 6e54d063..8cdbafa5 100644
--- a/modules/launch_utils.py
+++ b/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, "rev-parse", "HEAD"], shell=False, encoding='utf8').strip()

+        return subprocess.check_output([git, "-C", script_path, "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, "describe", "--tags"], shell=False, encoding='utf8').strip()

+        return subprocess.check_output([git, "-C", script_path, "describe", "--tags"], shell=False, encoding='utf8').strip()

     except Exception:

         try:

 

diff --git a/modules/localization.py b/modules/localization.py
index c1320288..108f792e 100644
--- a/modules/localization.py
+++ b/modules/localization.py
@@ -14,21 +14,24 @@ 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)

-        localizations[fn] = file.path

+        if fn not in localizations:

+            localizations[fn] = []

+        localizations[fn].append(file.path)

 

 

 def localization_js(current_localization_name: str) -> str:

-    fn = localizations.get(current_localization_name, None)

+    fns = localizations.get(current_localization_name, None)

     data = {}

-    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)

+    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)

 

     return f"window.localization = {json.dumps(data)}"

diff --git a/modules/options.py b/modules/options.py
index 758b1ce5..ab40aff7 100644
--- a/modules/options.py
+++ b/modules/options.py
@@ -210,6 +210,8 @@ 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"""

diff --git a/modules/paths.py b/modules/paths.py
index 25052339..187b9496 100644
--- a/modules/paths.py
+++ b/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  # noqa: F401

+from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir, cwd  # noqa: F401

 

 import modules.safe  # noqa: F401

 

diff --git a/modules/paths_internal.py b/modules/paths_internal.py
index 005a9b0a..89131a54 100644
--- a/modules/paths_internal.py
+++ b/modules/paths_internal.py
@@ -8,6 +8,7 @@ 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)

 

diff --git a/modules/processing.py b/modules/processing.py
index e124e7f0..40598f5c 100644
--- a/modules/processing.py
+++ b/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 = 0

+    denoising_strength: float = None

     ddim_discretize: str = None

     s_min_uncond: float = None

     s_churn: float = None

@@ -533,6 +533,7 @@ 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 = {

@@ -567,6 +568,7 @@ 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)

@@ -709,7 +711,7 @@ 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()}

+    stored_opts = {k: opts.data[k] if k in opts.data else opts.get_default(k) for k in p.override_settings.keys() if k in opts.data}

 

     try:

         # if no checkpoint override or the override checkpoint can't be found, remove override entry and load opts checkpoint

@@ -958,6 +960,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 

             state.nextjob()

 

+        if not infotexts:

+            infotexts.append(Processed(p, []).infotext(p, 0))

+

         p.color_corrections = None

 

         index_of_first_image = 0

diff --git a/modules/processing_scripts/seed.py b/modules/processing_scripts/seed.py
index 6b6ff987..dc9c2da5 100644
--- a/modules/processing_scripts/seed.py
+++ b/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"), label='Random seed')

-            reuse_seed = ToolButton(ui.reuse_symbol, elem_id=self.elem_id("reuse_seed"), label='Reuse seed')

+            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")

 

             seed_checkbox = gr.Checkbox(label='Extra', elem_id=self.elem_id("subseed_show"), value=False)

 

diff --git a/modules/prompt_parser.py b/modules/prompt_parser.py
index 334efeef..ddf4d2dd 100644
--- a/modules/prompt_parser.py
+++ b/modules/prompt_parser.py
@@ -2,7 +2,6 @@ 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]"

@@ -240,14 +239,14 @@ 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:

@@ -278,7 +277,7 @@ 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)

 

diff --git a/modules/restart.py b/modules/restart.py
index 18eacaf3..2dd6493b 100644
--- a/modules/restart.py
+++ b/modules/restart.py
@@ -14,7 +14,9 @@ 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"""
 
-    (Path(script_path) / "tmp" / "restart").touch()
+    tmpdir = Path(script_path) / "tmp"
+    tmpdir.mkdir(parents=True, exist_ok=True)
+    (tmpdir / "restart").touch()
 
     stop_program()
 
diff --git a/modules/script_callbacks.py b/modules/script_callbacks.py
index c99695eb..9ed7ad21 100644
--- a/modules/script_callbacks.py
+++ b/modules/script_callbacks.py
@@ -1,7 +1,7 @@
 import inspect

 import os

 from collections import namedtuple

-from typing import Optional, Dict, Any

+from typing import Optional, 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)

 

diff --git a/modules/scripts.py b/modules/scripts.py
index e8518ad0..5c6e0226 100644
--- a/modules/scripts.py
+++ b/modules/scripts.py
@@ -491,11 +491,15 @@ class ScriptRunner:
 

             arg_info = api_models.ScriptArg(label=control.label or "")

 

-            for field in ("value", "minimum", "maximum", "step", "choices"):

+            for field in ("value", "minimum", "maximum", "step"):

                 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(

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 592f0055..bc5fbcd3 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -2,14 +2,15 @@ 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

+from modules import devices, sd_hijack_optimizations, shared, script_callbacks, errors, sd_unet, patches

 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

+from modules import sd_hijack_clip, sd_hijack_open_clip, sd_hijack_unet, sd_hijack_xlmr, xlmr, xlmr_m18

 

 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

@@ -37,6 +38,8 @@ 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()

@@ -208,7 +211,7 @@ class StableDiffusionModelHijack:
             else:

                 m.cond_stage_model = conditioner

 

-        if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation:

+        if type(m.cond_stage_model) == xlmr.BertSeriesModelWithTransformation or type(m.cond_stage_model) == xlmr_m18.BertSeriesModelWithTransformation:

             model_embeddings = m.cond_stage_model.roberta.embeddings

             model_embeddings.token_embedding = EmbeddingsWithFixes(model_embeddings.word_embeddings, self)

             m.cond_stage_model = sd_hijack_xlmr.FrozenXLMREmbedderWithCustomWords(m.cond_stage_model, self)

@@ -239,10 +242,13 @@ class StableDiffusionModelHijack:
 

         self.layers = flatten(m)

 

-        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

+        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

 

-        ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = sd_unet.UNetModel_forward

 

     def undo_hijack(self, m):

         conditioner = getattr(m, 'conditioner', None)

@@ -279,7 +285,8 @@ class StableDiffusionModelHijack:
         self.layers = None

         self.clip = None

 

-        ldm.modules.diffusionmodules.openaimodel.UNetModel.forward = ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui

+        sd_unet.original_forward = None

+

 

     def apply_circular(self, enable):

         if self.circular_enabled == enable:

diff --git a/modules/sd_models.py b/modules/sd_models.py
index 930d0bee..c8efeedc 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -7,16 +7,17 @@ import threading
 import torch

 import re

 import safetensors.torch

-from omegaconf import OmegaConf

+from omegaconf import OmegaConf, ListConfig

 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

+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.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))

@@ -49,11 +50,12 @@ 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 shared.cmd_opts.ckpt_dir is not None and abspath.startswith(shared.cmd_opts.ckpt_dir):

-            name = abspath.replace(shared.cmd_opts.ckpt_dir, '')

+        if abs_ckpt_dir and abspath.startswith(abs_ckpt_dir):

+            name = abspath.replace(abs_ckpt_dir, '')

         elif abspath.startswith(model_path):

             name = abspath.replace(model_path, '')

         else:

@@ -129,9 +131,12 @@ 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):

@@ -309,6 +314,8 @@ 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}")

@@ -350,12 +357,12 @@ def load_model_weights(model, checkpoint_info: CheckpointInfo, state_dict, timer
     if model.is_sdxl:

         sd_models_xl.extend_sdxl(model)

 

-    model.load_state_dict(state_dict, strict=False)

-    timer.record("apply weights to model")

-

     if shared.opts.sd_checkpoint_cache > 0:

         # cache newly loaded model

-        checkpoints_loaded[checkpoint_info] = state_dict

+        checkpoints_loaded[checkpoint_info] = state_dict.copy()

+

+    model.load_state_dict(state_dict, strict=False)

+    timer.record("apply weights to model")

 

     del state_dict

 

@@ -453,6 +460,20 @@ 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"):

diff --git a/modules/sd_models_config.py b/modules/sd_models_config.py
index 08dd03f1..deab2f6e 100644
--- a/modules/sd_models_config.py
+++ b/modules/sd_models_config.py
@@ -21,7 +21,7 @@ config_unopenclip = os.path.join(sd_repo_configs_path, "v2-1-stable-unclip-h-inf
 config_inpainting = os.path.join(sd_configs_path, "v1-inpainting-inference.yaml")

 config_instruct_pix2pix = os.path.join(sd_configs_path, "instruct-pix2pix.yaml")

 config_alt_diffusion = os.path.join(sd_configs_path, "alt-diffusion-inference.yaml")

-

+config_alt_diffusion_m18 = os.path.join(sd_configs_path, "alt-diffusion-m18-inference.yaml")

 

 def is_using_v_parameterization_for_sd2(state_dict):

     """

@@ -95,7 +95,10 @@ def guess_model_config_from_state_dict(sd, filename):
         if diffusion_model_input.shape[1] == 8:

             return config_instruct_pix2pix

 

+

     if sd.get('cond_stage_model.roberta.embeddings.word_embeddings.weight', None) is not None:

+        if sd.get('cond_stage_model.transformation.weight').size()[0] == 1024:

+            return config_alt_diffusion_m18

         return config_alt_diffusion

 

     return config_default

diff --git a/modules/sd_unet.py b/modules/sd_unet.py
index 5525cfbc..6a7bc9e2 100644
--- a/modules/sd_unet.py
+++ b/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 ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)

+    return original_forward(self, x, timesteps, context, *args, **kwargs)

 

diff --git a/modules/shared_items.py b/modules/shared_items.py
index 84d69c8d..b1459f8c 100644
--- a/modules/shared_items.py
+++ b/modules/shared_items.py
@@ -44,9 +44,9 @@ def refresh_unet_list():
     modules.sd_unet.list_unets()

 

 

-def list_checkpoint_tiles():

+def list_checkpoint_tiles(use_short=False):

     import modules.sd_models

-    return modules.sd_models.checkpoint_tiles()

+    return modules.sd_models.checkpoint_tiles(use_short)

 

 

 def refresh_checkpoints():

diff --git a/modules/shared_options.py b/modules/shared_options.py
index 00b273fa..ce395302 100644
--- a/modules/shared_options.py
+++ b/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"),

@@ -62,6 +62,8 @@ options_templates.update(options_section(('saving-images', "Saving images/grids"
     "clean_temp_dir_at_start": OptionInfo(False, "Cleanup non-default temporary directory when starting webui"),

 

     "save_incomplete_images": OptionInfo(False, "Save incomplete images").info("save images that has been interrupted in mid-generation; even if not saved, they will still show up in webui output."),

+

+    "notification_audio": OptionInfo(True, "Play notification sound after image generation").info("notification.mp3 should be present in the root directory").needs_reload_ui(),

 }))

 

 options_templates.update(options_section(('saving-paths', "Paths for saving"), {

@@ -100,6 +102,7 @@ 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"),

@@ -133,7 +136,7 @@ options_templates.update(options_section(('training', "Training"), {
 }))

 

 options_templates.update(options_section(('sd', "Stable Diffusion"), {

-    "sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext='Model hash'),

+    "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_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"),

@@ -255,12 +258,14 @@ 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(".,\\/!?%^*;:{}=`~()", "Ctrl+up/down word delimiters"),

+    "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_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(),

@@ -305,8 +310,8 @@ 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 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"),

+    '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"),

     '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"),

diff --git a/modules/shared_state.py b/modules/shared_state.py
index d272ee5b..a68789cc 100644
--- a/modules/shared_state.py
+++ b/modules/shared_state.py
@@ -103,6 +103,7 @@ 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

@@ -114,7 +115,6 @@ 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)

diff --git a/modules/sub_quadratic_attention.py b/modules/sub_quadratic_attention.py
index ae4ee4bb..4cb561ef 100644
--- a/modules/sub_quadratic_attention.py
+++ b/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, List
+from typing import Optional, NamedTuple
 
 
 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)))
diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index aa79dc09..401a0a2a 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/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_index, 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_name, 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[preview_sampler_index].name

+                        p.sampler_name = sd_samplers.samplers_map[preview_sampler_name.lower()]

                         p.cfg_scale = preview_cfg_scale

                         p.seed = preview_seed

                         p.width = preview_width

diff --git a/modules/txt2img.py b/modules/txt2img.py
index 1ee592ad..e4e18ceb 100644
--- a/modules/txt2img.py
+++ b/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, cmd_opts

+from modules.shared import 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 cmd_opts.enable_console_prompts:

+    if shared.opts.enable_console_prompts:

         print(f"\ntxt2img: {prompt}", file=shared.progress_print_out)

 

     with closing(p):

diff --git a/modules/ui.py b/modules/ui.py
index f4028475..bcf39199 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -151,11 +151,15 @@ def connect_clear_prompt(button):
     )

 

 

-def update_token_counter(text, steps):

+def update_token_counter(text, steps, *, is_positive=True):

     try:

         text, _ = extra_networks.parse_prompt(text)

 

-        _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])

+        if is_positive:

+            _, prompt_flat_list, _ = prompt_parser.get_multicond_prompt_list([text])

+        else:

+            prompt_flat_list = [text]

+

         prompt_schedules = prompt_parser.get_learned_conditioning_prompt_schedules(prompt_flat_list, steps)

 

     except Exception:

@@ -169,6 +173,10 @@ def update_token_counter(text, steps):
     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"""

 

@@ -215,9 +223,10 @@ class Toprow:
                     )

 

                 with gr.Row(elem_id=f"{id_part}_tools"):

-                    self.paste = ToolButton(value=paste_symbol, elem_id="paste")

-                    self.clear_prompt_button = ToolButton(value=clear_prompt_symbol, elem_id=f"{id_part}_clear_prompt")

-                    self.restore_progress_button = ToolButton(value=restore_progress_symbol, elem_id=f"{id_part}_restore_progress", visible=False)

+                    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.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")

@@ -232,6 +241,7 @@ 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,

@@ -348,7 +358,7 @@ 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", label="Switch dims")

+                                res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="txt2img_res_switch_btn", tooltip="Switch width/height")

 

                             if opts.dimensions_and_batch_together:

                                 with gr.Column(elem_id="txt2img_column_batch"):

@@ -533,7 +543,7 @@ 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_token_counter), inputs=[toprow.negative_prompt, steps], outputs=[toprow.negative_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])

 

         extra_networks_ui = ui_extra_networks.create_ui(txt2img_interface, [txt2img_generation_tab], 'txt2img')

         ui_extra_networks.setup_ui(extra_networks_ui, txt2img_gallery)

@@ -661,8 +671,8 @@ 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")

-                                                detect_image_size_btn = ToolButton(value=detect_image_size_symbol, elem_id="img2img_detect_image_size_btn")

+                                                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")

 

                                     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")

@@ -1286,7 +1296,7 @@ def create_ui():
 

             loadsave.setup_ui()

 

-        if os.path.exists(os.path.join(script_path, "notification.mp3")):

+        if os.path.exists(os.path.join(script_path, "notification.mp3")) and shared.opts.notification_audio:

             gr.Audio(interactive=False, value=os.path.join(script_path, "notification.mp3"), elem_id="audio_notification", visible=False)

 

         footer = shared.html("footer.html")

@@ -1338,7 +1348,6 @@ 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")

@@ -1347,7 +1356,7 @@ 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"])

 

diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index 2e8c1d6d..c0a73b57 100644
--- a/modules/ui_extensions.py
+++ b/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 = time.asctime(time.gmtime(config_state["created_at"]))

+    created_date = datetime.fromtimestamp(config_state["created_at"]).strftime('%Y-%m-%d %H:%M:%S')

     filepath = config_state.get("filepath", "<unknown>")

 

     try:

diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py
index 063bd7b8..59d6ecc6 100644
--- a/modules/ui_extra_networks.py
+++ b/modules/ui_extra_networks.py
@@ -1,3 +1,4 @@
+import functools

 import os.path

 import urllib.parse

 from pathlib import Path

@@ -15,6 +16,17 @@ 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"""

@@ -33,9 +45,9 @@ 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()

-    if ext not in (".png", ".jpg", ".jpeg", ".webp", ".gif"):

-        raise ValueError(f"File cannot be fetched: {filename}. Only png, jpg, webp, and gif.")

+    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()}.")

 

     # would profit from returning 304

     return FileResponse(filename, headers={"Accept-Ranges": "bytes"})

@@ -213,9 +225,9 @@ 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(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(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>"

+        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>"

 

         local_path = ""

         filename = item.get("filename", "")

@@ -235,7 +247,7 @@ class ExtraNetworksPage:
         if search_only and shared.opts.extra_networks_hidden_models == "Never":

             return ""

 

-        sort_keys = " ".join([html.escape(f'data-sort-{k}={v}') for k, v in item.get("sort_keys", {}).items()]).strip()

+        sort_keys = " ".join([f'data-sort-{k}="{html.escape(str(v))}"' for k, v in item.get("sort_keys", {}).items()]).strip()

 

         args = {

             "background_image": background_image,

@@ -273,11 +285,7 @@ class ExtraNetworksPage:
         Find a preview PNG for a given path (without extension) and call link_preview on it.

         """

 

-        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], [])

+        potential_files = sum([[path + "." + ext, path + ".preview." + ext] for ext in allowed_preview_extensions()], [])

 

         for file in potential_files:

             if os.path.isfile(file):

@@ -374,7 +382,7 @@ 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)

+    button_sortorder = ToolButton(switch_values_symbol, elem_id=tabname+"_extra_sortorder", elem_classes="sortorder", visible=False, tooltip="Invert sort order")

     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)

 

diff --git a/modules/ui_gradio_extensions.py b/modules/ui_gradio_extensions.py
index b824b113..0d368f8b 100644
--- a/modules/ui_gradio_extensions.py
+++ b/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

+from modules.paths import script_path, data_path, cwd

 

 

 def webpath(fn):

-    if fn.startswith(script_path):

-        web_path = os.path.relpath(fn, script_path).replace('\\', '/')

+    if fn.startswith(cwd):

+        web_path = os.path.relpath(fn, cwd)

     else:

         web_path = os.path.abspath(fn)

 

diff --git a/modules/ui_loadsave.py b/modules/ui_loadsave.py
index ec8fa8e8..eb20ff25 100644
--- a/modules/ui_loadsave.py
+++ b/modules/ui_loadsave.py
@@ -4,7 +4,7 @@ import os
 import gradio as gr

 

 from modules import errors

-from modules.ui_components import ToolButton

+from modules.ui_components import ToolButton, InputAccordion

 

 

 def radio_choices(comp):  # gradio 3.41 changes choices from list of values to list of pairs

@@ -32,8 +32,6 @@ 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"""

 

@@ -43,20 +41,24 @@ 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(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

+                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

                     saved_value = str(saved_value)

-                elif isinstance(x, gr.Number) and field == 'value':

+                elif isinstance(obj, gr.Number) and field == 'value':

                     try:

                         saved_value = float(saved_value)

                     except ValueError:

@@ -67,7 +69,7 @@ class UiLoadsave:
                     init_field(saved_value)

 

             if field == 'value' and key not in self.component_mapping:

-                self.component_mapping[key] = x

+                self.component_mapping[key] = obj

 

         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')

@@ -100,6 +102,12 @@ 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:

diff --git a/modules/ui_prompt_styles.py b/modules/ui_prompt_styles.py
index 85eb3a64..3bcf092f 100644
--- a/modules/ui_prompt_styles.py
+++ b/modules/ui_prompt_styles.py
@@ -4,6 +4,7 @@ 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):

@@ -52,6 +53,8 @@ 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")

@@ -61,7 +64,8 @@ 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", tooltip="Apply all selected styles from the style selction dropdown in main UI to the prompt.")

+                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.")

 

             with gr.Row():

                 self.prompt = gr.Textbox(label="Prompt", show_label=True, elem_id=f"{tabname}_edit_style_prompt", lines=3)

@@ -96,15 +100,21 @@ class UiPromptStyles:
             show_progress=False,

         ).then(refresh_styles, outputs=[self.dropdown, self.selection], show_progress=False)

 

-        self.materialize.click(

-            fn=materialize_styles,

-            inputs=[main_ui_prompt, main_ui_negative_prompt, self.dropdown],

-            outputs=[main_ui_prompt, main_ui_negative_prompt, self.dropdown],

+        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],

             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)

diff --git a/modules/ui_settings.py b/modules/ui_settings.py
index 8ff9c074..74a3aef3 100644
--- a/modules/ui_settings.py
+++ b/modules/ui_settings.py
@@ -5,6 +5,7 @@ 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):

@@ -63,6 +64,9 @@ 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 = []

@@ -135,7 +139,7 @@ class UiSettings:
                         gr.Group()

                         current_tab = gr.TabItem(elem_id=f"settings_{elem_id}", label=text)

                         current_tab.__enter__()

-                        current_row = gr.Column(variant='compact')

+                        current_row = gr.Column(elem_id=f"column_settings_{elem_id}", variant='compact')

                         current_row.__enter__()

 

                         previous_section = item.section

@@ -175,11 +179,18 @@ 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")

 

-                gr.Button(value="Show all pages", elem_id="settings_show_all_pages")

+                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)

 

                 self.text_settings = gr.Textbox(elem_id="settings_json", value=lambda: opts.dumpjson(), visible=False)

 

@@ -241,6 +252,21 @@ 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):

@@ -294,3 +320,8 @@ 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]

diff --git a/modules/xlmr_m18.py b/modules/xlmr_m18.py
new file mode 100644
index 00000000..a727e865
--- /dev/null
+++ b/modules/xlmr_m18.py
@@ -0,0 +1,164 @@
+from transformers import BertPreTrainedModel,BertConfig
+import torch.nn as nn
+import torch
+from transformers.models.xlm_roberta.configuration_xlm_roberta import XLMRobertaConfig
+from transformers import XLMRobertaModel,XLMRobertaTokenizer
+from typing import Optional
+
+class BertSeriesConfig(BertConfig):
+    def __init__(self, vocab_size=30522, hidden_size=768, num_hidden_layers=12, num_attention_heads=12, intermediate_size=3072, hidden_act="gelu", hidden_dropout_prob=0.1, attention_probs_dropout_prob=0.1, max_position_embeddings=512, type_vocab_size=2, initializer_range=0.02, layer_norm_eps=1e-12, pad_token_id=0, position_embedding_type="absolute", use_cache=True, classifier_dropout=None,project_dim=512, pooler_fn="average",learn_encoder=False,model_type='bert',**kwargs):
+
+        super().__init__(vocab_size, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, type_vocab_size, initializer_range, layer_norm_eps, pad_token_id, position_embedding_type, use_cache, classifier_dropout, **kwargs)
+        self.project_dim = project_dim
+        self.pooler_fn = pooler_fn
+        self.learn_encoder = learn_encoder
+
+class RobertaSeriesConfig(XLMRobertaConfig):
+    def __init__(self, pad_token_id=1, bos_token_id=0, eos_token_id=2,project_dim=512,pooler_fn='cls',learn_encoder=False, **kwargs):
+        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
+        self.project_dim = project_dim
+        self.pooler_fn = pooler_fn
+        self.learn_encoder = learn_encoder
+
+
+class BertSeriesModelWithTransformation(BertPreTrainedModel):
+
+    _keys_to_ignore_on_load_unexpected = [r"pooler"]
+    _keys_to_ignore_on_load_missing = [r"position_ids", r"predictions.decoder.bias"]
+    config_class = BertSeriesConfig
+
+    def __init__(self, config=None, **kargs):
+        # modify initialization for autoloading
+        if config is None:
+            config = XLMRobertaConfig()
+            config.attention_probs_dropout_prob= 0.1
+            config.bos_token_id=0
+            config.eos_token_id=2
+            config.hidden_act='gelu'
+            config.hidden_dropout_prob=0.1
+            config.hidden_size=1024
+            config.initializer_range=0.02
+            config.intermediate_size=4096
+            config.layer_norm_eps=1e-05
+            config.max_position_embeddings=514
+
+            config.num_attention_heads=16
+            config.num_hidden_layers=24
+            config.output_past=True
+            config.pad_token_id=1
+            config.position_embedding_type= "absolute"
+
+            config.type_vocab_size= 1
+            config.use_cache=True
+            config.vocab_size= 250002
+            config.project_dim = 1024
+            config.learn_encoder = False
+        super().__init__(config)
+        self.roberta = XLMRobertaModel(config)
+        self.transformation = nn.Linear(config.hidden_size,config.project_dim)
+        # self.pre_LN=nn.LayerNorm(config.hidden_size, eps=config.layer_norm_eps)
+        self.tokenizer = XLMRobertaTokenizer.from_pretrained('xlm-roberta-large')
+        # self.pooler = lambda x: x[:,0]
+        # self.post_init()
+
+        self.has_pre_transformation = True
+        if self.has_pre_transformation:
+            self.transformation_pre = nn.Linear(config.hidden_size, config.project_dim)
+            self.pre_LN = nn.LayerNorm(config.hidden_size, eps=config.layer_norm_eps)
+        self.post_init()
+
+    def encode(self,c):
+        device = next(self.parameters()).device
+        text = self.tokenizer(c,
+                        truncation=True,
+                        max_length=77,
+                        return_length=False,
+                        return_overflowing_tokens=False,
+                        padding="max_length",
+                        return_tensors="pt")
+        text["input_ids"] = torch.tensor(text["input_ids"]).to(device)
+        text["attention_mask"] = torch.tensor(
+            text['attention_mask']).to(device)
+        features = self(**text)
+        return features['projection_state']
+
+    def forward(
+        self,
+        input_ids: Optional[torch.Tensor] = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        token_type_ids: Optional[torch.Tensor] = None,
+        position_ids: Optional[torch.Tensor] = None,
+        head_mask: Optional[torch.Tensor] = None,
+        inputs_embeds: Optional[torch.Tensor] = None,
+        encoder_hidden_states: Optional[torch.Tensor] = None,
+        encoder_attention_mask: Optional[torch.Tensor] = None,
+        output_attentions: Optional[bool] = None,
+        return_dict: Optional[bool] = None,
+        output_hidden_states: Optional[bool] = None,
+    ) :
+        r"""
+        """
+
+        return_dict = return_dict if return_dict is not None else self.config.use_return_dict
+
+
+        outputs = self.roberta(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            token_type_ids=token_type_ids,
+            position_ids=position_ids,
+            head_mask=head_mask,
+            inputs_embeds=inputs_embeds,
+            encoder_hidden_states=encoder_hidden_states,
+            encoder_attention_mask=encoder_attention_mask,
+            output_attentions=output_attentions,
+            output_hidden_states=True,
+            return_dict=return_dict,
+        )
+
+        # # last module outputs
+        # sequence_output = outputs[0]
+
+
+        # # project every module
+        # sequence_output_ln = self.pre_LN(sequence_output)
+
+        # # pooler
+        # pooler_output = self.pooler(sequence_output_ln)
+        # pooler_output = self.transformation(pooler_output)
+        # projection_state = self.transformation(outputs.last_hidden_state)
+
+        if self.has_pre_transformation:
+            sequence_output2 = outputs["hidden_states"][-2]
+            sequence_output2 = self.pre_LN(sequence_output2)
+            projection_state2 = self.transformation_pre(sequence_output2)
+
+            return {
+                "projection_state": projection_state2,
+                "last_hidden_state": outputs.last_hidden_state,
+                "hidden_states": outputs.hidden_states,
+                "attentions": outputs.attentions,
+            }
+        else:
+            projection_state = self.transformation(outputs.last_hidden_state)
+            return {
+                "projection_state": projection_state,
+                "last_hidden_state": outputs.last_hidden_state,
+                "hidden_states": outputs.hidden_states,
+                "attentions": outputs.attentions,
+            }
+
+
+        # return {
+        #     'pooler_output':pooler_output,
+        #     'last_hidden_state':outputs.last_hidden_state,
+        #     'hidden_states':outputs.hidden_states,
+        #     'attentions':outputs.attentions,
+        #     'projection_state':projection_state,
+        #     'sequence_out': sequence_output
+        # }
+
+
+class RobertaSeriesModelWithTransformation(BertSeriesModelWithTransformation):
+    base_model_prefix = 'roberta'
+    config_class= RobertaSeriesConfig
diff --git a/requirements_versions.txt b/requirements_versions.txt
index f8ae1f38..7d27f2be 100644
--- a/requirements_versions.txt
+++ b/requirements_versions.txt
@@ -27,5 +27,5 @@ timm==0.9.2
 tomesd==0.1.3

 torch

 torchdiffeq==0.2.3

-torchsde==0.2.5

+torchsde==0.2.6

 transformers==4.30.2

diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py
index edb70ac0..eb42a29e 100644
--- a/scripts/postprocessing_upscale.py
+++ b/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")

+                                upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn", tooltip="Switch width/height")

                                 upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")

 

             with FormRow():

diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py
index 50320d55..ca73b2a5 100644
--- a/scripts/prompts_from_file.py
+++ b/scripts/prompts_from_file.py
@@ -5,11 +5,17 @@ import shlex
 import modules.scripts as scripts

 import gradio as gr

 

-from modules import sd_samplers, errors

+from modules import sd_samplers, errors, sd_models

 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

 

@@ -27,7 +33,7 @@ def process_boolean_tag(tag):
 

 

 prompt_tags = {

-    "sd_model": None,

+    "sd_model": process_model_tag,

     "outpath_samples": process_string_tag,

     "outpath_grids": process_string_tag,

     "prompt_for_display": process_string_tag,

@@ -156,7 +162,10 @@ class Script(scripts.Script):
 

             copy_p = copy.copy(p)

             for k, v in args.items():

-                setattr(copy_p, k, v)

+                if k == "sd_model":

+                    copy_p.override_settings['sd_model_checkpoint'] = v

+                else:

+                    setattr(copy_p, k, v)

 

             proc = process_images(copy_p)

             images += proc.images

diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py
index 939d8605..0dc255bc 100644
--- a/scripts/xyz_grid.py
+++ b/scripts/xyz_grid.py
@@ -205,13 +205,14 @@ 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):

+    def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None, prepare=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

 

 

@@ -536,6 +537,8 @@ 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)

 

@@ -773,6 +776,8 @@ 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:

diff --git a/style.css b/style.css
index fb4e2f1f..115626cd 100644
--- a/style.css
+++ b/style.css
@@ -83,8 +83,10 @@ div.compact{
     white-space: nowrap;

 }

 

-.gradio-dropdown ul.options li.item {

-    padding: 0.05em 0;

+@media (pointer:fine) {

+    .gradio-dropdown ul.options li.item {

+        padding: 0.05em 0;

+    }

 }

 

 .gradio-dropdown ul.options li.item.selected {

@@ -421,6 +423,7 @@ div#extras_scale_to_tab div.form{
 #settings > div{

     border: none;

     margin-left: 10em;

+    padding: 0 var(--spacing-xl);

 }

 

 #settings > div.tab-nav{

@@ -435,6 +438,7 @@ div#extras_scale_to_tab div.form{
     border: none;

     text-align: left;

     white-space: initial;

+    padding: 4px;

 }

 

 #settings_result{

@@ -581,7 +585,6 @@ table.popup-table .link{
     width: 100%;

     height: 100%;

     overflow: auto;

-    background-color: rgba(20, 20, 20, 0.95);

 }

 

 .global-popup *{

@@ -590,9 +593,6 @@ table.popup-table .link{
 

 .global-popup-close:before {

     content: "×";

-}

-

-.global-popup-close{

     position: fixed;

     right: 0.25em;

     top: 0;

@@ -601,10 +601,20 @@ 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 */

diff --git a/webui.bat b/webui.bat
index 42e7d517..a630ea4d 100644
--- a/webui.bat
+++ b/webui.bat
@@ -1,6 +1,7 @@
 @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

diff --git a/webui.sh b/webui.sh
index 3d0f87ee..08911469 100755
--- a/webui.sh
+++ b/webui.sh
@@ -4,12 +4,6 @@
 # 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 )
 
 
@@ -28,6 +22,12 @@ 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}" ]]
@@ -51,6 +51,8 @@ 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)
@@ -141,9 +143,8 @@ case "$gpu_info" in
     *"Navi 2"*) export HSA_OVERRIDE_GFX_VERSION=10.3.0
     ;;
     *"Navi 3"*) [[ -z "${TORCH_COMMAND}" ]] && \
-         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
+         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
     ;;
     *"Renoir"*) export HSA_OVERRIDE_GFX_VERSION=9.0.0
         printf "\n%s\n" "${delimiter}"