Merge branch 'master' into master

- Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6)

- Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6)

- Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix

- Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix

- Security advice - RyotaK

- Security advice - RyotaK

- UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC

- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.

- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.

- (You)

- (You)

import re

import re

import torch

import torch

from modules import shared, devices, sd_models

from modules import shared, devices, sd_models, errors

metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20}

re_digits = re.compile(r"\d+")

re_digits = re.compile(r"\d+")

re_unet_down_blocks = re.compile(r"lora_unet_down_blocks_(\d+)_attentions_(\d+)_(.+)")

re_unet_down_blocks = re.compile(r"lora_unet_down_blocks_(\d+)_attentions_(\d+)_(.+)")

    def __init__(self, name, filename):

    def __init__(self, name, filename):

        self.name = name

        self.name = name

        self.filename = filename

        self.filename = filename

        self.metadata = {}

        _, ext = os.path.splitext(filename)

        if ext.lower() == ".safetensors":

            try:

                self.metadata = sd_models.read_metadata_from_safetensors(filename)

            except Exception as e:

                errors.display(e, f"reading lora {filename}")

        if self.metadata:

            m = {}

            for k, v in sorted(self.metadata.items(), key=lambda x: metadata_tags_order.get(x[0], 999)):

                m[k] = v

            self.metadata = m

        self.ssmd_cover_images = self.metadata.pop('ssmd_cover_images', None)  # those are cover images and they are too big to display in UI as text

class LoraModule:

class LoraModule:

def lora_forward(module, input, res):

def lora_forward(module, input, res):

    input = devices.cond_cast_unet(input)

    if len(loaded_loras) == 0:

    if len(loaded_loras) == 0:

        return res

        return res

    def list_items(self):

    def list_items(self):

        for name, lora_on_disk in lora.available_loras.items():

        for name, lora_on_disk in lora.available_loras.items():

            path, ext = os.path.splitext(lora_on_disk.filename)

            path, ext = os.path.splitext(lora_on_disk.filename)

            previews = [path + ".png", path + ".preview.png"]

            preview = None

            for file in previews:

                if os.path.isfile(file):

                    preview = self.link_preview(file)

                    break

            yield {

            yield {

                "name": name,

                "name": name,

                "filename": path,

                "filename": path,

                "preview": preview,

                "preview": self.find_preview(path),

                "description": self.find_description(path),

                "search_term": self.search_terms_from_path(lora_on_disk.filename),

                "search_term": self.search_terms_from_path(lora_on_disk.filename),

                "prompt": json.dumps(f"<lora:{name}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),

                "prompt": json.dumps(f"<lora:{name}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),

                "local_preview": path + ".png",

                "local_preview": f"{path}.{shared.opts.samples_format}",

                "metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None,

            }

            }

    def allowed_directories_for_previews(self):

    def allowed_directories_for_previews(self):

function setupBracketChecking(id_prompt, id_counter){

function setupBracketChecking(id_prompt, id_counter){

    var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");

    var textarea = gradioApp().querySelector("#" + id_prompt + " > label > textarea");

    var counter = gradioApp().getElementById(id_counter)

    var counter = gradioApp().getElementById(id_counter)

    textarea.addEventListener("input", function(evt){

    textarea.addEventListener("input", function(evt){

        checkBrackets(evt, textarea, counter)

        checkBrackets(evt, textarea, counter)

    });

    });

}

}

var shadowRootLoaded = setInterval(function() {

onUiLoaded(function(){

    var shadowRoot = document.querySelector('gradio-app').shadowRoot;

    if(! shadowRoot)  return false;

    var shadowTextArea = shadowRoot.querySelectorAll('#txt2img_prompt > label > textarea');

    if(shadowTextArea.length < 1)  return false;

    clearInterval(shadowRootLoaded);

    setupBracketChecking('txt2img_prompt', 'txt2img_token_counter')

    setupBracketChecking('txt2img_prompt', 'txt2img_token_counter')

    setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter')

    setupBracketChecking('txt2img_neg_prompt', 'txt2img_negative_token_counter')

    setupBracketChecking('img2img_prompt', 'imgimg_token_counter')

    setupBracketChecking('img2img_prompt', 'img2img_token_counter')

    setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter')

    setupBracketChecking('img2img_neg_prompt', 'img2img_negative_token_counter')

}, 1000);

})

 No newline at end of file

			<span style="display:none" class='search_term'>{search_term}</span>

			<span style="display:none" class='search_term'>{search_term}</span>

		</div>

		</div>

		<span class='name'>{name}</span>

		<span class='name'>{name}</span>

		<span class='description'>{description}</span>

	</div>

	</div>

</div>

</div>