Merge branch 'AUTOMATIC1111:master' into fix/alternating-words-emphasis

                    e.addEventListener('mousedown', function (evt) {

                        if(!opts.js_modal_lightbox || evt.button != 0) return;

                        modalZoomSet(gradioApp().getElementById('modalImage'), opts.js_modal_lightbox_initially_zoomed)

                        evt.preventDefault()

                        showModal(evt)

                    }, true);

                }

import os

import sys

import traceback

import shutil

import numpy as np

from PIL import Image

    return '', geninfo, info

def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):

def create_config(ckpt_result, config_source, a, b, c):

    def config(x):

        return sd_models.find_checkpoint_config(x) if x else None

    if config_source == 0:

        cfg = config(a) or config(b) or config(c)

    elif config_source == 1:

        cfg = config(b)

    elif config_source == 2:

        cfg = config(c)

    else:

        cfg = None

    if cfg is None:

        return

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

    checkpoint_filename = filename + ".yaml"

    print("Copying config:")

    print("   from:", cfg)

    print("     to:", checkpoint_filename)

    shutil.copyfile(cfg, checkpoint_filename)

def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format, config_source):

    shared.state.begin()

    shared.state.job = 'model-merge'

    sd_models.list_models()

    create_config(output_modelname, config_source, primary_model_info, secondary_model_info, tertiary_model_info)

    print("Checkpoint saved.")

    shared.state.textinfo = "Checkpoint saved to " + output_modelname

    shared.state.end()

scripts_data = []

ScriptFile = namedtuple("ScriptFile", ["basedir", "filename", "path"])

ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir"])

ScriptClassData = namedtuple("ScriptClassData", ["script_class", "path", "basedir", "module"])

def list_scripts(scriptdirname, extension):

            for key, script_class in module.__dict__.items():

                if type(script_class) == type and issubclass(script_class, Script):

                    scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir))

                    scripts_data.append(ScriptClassData(script_class, scriptfile.path, scriptfile.basedir, module))

        except Exception:

            print(f"Error loading script: {scriptfile.filename}", file=sys.stderr)

        self.alwayson_scripts.clear()

        self.selectable_scripts.clear()

        for script_class, path, basedir in scripts_data:

        for script_class, path, basedir, script_module in scripts_data:

            script = script_class()

            script.filename = path

            script.is_txt2img = not is_img2img

    timer = Timer()

    sd_model = None

    try:

        with sd_disable_initialization.DisableInitialization():

            sd_model = instantiate_from_config(sd_config.model)

    except Exception as e:

        pass

    if sd_model is None:

        print('Failed to create model quickly; will retry using slow method.', file=sys.stderr)

        sd_model = instantiate_from_config(sd_config.model)

import html

import datetime

import csv

import safetensors.torch

from PIL import Image, PngImagePlugin

                name = data.get('name', name)

        elif ext in ['.BIN', '.PT']:

            data = torch.load(path, map_location="cpu")

        elif ext in ['.SAFETENSORS']:

            data = safetensors.torch.load_file(path, device="cpu")

        else:

            return