Merge branch 'dev' into move-start-timer

          --skip-prepare-environment

          --skip-torch-cuda-test

          --test-server

          --do-not-download-clip

          --no-half

          --disable-opt-split-attention

          --use-cpu all

 * SD XL support

 * user metadata system for custom networks

 * extended Lora metadata editor: set activation text, default weight, view tags, training info

 * Lora extension rework to include other types of networks (all that were previously handled by LyCORIS extension)

 * show github stars for extenstions

 * img2img batch mode can read extra stuff from png info

 * img2img batch works with subdirectories

 * restyle time taken/VRAM display

 * add textual inversion hashes to infotext

 * optimization: cache git extension repo information

 * move generate button next to the generated picture for mobile clients

 * hide cards for networks of incompatible Stable Diffusion version in Lora extra networks interface

 * skip installing packages with pip if they all are already installed - startup speedup of about 2 seconds

### Minor:

 * checkbox to check/uncheck all extensions in the Installed tab

 * speedup extra networks listing

 * added `[none]` filename token.

 * removed thumbs extra networks view mode (use settings tab to change width/height/scale to get thumbs)

 * add always_discard_next_to_last_sigma option to XYZ plot 

### Extensions and API:

 * api endpoints: /sdapi/v1/server-kill, /sdapi/v1/server-restart, /sdapi/v1/server-stop

 * fix: check fill size none zero when resize  (fixes #11425)

 * use submit and blur for quick settings textbox

 * save img2img batch with images.save_image()

 * 

 * prevent running preload.py for disabled extensions

## 1.4.1

            te_multiplier = float(params.positional[1]) if len(params.positional) > 1 else 1.0

            te_multiplier = float(params.named.get("te", te_multiplier))

            unet_multiplier = float(params.positional[2]) if len(params.positional) > 2 else 1.0

            unet_multiplier = float(params.positional[2]) if len(params.positional) > 2 else te_multiplier

            unet_multiplier = float(params.named.get("unet", unet_multiplier))

            dyn_dim = int(params.positional[3]) if len(params.positional) > 3 else None

import torch

from typing import Union

from modules import shared, devices, sd_models, errors, scripts, sd_hijack, paths

from modules import shared, devices, sd_models, errors, scripts, sd_hijack

module_types = [

    network_lora.ModuleTypeLora(),

    os.makedirs(shared.cmd_opts.lora_dir, exist_ok=True)

    candidates = list(shared.walk_files(shared.cmd_opts.lora_dir, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))

    candidates += list(shared.walk_files(os.path.join(paths.models_path, "LyCORIS"), allowed_extensions=[".pt", ".ckpt", ".safetensors"]))

    candidates += list(shared.walk_files(shared.cmd_opts.lyco_dir_backcompat, allowed_extensions=[".pt", ".ckpt", ".safetensors"]))

    for filename in candidates:

        if os.path.isdir(filename):

            continue

def preload(parser):

    parser.add_argument("--lora-dir", type=str, help="Path to directory with Lora networks.", default=os.path.join(paths.models_path, 'Lora'))

    parser.add_argument("--lyco-dir-backcompat", type=str, help="Path to directory with LyCORIS networks (for backawards compatibility; can also use --lyco-dir).", default=os.path.join(paths.models_path, 'LyCORIS'))