SYMBOL INDEX (9937 symbols across 1009 files)

FILE: cli/api-checkpoint.py
  function auth (line 21) | def auth():
  function get (line 27) | def get(endpoint: str, dct: dict = None):

FILE: cli/api-control.py
  function auth (line 27) | def auth():
  function post (line 33) | def post(endpoint: str, dct: dict = None):
  function encode (line 41) | def encode(f):
  function generate (line 53) | def generate(args): # pylint: disable=redefined-outer-name

FILE: cli/api-detect.py
  function auth (line 20) | def auth():
  function post (line 26) | def post(endpoint: str, dct: dict = None):
  function encode (line 34) | def encode(f):
  function detect (line 46) | def detect(args): # pylint: disable=redefined-outer-name

FILE: cli/api-enhance.py
  function auth (line 21) | def auth():
  function post (line 27) | def post(endpoint: str, dct: dict = None):
  function encode (line 35) | def encode(f):
  function enhance (line 51) | def enhance(args): # pylint: disable=redefined-outer-name

FILE: cli/api-faceid.py
  function auth (line 26) | def auth():
  function post (line 32) | def post(endpoint: str, dct: dict = None):
  function encode (line 40) | def encode(f):
  function generate (line 52) | def generate(args): # pylint: disable=redefined-outer-name

FILE: cli/api-grid.py
  class Options (line 16) | class Options: # set default parameters here
  class Server (line 30) | class Server: # set server and save options here or use command line arg...
  function post (line 49) | def post():
  function generate (line 61) | def generate(x: int, y: int): # pylint: disable=redefined-outer-name
  function merge (line 82) | def merge(images: list[Image.Image], horizontal: bool, labels: list[str]...
  function grid (line 102) | def grid(x_file: str, y_file: str):

FILE: cli/api-img2img.py
  function auth (line 26) | def auth():
  function post (line 32) | def post(endpoint: str, dct: dict = None):
  function encode (line 40) | def encode(f):
  function generate (line 52) | def generate(args): # pylint: disable=redefined-outer-name

FILE: cli/api-info.py
  function auth (line 21) | def auth():
  function get (line 27) | def get(endpoint: str, dct: dict = None):
  function post (line 35) | def post(endpoint: str, dct: dict = None):
  function info (line 43) | def info(args): # pylint: disable=redefined-outer-name

FILE: cli/api-interrogate.py
  function decode (line 21) | def decode(encoding):
  function encode (line 27) | def encode(f):
  function print_summary (line 39) | def print_summary():
  function interrogate (line 46) | async def interrogate(f):
  function main (line 87) | async def main():

FILE: cli/api-json.py
  function auth (line 25) | def auth():
  function post (line 31) | def post(endpoint: str, payload: dict = None):

FILE: cli/api-mask.py
  function auth (line 23) | def auth():
  function get (line 29) | def get(endpoint: str, dct: dict = None):
  function post (line 37) | def post(endpoint: str, dct: dict = None):
  function info (line 45) | def info(args): # pylint: disable=redefined-outer-name

FILE: cli/api-model.js
  function options (line 12) | async function options(data) {
  function main (line 22) | async function main() {

FILE: cli/api-preprocess.py
  function auth (line 23) | def auth():
  function get (line 29) | def get(endpoint: str, dct: dict = None):
  function post (line 37) | def post(endpoint: str, dct: dict = None):
  function info (line 45) | def info(args): # pylint: disable=redefined-outer-name

FILE: cli/api-progress.py
  class Dot (line 14) | class Dot(dict):
  function progress (line 34) | def progress():

FILE: cli/api-pulid.js
  function b64 (line 15) | function b64(file) {
  function options (line 24) | function options() {
  function init (line 58) | function init() {
  function main (line 70) | async function main() {

FILE: cli/api-txt2img.js
  function main (line 27) | async function main() {

FILE: cli/api-txt2img.py
  function auth (line 25) | def auth():
  function post (line 31) | def post(endpoint: str, dct: dict = None):
  function generate (line 39) | def generate(args): # pylint: disable=redefined-outer-name

FILE: cli/api-upscale.py
  function auth (line 21) | def auth():
  function get (line 27) | def get(endpoint: str, dct: dict = None):
  function post (line 35) | def post(endpoint: str, dct: dict = None):
  function encode (line 43) | def encode(f):
  function upscale (line 56) | def upscale(args): # pylint: disable=redefined-outer-name

FILE: cli/api-vqa.py
  function auth (line 21) | def auth():
  function get (line 27) | def get(endpoint: str, dct: dict = None):
  function post (line 35) | def post(endpoint: str, dct: dict = None):
  function info (line 43) | def info(args): # pylint: disable=redefined-outer-name

FILE: cli/api-xyz.py
  function auth (line 27) | def auth():
  function post (line 33) | def post(endpoint: str, dct: dict = None):
  function generate (line 41) | def generate(args): # pylint: disable=redefined-outer-name

FILE: cli/api-xyzenum.py
  function auth (line 21) | def auth():
  function get (line 27) | def get(endpoint: str, dct: dict = None):

FILE: cli/civitai-search.py
  class ModelImage (line 18) | class ModelImage():
    method __init__ (line 19) | def __init__(self, dct: dict):
    method __str__ (line 29) | def __str__(self):
  class ModelFile (line 33) | class ModelFile():
    method __init__ (line 34) | def __init__(self, dct: dict):
    method __str__ (line 45) | def __str__(self):
  class ModelVersion (line 50) | class ModelVersion():
    method __init__ (line 51) | def __init__(self, dct: dict):
    method __str__ (line 67) | def __str__(self):
  class Model (line 72) | class Model():
    method __init__ (line 73) | def __init__(self, dct: dict):
    method __str__ (line 92) | def __str__(self):
  function search_civitai (line 96) | def search_civitai(
  function models_to_dct (line 167) | def models_to_dct(all_models:list, model_id:int=None):
  function print_models (line 184) | def print_models(models: list[Model]):

FILE: cli/download-file.py
  function get_filename (line 20) | def get_filename(args, res):
  function download_requests (line 25) | def download_requests(args):
  function download_urllib (line 39) | def download_urllib(args):
  function download_urllib3 (line 58) | def download_urllib3(args):
  function download_httpx (line 76) | def download_httpx(args):

FILE: cli/gen-styles.py
  function pil_to_b64 (line 27) | def pil_to_b64(img: Image, size: int, quality: int):
  function post (line 36) | def post(endpoint: str, dct: dict = None):

FILE: cli/generate.py
  function grid (line 45) | def grid(data):
  function exif (line 63) | def exif(info, i = None, op = 'generate'):
  function randomize (line 83) | def randomize(lst):
  function prompt (line 90) | def prompt(params): # generate dynamic prompt or use one if provided
  function sampler (line 110) | def sampler(params, options): # find sampler
  function generate (line 123) | async def generate(prompt = None, options = None, quiet = False): # pyli...
  function upscale (line 158) | async def upscale(data):
  function init (line 175) | async def init():
  function args (line 219) | def args(): # parse cmd arguments
  function main (line 321) | async def main():

FILE: cli/git-clone.py
  class GitRemoteProgress (line 8) | class GitRemoteProgress(git.RemoteProgress):
    method __init__ (line 12) | def __init__(self, url, folder) -> None:
    method __del__ (line 30) | def __del__(self) -> None:
    method get_curr_op (line 34) | def get_curr_op(cls, op_code: int) -> str:
    method update (line 38) | def update(self, op_code: int, cur_count: str | float, max_count: str ...
  function clone (line 47) | def clone(url: str, folder: str):

FILE: cli/image-encode.py
  function encode (line 10) | def encode(file: str):

FILE: cli/image-exif.py
  class Exif (line 21) | class Exif: # pylint: disable=single-string-used-for-slots
    method __init__ (line 23) | def __init__(self, image = None):
    method __getattr__ (line 31) | def __getattr__(self, attr):
    method load (line 36) | def load(self, img: Image):
    method decode (line 65) | def decode(self, s: bytes):
    method parse (line 84) | def parse(self):
    method get_bytes (line 89) | def get_bytes(self):
  function print_json (line 102) | def print_json(data):
  function read_exif (line 110) | def read_exif(filename: str):

FILE: cli/image-grid.py
  function wrap (line 19) | def wrap(text: str, font: ImageFont.ImageFont, length: int):
  function grid (line 30) | def grid(images, labels = None, width = 0, height = 0, border = 0, squar...

FILE: cli/image-palette.py
  function color_to_df (line 22) | def color_to_df(param):
  function palette (line 34) | def palette(img, params, output):

FILE: cli/image-search.py
  class ImageDB (line 16) | class ImageDB:
    method __init__ (line 19) | def __init__(self,
    method __str__ (line 49) | def __str__(self):
    method init (line 52) | def init(self): # initialize models
    method load (line 65) | def load(self): # load db to disk
    method save (line 80) | def save(self): # save db to disk
    method normalize (line 90) | def normalize(self, embed) -> np.ndarray: # normalize embed before usi...
    method embedding (line 95) | def embedding(self, query: Union[PIL.Image.Image | str]) -> np.ndarray...
    method add (line 118) | def add(self, embed, filename=None, metadata=None): # add embed to db
    method search (line 126) | def search(self, filename: str = None, metadata: str = None, embed: np...
    method decode (line 151) | def decode(self, s: bytes): # decode byte-encoded exif metadata
    method metadata (line 167) | def metadata(self, image: PIL.Image.Image): # get exif metadata from i...
    method image (line 176) | def image(self, filename: str, image=None): # add file/image to db
    method folder (line 189) | def folder(self, folder: str): # add all files from folder to db
    method offload (line 201) | def offload(self): # offload model to cpu

FILE: cli/image-watermark.py
  function get_exif (line 20) | def get_exif(image):
  function set_exif (line 40) | def set_exif(d: dict):
  function get_watermark (line 51) | def get_watermark(image, params):
  function set_watermark (line 59) | def set_watermark(image, params):
  function watermark (line 71) | def watermark(params, file):

FILE: cli/install-stablefast.py
  function install_pip (line 14) | def install_pip(arg: str):
  function get_nightly (line 22) | def get_nightly():
  function install_stable_fast (line 45) | def install_stable_fast():

FILE: cli/load-unet.py
  class StateDictStats (line 7) | class StateDictStats():
    method __repr__ (line 15) | def __repr__(self):
  function set_module_tensor (line 19) | def set_module_tensor(
  function load_unet (line 50) | def load_unet(config_file: str, state_dict: dict, device: torch.device =...
  function load_safetensors (line 73) | def load_safetensors(fn: str):

FILE: cli/localize.js
  function localize (line 28) | async function localize() {

FILE: cli/model-keys.py
  function has (line 7) | def has(obj, attr, *args):
  function remove_entries_after_depth (line 16) | def remove_entries_after_depth(d, depth, current_depth=0):
  function list_to_dict (line 27) | def list_to_dict(flat_list):
  function list_compact (line 41) | def list_compact(flat_list):
  function guess_dct (line 51) | def guess_dct(dct: dict):
  function read_keys (line 69) | def read_keys(fn):
  function main (line 90) | def main():

FILE: cli/model-metadata.py
  function read_metadata (line 8) | def read_metadata(fn):
  function main (line 33) | def main():

FILE: cli/nvidia-smi.py
  function get_nvidia_smi (line 11) | def get_nvidia_smi(output='dict'):

FILE: cli/process.py
  class Result (line 24) | class Result():
    method __init__ (line 25) | def __init__(self, typ: str, fn: str, tag: str = None, requested: list...
  function detect_blur (line 39) | def detect_blur(image: Image):
  function detect_dynamicrange (line 53) | def detect_dynamicrange(image: Image):
  function detect_simmilar (line 72) | def detect_simmilar(image: Image):
  function segmentation (line 85) | def segmentation(res: Result):
  function unload (line 101) | def unload():
  function encode (line 113) | def encode(img):
  function reset (line 121) | def reset():
  function upscale_restore_image (line 129) | def upscale_restore_image(res: Result, upscale: bool = False, restore: b...
  function interrogate_image (line 154) | def interrogate_image(res: Result, tag: str = None):
  function resize_image (line 183) | def resize_image(res: Result):
  function square_image (line 191) | def square_image(res: Result):
  function process_face (line 200) | def process_face(res: Result):
  function process_body (line 224) | def process_body(res: Result):
  function process_original (line 246) | def process_original(res: Result):
  function save_image (line 251) | def save_image(res: Result, folder: str):
  function file (line 265) | def file(filename: str, folder: str, tag = None, requested = []):

FILE: cli/run-benchmark.py
  function txt2img (line 22) | async def txt2img():
  function memstats (line 50) | def memstats():
  function gb (line 67) | def gb(val: float):
  function main (line 71) | async def main():

FILE: cli/sdapi.py
  class AnyThreadEventLoopPolicy (line 36) | class AnyThreadEventLoopPolicy(BaseThreadPolicy):
    method get_event_loop (line 37) | def get_event_loop(self) -> asyncio.AbstractEventLoop:
  function authsync (line 48) | def authsync():
  function auth (line 54) | def auth():
  function result (line 60) | async def result(req):
  function resultsync (line 79) | def resultsync(req: requests.Response):
  function get (line 96) | async def get(endpoint: str, json: dict = None):
  function getsync (line 108) | def getsync(endpoint: str, json: dict = None):
  function post (line 118) | async def post(endpoint: str, json: dict = None):
  function postsync (line 133) | def postsync(endpoint: str, json: dict = None):
  function interrupt (line 139) | async def interrupt():
  function interruptsync (line 151) | def interruptsync():
  function progress (line 162) | async def progress():
  function progresssync (line 173) | def progresssync():
  function get_log (line 179) | def get_log():
  function get_info (line 186) | def get_info():
  function options (line 195) | def options():
  function shutdown (line 201) | def shutdown():
  function session (line 208) | async def session():
  function close (line 228) | async def close():

FILE: cli/search-docs.py
  class Page (line 12) | class Page():
    method __init__ (line 13) | def __init__(self, fn, full: bool = True):
    method read (line 24) | def read(self, full: bool = True):
    method search (line 40) | def search(self, text):
    method get (line 82) | def get(self):
    method __str__ (line 91) | def __str__(self):
  class Pages (line 95) | class Pages():
    method __init__ (line 96) | def __init__(self):
    method build (line 102) | def build(self, full: bool = True):
    method search (line 112) | def search(self, text: str, topk: int = 10, full: bool = True) -> list...

FILE: cli/test-schedulers.py
  function test_scheduler (line 32) | def test_scheduler(name, scheduler_class, config):
  function run_tests (line 151) | def run_tests():

FILE: cli/test-tagger.py
  function find_test_image (line 49) | def find_test_image():
  function create_test_image (line 58) | def create_test_image():
  class TaggerTest (line 68) | class TaggerTest:
    method __init__ (line 71) | def __init__(self):
    method log_pass (line 77) | def log_pass(self, msg):
    method log_fail (line 81) | def log_fail(self, msg):
    method log_skip (line 85) | def log_skip(self, msg):
    method log_warn (line 89) | def log_warn(self, msg):
    method setup (line 93) | def setup(self):
    method cleanup (line 129) | def cleanup(self):
    method print_summary (line 143) | def print_summary(self):
    method test_onnx_providers (line 171) | def test_onnx_providers(self):
    method get_memory_stats (line 220) | def get_memory_stats(self):
    method test_memory_management (line 245) | def test_memory_management(self):
    method test_settings_exist (line 457) | def test_settings_exist(self):
    method test_parameter (line 489) | def test_parameter(self, param_name, test_func, waifudiffusion_support...
    method tag (line 521) | def tag(self, tagger, **kwargs):
    method test_threshold (line 533) | def test_threshold(self):
    method test_max_tags (line 560) | def test_max_tags(self):
    method test_use_spaces (line 582) | def test_use_spaces(self):
    method test_escape_brackets (line 613) | def test_escape_brackets(self):
    method test_sort_alpha (line 643) | def test_sort_alpha(self):
    method test_exclude_tags (line 667) | def test_exclude_tags(self):
    method test_show_scores (line 699) | def test_show_scores(self):
    method test_include_rating (line 731) | def test_include_rating(self):
    method test_character_threshold (line 764) | def test_character_threshold(self):
    method test_unified_interface (line 791) | def test_unified_interface(self):
    method run_all_tests (line 820) | def run_all_tests(self):

FILE: cli/util.py
  function set_logfile (line 19) | def set_logfile(logfile):
  function safestring (line 28) | def safestring(text: str):
  function get_memory (line 36) | def get_memory():
  class Map (line 73) | class Map(dict): # pylint: disable=C0205
    method __init__ (line 75) | def __init__(self, *args, **kwargs):
    method __convert (line 92) | def __convert(self, v):
    method __getattr__ (line 98) | def __getattr__(self, attr):
    method __setattr__ (line 100) | def __setattr__(self, key, value):
    method __setitem__ (line 102) | def __setitem__(self, key, value):
    method __delattr__ (line 105) | def __delattr__(self, item):
    method __delitem__ (line 107) | def __delitem__(self, key):

FILE: cli/video-extract.py
  function probe (line 14) | def probe(src: str):
  function extract (line 31) | def extract(src: str, dst: str, rate: float = 0.015, fps: float = 0, sta...

FILE: cli/zluda-python.py
  class Interpreter (line 6) | class Interpreter:
    method __init__ (line 10) | def __init__(self, env_globals, env_locals):
    method execute (line 14) | def execute(self, s: str):
    method from_file (line 20) | def from_file(self, path):

FILE: installer.py
  class Dot (line 17) | class Dot(dict): # dot notation access to dictionary attributes
  function get_console (line 88) | def get_console():
  function get_log (line 92) | def get_log():
  function str_to_bool (line 97) | def str_to_bool(val: str | bool) -> bool: ...
  function str_to_bool (line 99) | def str_to_bool(val: None) -> None: ...
  function str_to_bool (line 100) | def str_to_bool(val: str | bool | None) -> bool | None:
  function install_traceback (line 108) | def install_traceback(suppress: list = []):
  function setup_logging (line 131) | def setup_logging():
  function get_logfile (line 312) | def get_logfile():
  function custom_excepthook (line 318) | def custom_excepthook(exc_type, exc_value, exc_traceback):
  function print_dict (line 330) | def print_dict(d):
  function print_profile (line 336) | def print_profile(profiler: cProfile.Profile, msg: str):
  function package_version (line 342) | def package_version(package):
  function package_spec (line 352) | def package_spec(package):
  function installed (line 365) | def installed(package, friendly: str = None, reload = False, quiet = Fal...
  function uninstall (line 411) | def uninstall(package, quiet = False):
  function run (line 424) | def run(cmd: str, arg: str):
  function pip (line 434) | def pip(arg: str, ignore: bool = False, quiet: bool = True, uv = True):
  function install (line 471) | def install(package, friendly: str = None, ignore: bool = False, reinsta...
  function git (line 490) | def git(arg: str, folder: str = None, ignore: bool = False, optional: bo...
  function branch (line 521) | def branch(folder=None):
  function restart (line 552) | def restart():
  function update (line 558) | def update(folder, keep_branch = False, rebase = True):
  function clone (line 586) | def clone(url, folder, commithash=None):
  function get_platform (line 606) | def get_platform():
  function check_python (line 628) | def check_python(supported_minors=[], experimental_minors=[], reason=None):
  function check_diffusers (line 664) | def check_diffusers():
  function check_transformers (line 689) | def check_transformers():
  function check_onnx (line 716) | def check_onnx():
  function install_cuda (line 727) | def install_cuda():
  function install_rocm_zluda (line 738) | def install_rocm_zluda():
  function install_ipex (line 856) | def install_ipex():
  function install_openvino (line 871) | def install_openvino():
  function install_torch_addons (line 889) | def install_torch_addons():
  function check_cudnn (line 923) | def check_cudnn():
  function check_torch (line 938) | def check_torch():
  function check_modified_files (line 1074) | def check_modified_files():
  function install_packages (line 1096) | def install_packages():
  function run_extension_installer (line 1116) | def run_extension_installer(folder):
  function list_extensions_folder (line 1147) | def list_extensions_folder(folder, quiet=False):
  function install_extensions (line 1159) | def install_extensions(force=False):
  function install_submodules (line 1218) | def install_submodules(force=True):
  function reload (line 1251) | def reload(package, desired=None):
  function ensure_base_requirements (line 1265) | def ensure_base_requirements():
  function install_gradio (line 1316) | def install_gradio():
  function install_pydantic (line 1328) | def install_pydantic():
  function install_opencv (line 1337) | def install_opencv():
  function install_insightface (line 1344) | def install_insightface():
  function install_optional (line 1355) | def install_optional():
  function install_requirements (line 1385) | def install_requirements():
  function set_environment (line 1420) | def set_environment():
  function check_extensions (line 1468) | def check_extensions():
  function get_version (line 1497) | def get_version(force=False):
  function check_ui (line 1557) | def check_ui(ver):
  function check_venv (line 1580) | def check_venv():
  function check_version (line 1611) | def check_version(reset=True): # pylint: disable=unused-argument
  function update_wiki (line 1688) | def update_wiki():
  function check_timestamp (line 1700) | def check_timestamp():
  function add_args (line 1737) | def add_args(parser):
  function parse_args (line 1815) | def parse_args(parser):
  function extensions_preload (line 1828) | def extensions_preload(parser):
  function git_reset (line 1854) | def git_reset(folder='.'):
  function read_options (line 1874) | def read_options():

FILE: javascript/aspectRatioOverlay.js
  function dimensionChange (line 5) | function dimensionChange(e, is_width, is_height) {

FILE: javascript/authWrap.js
  function getToken (line 4) | async function getToken() {
  function authFetch (line 17) | async function authFetch(url, options = {}) {

FILE: javascript/changelog.js
  function getText (line 12) | function getText(el) {
  function changelogNavigate (line 22) | function changelogNavigate(found) {
  function initChangelog (line 60) | async function initChangelog() {

FILE: javascript/civitai.js
  function clearModelDetails (line 15) | function clearModelDetails() {
  function modelCardClick (line 72) | async function modelCardClick(id) {
  function startCivitDownload (line 116) | function startCivitDownload(url, name, type) {
  function startCivitAllDownload (line 125) | function startCivitAllDownload(evt) {
  function downloadCivitModel (line 142) | function downloadCivitModel(modelUrl, modelName, modelType, modelPath, c...

FILE: javascript/contextMenus.js
  function showContextMenu (line 7) | function showContextMenu(event, element, menuEntries) {
  function appendContextMenuOption (line 34) | function appendContextMenuOption(targetElementSelector, entryName, entry...
  function removeContextMenuOption (line 51) | function removeContextMenuOption(id) {
  function addContextMenuEventListener (line 61) | async function addContextMenuEventListener() {
  function initContextMenu (line 150) | async function initContextMenu() {

FILE: javascript/control.js
  function controlInputMode (line 1) | function controlInputMode(inputMode, ...args) {
  function setupControlUI (line 19) | async function setupControlUI() {

FILE: javascript/docs.js
  function clickGitHubWikiPage (line 4) | async function clickGitHubWikiPage(page) {
  function getGitHubWikiPage (line 11) | function getGitHubWikiPage() {
  function clickDocsPage (line 15) | async function clickDocsPage(page) {
  function getDocsPage (line 22) | function getDocsPage() {

FILE: javascript/dragDrop.js
  function isValidImageList (line 1) | function isValidImageList(files) {
  function dropReplaceImage (line 5) | function dropReplaceImage(imgWrap, files) {

FILE: javascript/editAttention.js
  function keyupEditAttention (line 1) | function keyupEditAttention(event) {

FILE: javascript/exifr.js
  function h (line 1) | function h(e,t=l){if(s)try{return"function"==typeof require?Promise.reso...
  function f (line 1) | function f(e,t,i){return t in e?Object.defineProperty(e,t,{value:i,enume...
  function g (line 1) | function g(e){return void 0===e||(e instanceof Map?0===e.size:0===Object...
  function m (line 1) | function m(e){let t=new Error(e);throw delete t.stack,t}
  function S (line 1) | function S(e){return""===(e=function(e){for(;e.endsWith("\0");)e=e.slice...
  function C (line 1) | function C(e){let t=function(e){let t=0;return e.ifd0.enabled&&(t+=1024)...
  function P (line 1) | function P(e){return b?b.decode(e):o?Buffer.from(e).toString("utf8"):dec...
  class I (line 1) | class I{static from(e,t){return e instanceof this&&e.le===t?e:new I(e,vo...
    method from (line 1) | static from(e,t){return e instanceof this&&e.le===t?e:new I(e,void 0,v...
    method constructor (line 1) | constructor(e,t=0,i,n){if("boolean"==typeof n&&(this.le=n),Array.isArr...
    method _swapArrayBuffer (line 1) | _swapArrayBuffer(e){this._swapDataView(new DataView(e))}
    method _swapBuffer (line 1) | _swapBuffer(e){this._swapDataView(new DataView(e.buffer,e.byteOffset,e...
    method _swapDataView (line 1) | _swapDataView(e){this.dataView=e,this.buffer=e.buffer,this.byteOffset=...
    method _lengthToEnd (line 1) | _lengthToEnd(e){return this.byteLength-e}
    method set (line 1) | set(e,t,i=I){return e instanceof DataView||e instanceof I?e=new Uint8A...
    method subarray (line 1) | subarray(e,t){return t=t||this._lengthToEnd(e),new I(this,e,t)}
    method toUint8 (line 1) | toUint8(){return new Uint8Array(this.buffer,this.byteOffset,this.byteL...
    method getUint8Array (line 1) | getUint8Array(e,t){return new Uint8Array(this.buffer,this.byteOffset+e...
    method getString (line 1) | getString(e=0,t=this.byteLength){return P(this.getUint8Array(e,t))}
    method getLatin1String (line 1) | getLatin1String(e=0,t=this.byteLength){let i=this.getUint8Array(e,t);r...
    method getUnicodeString (line 1) | getUnicodeString(e=0,t=this.byteLength){const i=[];for(let n=0;n<t&&e+...
    method getInt8 (line 1) | getInt8(e){return this.dataView.getInt8(e)}
    method getUint8 (line 1) | getUint8(e){return this.dataView.getUint8(e)}
    method getInt16 (line 1) | getInt16(e,t=this.le){return this.dataView.getInt16(e,t)}
    method getInt32 (line 1) | getInt32(e,t=this.le){return this.dataView.getInt32(e,t)}
    method getUint16 (line 1) | getUint16(e,t=this.le){return this.dataView.getUint16(e,t)}
    method getUint32 (line 1) | getUint32(e,t=this.le){return this.dataView.getUint32(e,t)}
    method getFloat32 (line 1) | getFloat32(e,t=this.le){return this.dataView.getFloat32(e,t)}
    method getFloat64 (line 1) | getFloat64(e,t=this.le){return this.dataView.getFloat64(e,t)}
    method getFloat (line 1) | getFloat(e,t=this.le){return this.dataView.getFloat32(e,t)}
    method getDouble (line 1) | getDouble(e,t=this.le){return this.dataView.getFloat64(e,t)}
    method getUintBytes (line 1) | getUintBytes(e,t,i){switch(t){case 1:return this.getUint8(e,i);case 2:...
    method getUint (line 1) | getUint(e,t,i){switch(t){case 8:return this.getUint8(e,i);case 16:retu...
    method toString (line 1) | toString(e){return this.dataView.toString(e,this.constructor.name)}
    method ensureChunk (line 1) | ensureChunk(){}
  function k (line 1) | function k(e,t){m(`${e} '${t}' was not loaded, try using full build of e...
  class w (line 1) | class w extends Map{constructor(e){super(),this.kind=e}get(e,t){return t...
    method constructor (line 1) | constructor(e){super(),this.kind=e}
    method get (line 1) | get(e,t){return this.has(e)||k(this.kind,e),t&&(e in t||function(e,t){...
    method keyList (line 1) | keyList(){return Array.from(this.keys())}
  function x (line 1) | function x(e,t){return"string"==typeof e?v(e,t):i&&!n&&e instanceof HTML...
  function v (line 1) | function v(e,t){return(n=e).startsWith("data:")||n.length>1e4?R(e,t,"bas...
  function M (line 1) | async function M(e,t,i,n){return D.has(i)?R(e,t,i):n?async function(e,t)...
  function R (line 1) | async function R(e,t,i){let n=new(D.get(i))(e,t);return await n.read(),n}
  class F (line 1) | class F extends Map{get tagKeys(){return this.allKeys||(this.allKeys=Arr...
    method tagKeys (line 1) | get tagKeys(){return this.allKeys||(this.allKeys=Array.from(this.keys(...
    method tagValues (line 1) | get tagValues(){return this.allValues||(this.allValues=Array.from(this...
  function B (line 1) | function B(e,t,i){let n=new F;for(let[e,t]of i)n.set(e,t);if(Array.isArr...
  function E (line 1) | function E(e,t,i){let n,s=e.get(t);for(n of i)s.set(n[0],n[1])}
  class ne (line 1) | class ne{get translate(){return this.translateKeys||this.translateValues...
    method translate (line 1) | get translate(){return this.translateKeys||this.translateValues||this....
  class se (line 1) | class se extends ne{get needed(){return this.enabled||this.deps.size>0}c...
    method needed (line 1) | get needed(){return this.enabled||this.deps.size>0}
    method constructor (line 1) | constructor(e,t,i,n){if(super(),f(this,"enabled",!1),f(this,"skip",new...
    method applyInheritables (line 1) | applyInheritables(e){let t,i;for(t of te)i=e[t],void 0!==i&&(this[t]=i)}
    method translateTagSet (line 1) | translateTagSet(e,t){if(this.dict){let i,n,{tagKeys:s,tagValues:r}=thi...
    method finalizeFilters (line 1) | finalizeFilters(){!this.enabled&&this.deps.size>0?(this.enabled=!0,ue(...
  class oe (line 1) | class oe extends ne{static useCached(e){let t=ae.get(e);return void 0!==...
    method useCached (line 1) | static useCached(e){let t=ae.get(e);return void 0!==t||(t=new this(e),...
    method constructor (line 1) | constructor(e){super(),!0===e?this.setupFromTrue():void 0===e?this.set...
    method setupFromUndefined (line 1) | setupFromUndefined(){let e;for(e of $)this[e]=re[e];for(e of ie)this[e...
    method setupFromTrue (line 1) | setupFromTrue(){let e;for(e of $)this[e]=re[e];for(e of ie)this[e]=re[...
    method setupFromArray (line 1) | setupFromArray(e){let t;for(t of $)this[t]=re[t];for(t of ie)this[t]=r...
    method setupFromObject (line 1) | setupFromObject(e){let t;for(t of(Q.ifd0=Q.ifd0||Q.image,Q.ifd1=Q.ifd1...
    method batchEnableWithBool (line 1) | batchEnableWithBool(e,t){for(let i of e)this[i].enabled=t}
    method batchEnableWithUserValue (line 1) | batchEnableWithUserValue(e,t){for(let i of e){let e=t[i];this[i].enabl...
    method setupGlobalFilters (line 1) | setupGlobalFilters(e,t,i,n=i){if(e&&e.length){for(let e of n)this[e].e...
    method filterNestedSegmentTags (line 1) | filterNestedSegmentTags(){let{ifd0:e,exif:t,xmp:i,iptc:n,icc:s}=this;t...
    method traverseTiffDependencyTree (line 1) | traverseTiffDependencyTree(){let{ifd0:e,exif:t,gps:i,interop:n}=this;n...
    method onlyTiff (line 1) | get onlyTiff(){return!J.map((e=>this[e].enabled)).some((e=>!0===e))&&t...
    method checkLoadedPlugins (line 1) | checkLoadedPlugins(){for(let e of q)this[e].enabled&&!A.has(e)&&k("seg...
  function le (line 1) | function le(e,t){let i,n,s,r,a=[];for(s of t){for(r of(i=N.get(s),n=[],i...
  function he (line 1) | function he(e,t){return void 0!==e?e:void 0!==t?t:void 0}
  function ue (line 1) | function ue(e,t){for(let i of t)e.add(i)}
  class ce (line 1) | class ce{constructor(e){f(this,"parsers",{}),f(this,"output",{}),f(this,...
    method constructor (line 1) | constructor(e){f(this,"parsers",{}),f(this,"output",{}),f(this,"errors...
    method read (line 1) | async read(e){this.file=await x(e,this.options)}
    method setup (line 1) | setup(){if(this.fileParser)return;let{file:e}=this,t=e.getUint16(0);fo...
    method parse (line 1) | async parse(){let{output:e,errors:t}=this;return this.setup(),this.opt...
    method executeParsers (line 1) | async executeParsers(){let{output:e}=this;await this.fileParser.parse(...
    method extractThumbnail (line 1) | async extractThumbnail(){this.setup();let{options:e,file:t}=this,i=A.g...
  function fe (line 1) | async function fe(e,t){let i=new ce(t);return await i.read(e),i.parse()}
  class pe (line 1) | class pe{constructor(e,t,i){f(this,"errors",[]),f(this,"ensureSegmentChu...
    method constructor (line 1) | constructor(e,t,i){f(this,"errors",[]),f(this,"ensureSegmentChunk",(as...
    method injectSegment (line 1) | injectSegment(e,t){this.options[e].enabled&&this.createParser(e,t)}
    method createParser (line 1) | createParser(e,t){let i=new(A.get(e))(t,this.options,this.file);return...
    method createParsers (line 1) | createParsers(e){for(let t of e){let{type:e,chunk:i}=t,n=this.options[...
    method readSegments (line 1) | async readSegments(e){let t=e.map(this.ensureSegmentChunk);await Promi...
  class ge (line 1) | class ge{static findPosition(e,t){let i=e.getUint16(t+2)+2,n="function"=...
    method findPosition (line 1) | static findPosition(e,t){let i=e.getUint16(t+2)+2,n="function"==typeof...
    method parse (line 1) | static parse(e,t={}){return new this(e,new oe({[this.type]:t}),e).pars...
    method normalizeInput (line 1) | normalizeInput(e){return e instanceof I?e:new I(e)}
    method constructor (line 1) | constructor(e,t={},i){f(this,"errors",[]),f(this,"raw",new Map),f(this...
    method translate (line 1) | translate(){this.canTranslate&&(this.translated=this.translateBlock(th...
    method output (line 1) | get output(){return this.translated?this.translated:this.raw?Object.fr...
    method translateBlock (line 1) | translateBlock(e,t){let i=V.get(t),n=G.get(t),s=N.get(t),r=this.option...
    method translateValue (line 1) | translateValue(e,t){return t[e]||t.DEFAULT||e}
    method assignToOutput (line 1) | assignToOutput(e,t){this.assignObjectToOutput(e,this.constructor.type,t)}
    method assignObjectToOutput (line 1) | assignObjectToOutput(e,t,i){if(this.globalOptions.mergeOutput)return O...
  function me (line 1) | function me(e){return 192===e||194===e||196===e||219===e||221===e||218==...
  function Se (line 1) | function Se(e){return e>=224&&e<=239}
  function Ce (line 1) | function Ce(e,t,i){for(let[n,s]of A)if(s.canHandle(e,t,i))return n}
  class ye (line 1) | class ye extends pe{constructor(...e){super(...e),f(this,"appSegments",[...
    method constructor (line 1) | constructor(...e){super(...e),f(this,"appSegments",[]),f(this,"jpegSeg...
    method canHandle (line 1) | static canHandle(e,t){return 65496===t}
    method parse (line 1) | async parse(){await this.findAppSegments(),await this.readSegments(thi...
    method setupSegmentFinderArgs (line 1) | setupSegmentFinderArgs(e){!0===e?(this.findAll=!0,this.wanted=new Set(...
    method findAppSegments (line 1) | async findAppSegments(e=0,t){this.setupSegmentFinderArgs(t);let{file:i...
    method findAppSegmentsInRange (line 1) | findAppSegmentsInRange(e,t){t-=2;let i,n,s,r,a,o,{file:l,findAll:h,wan...
    method mergeMultiSegments (line 1) | mergeMultiSegments(){if(!this.appSegments.some((e=>e.multiSegment)))re...
    method getSegment (line 1) | getSegment(e){return this.appSegments.find((t=>t.type===e))}
    method getOrFindSegment (line 1) | async getOrFindSegment(e){let t=this.getSegment(e);return void 0===t&&...
  class Pe (line 1) | class Pe extends ge{parseHeader(){var e=this.chunk.getUint16();18761===e...
    method parseHeader (line 1) | parseHeader(){var e=this.chunk.getUint16();18761===e?this.le=!0:19789=...
    method parseTags (line 1) | parseTags(e,t,i=new Map){let{pick:n,skip:s}=this.options[t];n=new Set(...
    method parseTag (line 1) | parseTag(e,t,i){let{chunk:n}=this,s=n.getUint16(e+2),r=n.getUint32(e+4...
    method parseTagValue (line 1) | parseTagValue(e,t){let{chunk:i}=this;switch(e){case 1:return i.getUint...
  class Ie (line 1) | class Ie extends Pe{static canHandle(e,t){return 225===e.getUint8(t+1)&&...
    method canHandle (line 1) | static canHandle(e,t){return 225===e.getUint8(t+1)&&1165519206===e.get...
    method parse (line 1) | async parse(){this.parseHeader();let{options:e}=this;return e.ifd0.ena...
    method safeParse (line 1) | safeParse(e){let t=this[e]();return void 0!==t.catch&&(t=t.catch(this....
    method findIfd0Offset (line 1) | findIfd0Offset(){void 0===this.ifd0Offset&&(this.ifd0Offset=this.chunk...
    method findIfd1Offset (line 1) | findIfd1Offset(){if(void 0===this.ifd1Offset){this.findIfd0Offset();le...
    method parseBlock (line 1) | parseBlock(e,t){let i=new Map;return this[t]=i,this.parseTags(e,t,i),i}
    method parseIfd0Block (line 1) | async parseIfd0Block(){if(this.ifd0)return;let{file:e}=this;this.findI...
    method parseExifBlock (line 1) | async parseExifBlock(){if(this.exif)return;if(this.ifd0||await this.pa...
    method unpack (line 1) | unpack(e,t){let i=e.get(t);i&&1===i.length&&e.set(t,i[0])}
    method parseGpsBlock (line 1) | async parseGpsBlock(){if(this.gps)return;if(this.ifd0||await this.pars...
    method parseInteropBlock (line 1) | async parseInteropBlock(){if(!this.interop&&(this.ifd0||await this.par...
    method parseThumbnailBlock (line 1) | async parseThumbnailBlock(e=!1){if(!this.ifd1&&!this.ifd1Parsed&&(!thi...
    method extractThumbnail (line 1) | async extractThumbnail(){if(this.headerParsed||this.parseHeader(),this...
    method image (line 1) | get image(){return this.ifd0}
    method thumbnail (line 1) | get thumbnail(){return this.ifd1}
    method createOutput (line 1) | createOutput(){let e,t,i,n={};for(t of Q)if(e=this[t],!g(e))if(i=this....
    method assignToOutput (line 1) | assignToOutput(e,t){if(this.globalOptions.mergeOutput)Object.assign(e,...
  function ke (line 1) | function ke(e,t,i,n){var s=e+t/60+i/3600;return"S"!==n&&"W"!==n||(s*=-1),s}
  function De (line 1) | async function De(e){let t=new ce(Ae);await t.read(e);let i=await t.pars...
  function xe (line 1) | async function xe(e){let t=new ce(Oe);await t.read(e);let i=await t.extr...
  function ve (line 1) | async function ve(e){let t=await this.thumbnail(e);if(void 0!==t){let e=...
  function Re (line 1) | async function Re(e){let t=new ce(Me);await t.read(e);let i=await t.pars...
  function Ue (line 1) | async function Ue(t){let i=await Re(t);return Object.assign({canvas:e.ro...
  class Fe (line 1) | class Fe extends I{constructor(...e){super(...e),f(this,"ranges",new Be)...
    method constructor (line 1) | constructor(...e){super(...e),f(this,"ranges",new Be),0!==this.byteLen...
    method _tryExtend (line 1) | _tryExtend(e,t,i){if(0===e&&0===this.byteLength&&i){let e=new DataView...
    method _extend (line 1) | _extend(e){let t;t=o?r.allocUnsafe(e):new Uint8Array(e);let i=new Data...
    method subarray (line 1) | subarray(e,t,i=!1){return t=t||this._lengthToEnd(e),i&&this._tryExtend...
    method set (line 1) | set(e,t,i=!1){i&&this._tryExtend(t,e.byteLength,e);let n=super.set(e,t...
    method ensureChunk (line 1) | async ensureChunk(e,t){this.chunked&&(this.ranges.available(e,t)||awai...
    method available (line 1) | available(e,t){return this.ranges.available(e,t)}
  class Be (line 1) | class Be{constructor(){f(this,"list",[])}get length(){return this.list.l...
    method constructor (line 1) | constructor(){f(this,"list",[])}
    method length (line 1) | get length(){return this.list.length}
    method add (line 1) | add(e,t,i=0){let n=e+t,s=this.list.filter((t=>Ee(e,t.offset,n)||Ee(e,t...
    method available (line 1) | available(e,t){let i=e+t;return this.list.some((t=>t.offset<=e&&i<=t.e...
  function Ee (line 1) | function Ee(e,t,i){return e<=t&&t<=i}
  class Ne (line 1) | class Ne extends Fe{constructor(e,t){super(0),f(this,"chunksRead",0),thi...
    method constructor (line 1) | constructor(e,t){super(0),f(this,"chunksRead",0),this.input=e,this.opt...
    method readWhole (line 1) | async readWhole(){this.chunked=!1,await this.readChunk(this.nextChunkO...
    method readChunked (line 1) | async readChunked(){this.chunked=!0,await this.readChunk(0,this.option...
    method readNextChunk (line 1) | async readNextChunk(e=this.nextChunkOffset){if(this.fullyRead)return t...
    method readChunk (line 1) | async readChunk(e,t){if(this.chunksRead++,0!==(t=this.safeWrapAddress(...
    method safeWrapAddress (line 1) | safeWrapAddress(e,t){return void 0!==this.size&&e+t>this.size?Math.max...
    method nextChunkOffset (line 1) | get nextChunkOffset(){if(0!==this.ranges.list.length)return this.range...
    method canReadNextChunk (line 1) | get canReadNextChunk(){return this.chunksRead<this.options.chunkLimit}
    method fullyRead (line 1) | get fullyRead(){return void 0!==this.size&&this.nextChunkOffset===this...
    method read (line 1) | read(){return this.options.chunked?this.readChunked():this.readWhole()}
    method close (line 1) | close(){}
  method readWhole (line 1) | async readWhole(){this.chunked=!1;let e=await U(this.input);this._swapAr...
  method readChunked (line 1) | readChunked(){return this.chunked=!0,this.size=this.input.size,super.rea...
  method _readChunk (line 1) | async _readChunk(e,t){let i=t?e+t:void 0,n=this.input.slice(e,i),s=await...
  method rotateCanvas (line 1) | get rotateCanvas(){return e.rotateCanvas}
  method rotateCss (line 1) | get rotateCss(){return e.rotateCss}
  method readWhole (line 1) | async readWhole(){this.chunked=!1;let e=await L(this.input);e instanceof...
  method _readChunk (line 1) | async _readChunk(e,t){let i=t?e+t-1:void 0,n=this.options.httpHeaders||{...
  class Ve (line 1) | class Ve extends pe{parseBoxes(e=0){let t=[];for(;e<this.file.byteLength...
    method parseBoxes (line 1) | parseBoxes(e=0){let t=[];for(;e<this.file.byteLength-4;){let i=this.pa...
    method parseSubBoxes (line 1) | parseSubBoxes(e){e.boxes=this.parseBoxes(e.start)}
    method findBox (line 1) | findBox(e,t){return void 0===e.boxes&&this.parseSubBoxes(e),e.boxes.fi...
    method parseBoxHead (line 1) | parseBoxHead(e){let t=this.file.getUint32(e),i=this.file.getString(e+4...
    method parseBoxFullHead (line 1) | parseBoxFullHead(e){if(void 0!==e.version)return;let t=this.file.getUi...
  class ze (line 1) | class ze extends Ve{static canHandle(e,t){if(0!==t)return!1;let i=e.getU...
    method canHandle (line 1) | static canHandle(e,t){if(0!==t)return!1;let i=e.getUint16(2);if(i>50)r...
    method parse (line 1) | async parse(){let e=this.file.getUint32(0),t=this.parseBoxHead(e);for(...
    method registerSegment (line 1) | async registerSegment(e,t,i){await this.file.ensureChunk(t,i);let n=th...
    method findIcc (line 1) | async findIcc(e){let t=this.findBox(e,"iprp");if(void 0===t)return;let...
    method findExif (line 1) | async findExif(e){let t=this.findBox(e,"iinf");if(void 0===t)return;le...
    method findExifLocIdInIinf (line 1) | findExifLocIdInIinf(e){this.parseBoxFullHead(e);let t,i,n,s,r=e.start,...
    method get8bits (line 1) | get8bits(e){let t=this.file.getUint8(e);return[t>>4,15&t]}
    method findExtentInIloc (line 1) | findExtentInIloc(e,t){this.parseBoxFullHead(e);let i=e.start,[n,s]=thi...
  class He (line 1) | class He extends ze{}
  class je (line 1) | class je extends ze{}
  function _e (line 1) | function _e(e){return"object"==typeof e&&void 0!==e.length?e[0]:e}
  function Ye (line 1) | function Ye(e){let t=Array.from(e).slice(1);return t[1]>15&&(t=t.map((e=...
  function $e (line 1) | function $e(e){if("string"==typeof e){var[t,i,n,s,r,a]=e.trim().split(/[...
  function Je (line 1) | function Je(e){if("string"==typeof e)return e;let t=[];if(0===e[1]&&0===...
  function qe (line 1) | function qe(e,t){return e<<8|t}
  class et (line 1) | class et extends ge{static canHandle(e,t){return 225===e.getUint8(t+1)&&...
    method canHandle (line 1) | static canHandle(e,t){return 225===e.getUint8(t+1)&&1752462448===e.get...
    method headerLength (line 1) | static headerLength(e,t){return e.getString(t+4,Ze.length)===Ze?79:4+"...
    method findPosition (line 1) | static findPosition(e,t){let i=super.findPosition(e,t);return i.multiS...
    method handleMultiSegments (line 1) | static handleMultiSegments(e){return e.map((e=>e.chunk.getString())).j...
    method normalizeInput (line 1) | normalizeInput(e){return"string"==typeof e?e:I.from(e).getString()}
    method parse (line 1) | parse(e=this.chunk){if(!this.localOptions.parse)return e;e=function(e)...
    method assignToOutput (line 1) | assignToOutput(e,t){if(this.localOptions.parse)for(let[i,n]of Object.e...
  class tt (line 1) | class tt{static findAll(e){return lt(e,/([a-zA-Z0-9-]+):([a-zA-Z0-9-]+)=...
    method findAll (line 1) | static findAll(e){return lt(e,/([a-zA-Z0-9-]+):([a-zA-Z0-9-]+)=("[^"]*...
    method unpackMatch (line 1) | static unpackMatch(e){let t=e[1],i=e[2],n=e[3].slice(1,-1);return n=ht...
    method constructor (line 1) | constructor(e,t,i){this.ns=e,this.name=t,this.value=i}
    method serialize (line 1) | serialize(){return this.value}
  class nt (line 1) | class nt{static findAll(e,t,i){if(void 0!==t||void 0!==i){t=t||it,i=i||i...
    method findAll (line 1) | static findAll(e,t,i){if(void 0!==t||void 0!==i){t=t||it,i=i||it;var n...
    method unpackMatch (line 1) | static unpackMatch(e){let t=e[1],i=e[2],n=e[4],s=e[8];return new nt(t,...
    method constructor (line 1) | constructor(e,t,i,n){this.ns=e,this.name=t,this.attrString=i,this.inne...
    method isPrimitive (line 1) | get isPrimitive(){return void 0!==this.value&&0===this.attrs.length&&0...
    method isListContainer (line 1) | get isListContainer(){return 1===this.children.length&&this.children[0...
    method isList (line 1) | get isList(){let{ns:e,name:t}=this;return"rdf"===e&&("Seq"===t||"Bag"=...
    method isListItem (line 1) | get isListItem(){return"rdf"===this.ns&&"li"===this.name}
    method serialize (line 1) | serialize(){if(0===this.properties.length&&void 0===this.value)return;...
  function st (line 1) | function st(e,t){let i=e.serialize();void 0!==i&&(t[e.name]=i)}
  function lt (line 1) | function lt(e,t){let i,n=[];if(!e)return n;for(;null!==(i=t.exec(e));)n....
  function ht (line 1) | function ht(e){if(function(e){return null==e||"null"===e||"undefined"===...
  method rotateCanvas (line 1) | get rotateCanvas(){return e.rotateCanvas}
  method rotateCss (line 1) | get rotateCss(){return e.rotateCss}
  function gt (line 1) | async function gt(e,t,i){let n=i[e];return n.enabled=!0,n.parse=!0,A.get...
  method readWhole (line 1) | async readWhole(){this.chunked=!1,this.fs=await mt;let e=await this.fs.r...
  method readChunked (line 1) | async readChunked(){this.chunked=!0,this.fs=await mt,await this.open(),a...
  method open (line 1) | async open(){void 0===this.fh&&(this.fh=await this.fs.open(this.input,"r...
  method _readChunk (line 1) | async _readChunk(e,t){void 0===this.fh&&await this.open(),e+t>this.size&...
  method close (line 1) | async close(){if(this.fh){let e=this.fh;this.fh=void 0,await e.close()}}
  method constructor (line 1) | constructor(...e){super(...e),this.input=this.input.replace(/^data:([^;]...
  method _readChunk (line 1) | async _readChunk(e,t){let i,n,s=this.input;void 0===e?(e=0,i=0,n=0):(i=4...
  class St (line 1) | class St extends pe{static canHandle(e,t){return 18761===t||19789===t}ex...
    method canHandle (line 1) | static canHandle(e,t){return 18761===t||19789===t}
    method extendOptions (line 1) | extendOptions(e){let{ifd0:t,xmp:i,iptc:n,icc:s}=e;i.enabled&&t.deps.ad...
    method parse (line 1) | async parse(){let{tiff:e,xmp:t,iptc:i,icc:n}=this.options;if(e.enabled...
    method adaptTiffPropAsSegment (line 1) | adaptTiffPropAsSegment(e){if(this.parsers.tiff[e]){let t=this.parsers....
  class Tt (line 1) | class Tt extends pe{constructor(...e){super(...e),f(this,"catchError",(e...
    method constructor (line 1) | constructor(...e){super(...e),f(this,"catchError",(e=>this.errors.push...
    method canHandle (line 1) | static canHandle(e,t){return 35152===t&&2303741511===e.getUint32(0)&&2...
    method parse (line 1) | async parse(){let{file:e}=this;await this.findPngChunksInRange("‰PNG\r...
    method findPngChunksInRange (line 1) | async findPngChunksInRange(e,t){let{file:i}=this;for(;e<t;){let t=i.ge...
    method parseTextChunks (line 1) | parseTextChunks(){let e=this.metaChunks.filter((e=>e.type===It));for(l...
    method injectKeyValToIhdr (line 1) | injectKeyValToIhdr(e,t){let i=this.parsers.ihdr;i&&i.raw.set(e,t)}
    method findIhdr (line 1) | findIhdr(){let e=this.metaChunks.find((e=>e.type===bt));e&&!1!==this.o...
    method findExif (line 1) | async findExif(){let e=this.metaChunks.find((e=>"exif"===e.type));e&&t...
    method findXmp (line 1) | async findXmp(){let e=this.metaChunks.filter((e=>e.type===kt));for(let...
    method findIcc (line 1) | async findIcc(){let e=this.metaChunks.find((e=>e.type===Pt));if(!e)ret...
  class Dt (line 1) | class Dt extends ge{static canHandle(e,t){return 224===e.getUint8(t+1)&&...
    method canHandle (line 1) | static canHandle(e,t){return 224===e.getUint8(t+1)&&1246120262===e.get...
    method parse (line 1) | parse(){return this.parseTags(),this.translate(),this.output}
    method parseTags (line 1) | parseTags(){this.raw=new Map([[0,this.chunk.getUint16(0)],[2,this.chun...
  class Ot (line 1) | class Ot extends ge{parse(){return this.parseTags(),this.translate(),thi...
    method parse (line 1) | parse(){return this.parseTags(),this.translate(),this.output}
    method parseTags (line 1) | parseTags(){this.raw=new Map([[0,this.chunk.getUint32(0)],[4,this.chun...
  class vt (line 1) | class vt extends ge{static canHandle(e,t){return 226===e.getUint8(t+1)&&...
    method canHandle (line 1) | static canHandle(e,t){return 226===e.getUint8(t+1)&&1229144927===e.get...
    method findPosition (line 1) | static findPosition(e,t){let i=super.findPosition(e,t);return i.chunkN...
    method handleMultiSegments (line 1) | static handleMultiSegments(e){return function(e){let t=function(e){let...
    method parse (line 1) | parse(){return this.raw=new Map,this.parseHeader(),this.parseTags(),th...
    method parseHeader (line 1) | parseHeader(){let{raw:e}=this;this.chunk.byteLength<84&&m("ICC header ...
    method parseTags (line 1) | parseTags(){let e,t,i,n,s,{raw:r}=this,a=this.chunk.getUint32(128),o=1...
    method parseTag (line 1) | parseTag(e,t,i){switch(e){case"desc":return this.parseDesc(t);case"mlu...
    method parseDesc (line 1) | parseDesc(e){let t=this.chunk.getUint32(e+8)-1;return S(this.chunk.get...
    method parseText (line 1) | parseText(e,t){return S(this.chunk.getString(e+8,t-8))}
    method parseSig (line 1) | parseSig(e){return S(this.chunk.getString(e+8,4))}
    method parseMluc (line 1) | parseMluc(e){let{chunk:t}=this,i=t.getUint32(e+8),n=t.getUint32(e+12),...
    method translateValue (line 1) | translateValue(e,t){return"string"==typeof e?t[e]||t[e.toLowerCase()]|...
  function Rt (line 1) | function Rt(e,t){return S(e.getString(t,4))}
  class Ft (line 1) | class Ft extends ge{static canHandle(e,t,i){return 237===e.getUint8(t+1)...
    method canHandle (line 1) | static canHandle(e,t,i){return 237===e.getUint8(t+1)&&"Photoshop"===e....
    method headerLength (line 1) | static headerLength(e,t,i){let n,s=this.containsIptc8bim(e,t,i);if(voi...
    method containsIptc8bim (line 1) | static containsIptc8bim(e,t,i){for(let n=0;n<i;n++)if(this.isIptcSegme...
    method isIptcSegmentHead (line 1) | static isIptcSegmentHead(e,t){return 56===e.getUint8(t)&&943868237===e...
    method parse (line 1) | parse(){let{raw:e}=this,t=this.chunk.byteLength-1,i=!1;for(let n=0;n<t...
    method pluralizeValue (line 1) | pluralizeValue(e,t){return void 0!==e?e instanceof Array?(e.push(t),e)...

FILE: javascript/extensions.js
  function extensions_apply (line 1) | function extensions_apply(extensions_disabled_list, extensions_update_li...
  function extensions_check (line 13) | function extensions_check(info, extensions_disabled_list, search_text, s...
  function install_extension (line 23) | function install_extension(button, url) {
  function uninstall_extension (line 34) | function uninstall_extension(button, url) {
  function update_extension (line 45) | function update_extension(button, url) {

FILE: javascript/extraNetworks.js
  function showCardDetails (line 60) | function showCardDetails(event) {
  function getCardDetails (line 69) | function getCardDetails(...args) {
  function readCardTags (line 77) | function readCardTags(el, tags) {
  function readCardDescription (line 109) | function readCardDescription(page, item) {
  function getCardsForActivePage (line 121) | function getCardsForActivePage() {
  function filterExtraNetworksForTab (line 130) | async function filterExtraNetworksForTab(searchTerm) {
  function tryToRemoveExtraNetworkFromPrompt (line 216) | function tryToRemoveExtraNetworkFromPrompt(textarea, text) {
  function sortExtraNetworks (line 248) | function sortExtraNetworks(fixed = 'no') {
  function refreshENInput (line 282) | function refreshENInput(tabName) {
  function markSelectedCards (line 287) | async function markSelectedCards(selected, page = '') {
  function extractLoraNames (line 296) | function extractLoraNames(prompt) {
  function cardClicked (line 304) | function cardClicked(textToAdd) {
  function extraNetworksSearchButton (line 314) | function extraNetworksSearchButton(event) {
  function extraNetworksFilterVersion (line 327) | function extraNetworksFilterVersion(event) {
  function selectStyle (line 348) | function selectStyle(name) {
  function applyStyles (line 355) | function applyStyles(styles) {
  function quickApplyStyle (line 371) | function quickApplyStyle() {
  function quickSaveStyle (line 377) | function quickSaveStyle() {
  function selectHistory (line 388) | function selectHistory(id) {
  function closeDetailsEN (line 396) | function closeDetailsEN(...args) {
  function refeshDetailsEN (line 407) | function refeshDetailsEN(args) {
  function refreshENpage (line 417) | function refreshENpage() {
  function setupExtraNetworksForTab (line 427) | function setupExtraNetworksForTab(tabName) {
  function showNetworks (line 599) | async function showNetworks() {
  function setupExtraNetworks (line 607) | async function setupExtraNetworks() {

FILE: javascript/gallery.js
  constant SUPPORTED_EXTENSIONS (line 27) | const SUPPORTED_EXTENSIONS = ['jpg', 'jpeg', 'png', 'webp', 'tiff', 'jp2...
  function getVisibleGalleryFiles (line 29) | function getVisibleGalleryFiles() {
  function updateGallerySelectionClasses (line 34) | function updateGallerySelectionClasses(files = gallerySelection.files, i...
  function refreshGallerySelection (line 40) | function refreshGallerySelection() {
  function resetGallerySelection (line 48) | function resetGallerySelection() {
  function applyGallerySelection (line 54) | function applyGallerySelection(index, { send = true } = {}) {
  function setGallerySelectionByElement (line 69) | function setGallerySelectionByElement(element, options) {
  function buildGalleryFileUrl (line 79) | function buildGalleryFileUrl(path) {
  function awaitForOutstanding (line 92) | async function awaitForOutstanding(num, signal) {
  function awaitForGallery (line 102) | async function awaitForGallery(expectedSize, signal) {
  function updateGalleryStyles (line 107) | function updateGalleryStyles() {
  class SimpleProgressBar (line 177) | class SimpleProgressBar {
    method constructor (line 189) | constructor(monitoredSet) {
    method start (line 201) | start(total) {
    method attachTo (line 209) | attachTo(element) {
    method clear (line 216) | clear() {
    method #update (line 226) | #update(loaded, max) {
    method #stop (line 246) | #stop() {
  class SimpleFunctionQueue (line 255) | class SimpleFunctionQueue {
    method constructor (line 260) | constructor(id) {
    method abortLogger (line 266) | static abortLogger(identifier, result) {
    method enqueue (line 280) | enqueue(config) {
    method #tryRunNext (line 292) | async #tryRunNext() {
  class GalleryFolder (line 316) | class GalleryFolder extends HTMLElement {
    method constructor (line 321) | constructor(folder) {
    method connectedCallback (line 338) | connectedCallback() {
    method disconnectedCallback (line 353) | async disconnectedCallback() {
    method getActive (line 362) | static getActive() {
    method updateSelected (line 366) | updateSelected() {
  function delayFetchThumb (line 377) | async function delayFetchThumb(fn, signal) {
  class GalleryFile (line 398) | class GalleryFile extends HTMLElement {
    method constructor (line 402) | constructor(folder, file, signal) {
    method connectedCallback (line 421) | async connectedCallback() {
  function createThumb (line 514) | async function createThumb(img) {
  function handleSeparator (line 531) | async function handleSeparator(separator) {
  function addSeparators (line 558) | async function addSeparators() {
  function getHash (line 645) | async function getHash(str, algo = 'SHA-256') {
  function updateStatusWithSort (line 663) | function updateStatusWithSort(...messages) {
  function injectGalleryStatusCSS (line 688) | async function injectGalleryStatusCSS() {
  function wsConnect (line 722) | async function wsConnect(socket, timeout = 5000) {
  function gallerySearch (line 736) | async function gallerySearch() {
  function gallerySort (line 840) | async function gallerySort(btn) {
  function showCleaningMsg (line 962) | function showCleaningMsg(count, all = false) {
  function thumbCacheCleanup (line 995) | async function thumbCacheCleanup(folder, imgCount, controller, force = f...
  function resetGalleryState (line 1051) | function resetGalleryState(reason) {
  function clearCacheIfDisabled (line 1062) | function clearCacheIfDisabled(browser_cache) {
  function addCacheClearLabel (line 1090) | function addCacheClearLabel() { // Don't use async
  function fetchFilesHT (line 1121) | async function fetchFilesHT(evt, controller) {
  function fetchFilesWS (line 1156) | async function fetchFilesWS(evt) { // fetch file-by-file list over webso...
  function updateFolders (line 1224) | async function updateFolders() {
  function monitorGalleries (line 1237) | async function monitorGalleries() {
  function setOverlayAnimation (line 1258) | async function setOverlayAnimation() {
  function galleryClearInit (line 1265) | async function galleryClearInit() {
  function initGalleryAutoRefresh (line 1275) | async function initGalleryAutoRefresh() {
  function blockQueueUntilReady (line 1312) | async function blockQueueUntilReady() {
  function initGallery (line 1328) | async function initGallery() { // triggered on gradio change to monitor ...

FILE: javascript/generationParams.js
  function attachGalleryListeners (line 3) | function attachGalleryListeners(tabName) {
  function initiGenerationParams (line 22) | async function initiGenerationParams() {

FILE: javascript/gpu.js
  function updateGPUChart (line 4) | async function updateGPUChart(mem, load) {
  function updateGPU (line 29) | async function updateGPU() {
  function startGPU (line 60) | async function startGPU() {
  function disableGPU (line 70) | async function disableGPU() {

FILE: javascript/guidance.js
  function getGuidanceDocs (line 15) | function getGuidanceDocs(guider) {

FILE: javascript/hires.js
  function onCalcResolutionHires (line 1) | function onCalcResolutionHires(width, height, hr_scale, hr_resize_x, hr_...

FILE: javascript/history.js
  function refreshHistory (line 4) | function refreshHistory() {

FILE: javascript/imageParams.js
  function initDragDrop (line 1) | async function initDragDrop() {

FILE: javascript/imageViewer.js
  function cycleImageFit (line 6) | function cycleImageFit() {
  function isInViewport (line 18) | function isInViewport(element) {
  function closeModal (line 23) | function closeModal(evt, force = false) {
  function modalImageSwitch (line 34) | function modalImageSwitch(offset) {
  function modalSaveImage (line 70) | function modalSaveImage(event) {
  function modalKeyHandler (line 78) | function modalKeyHandler(event) {
  function getExif (line 97) | async function getExif(el) {
  function displayExif (line 128) | async function displayExif(el) {
  function showModal (line 134) | function showModal(event) {
  function modalDownloadImage (line 151) | function modalDownloadImage() {
  function modalZoomSet (line 164) | function modalZoomSet(modalImage, enable) {
  function setupImageForLightbox (line 169) | function setupImageForLightbox(image) {
  function modalZoomToggle (line 176) | function modalZoomToggle(event) {
  function modalTileToggle (line 183) | function modalTileToggle(event) {
  function modalResetInstance (line 198) | function modalResetInstance(event) {
  function modalToggleParams (line 206) | function modalToggleParams(event) {
  function galleryClickEventHandler (line 217) | function galleryClickEventHandler(event) {
  function bindImageViewer (line 227) | async function bindImageViewer() {
  function initImageViewer (line 237) | async function initImageViewer() {

FILE: javascript/indexdb.js
  function initIndexDB (line 6) | async function initIndexDB() {
  function idbIsReady (line 39) | function idbIsReady() {
  function configureTransactionAbort (line 53) | function configureTransactionAbort({ transaction, signal, resolve, rejec...
  function add (line 74) | async function add(record) {
  function del (line 86) | async function del(hash) {
  function get (line 98) | async function get(hash) {
  function put (line 110) | async function put(record) {
  function idbGetAllKeys (line 122) | async function idbGetAllKeys(index = null, query = null) {
  function idbCount (line 150) | async function idbCount(folder) {
  function idbFolderCleanup (line 179) | async function idbFolderCleanup(keepSet, folder, signal) {
  function idbClearAll (line 196) | async function idbClearAll(signal) {

FILE: javascript/inputAccordion.js
  function inputAccordionChecked (line 1) | function inputAccordionChecked(id, checked) {
  function setupAccordion (line 7) | function setupAccordion(accordion) {
  function initAccordions (line 53) | function initAccordions() {

FILE: javascript/loader.js
  function preloadImages (line 3) | async function preloadImages() {
  function removeSplash (line 29) | async function removeSplash() {
  function createSplash (line 38) | async function createSplash() {

FILE: javascript/logMonitor.js
  function dateToStr (line 7) | function dateToStr(ts) {
  function htmlEscape (line 20) | function htmlEscape(text) {
  function logMonitor (line 24) | async function logMonitor() {
  function initLogMonitor (line 102) | async function initLogMonitor() {

FILE: javascript/logger.js
  function xhrPost (line 82) | function xhrPost(url, data, handler = undefined, errorHandler = undefine...

FILE: javascript/login.js
  function forceLogin (line 25) | function forceLogin() {
  function loginCheck (line 63) | function loginCheck() {

FILE: javascript/monitor.js
  class ConnectionMonitorState (line 1) | class ConnectionMonitorState {
    method getModel (line 8) | static getModel() {
    method trimModelName (line 13) | static trimModelName(name) {
    method setData (line 18) | static setData({ online, updated, commit, branch }) {
    method setElement (line 25) | static setElement(el) {
    method toHTML (line 29) | static toHTML(modelOverride) {
    method updateState (line 40) | static updateState(incomingModel) {
  function updateIndicator (line 48) | async function updateIndicator(online, data, msg) {
  function monitorConnection (line 65) | async function monitorConnection() {

FILE: javascript/notification.js
  function sendNotification (line 6) | async function sendNotification() {

FILE: javascript/panZoom.js
  function r (line 1) | function r(e,n,t){function o(i,f){if(!n[i]){if(!e[i]){var c="function"==...
  function createPanZoom (line 28) | function createPanZoom(domElement, options) {
  function parseTransformOrigin (line 893) | function parseTransformOrigin(options) {
  function failTransformOrigin (line 904) | function failTransformOrigin(options) {
  function noop (line 917) | function noop() { }
  function validateBounds (line 919) | function validateBounds(bounds) {
  function isNumber (line 936) | function isNumber(x) {
  function isNaN (line 941) | function isNaN(value) {
  function rigidScroll (line 949) | function rigidScroll() {
  function autoRun (line 957) | function autoRun() {
  function createTextSelectionInterceptor (line 1036) | function createTextSelectionInterceptor(useFake) {
  function disabled (line 1074) | function disabled(e) {
  function noop (line 1079) | function noop() {}
  function makeDomController (line 1086) | function makeDomController(domElement, options) {
  function isDomElement (line 1131) | function isDomElement(element) {
  function kinetic (line 1141) | function kinetic(getPoint, scroll, settings) {
  function getCancelAnimationFrame (line 1260) | function getCancelAnimationFrame() {
  function getRequestAnimationFrame (line 1265) | function getRequestAnimationFrame() {
  function makeSvgController (line 1276) | function makeSvgController(svgElement, options) {
  function isSVGElement (line 1349) | function isSVGElement(element) {
  function Transform (line 1355) | function Transform() {
  function animate (line 1379) | function animate(source, target, options) {
  function noop (line 1441) | function noop() { }
  function getScheduler (line 1443) | function getScheduler(scheduler) {
  function rafScheduler (line 1454) | function rafScheduler() {
  function timeoutScheduler (line 1461) | function timeoutScheduler() {
  function makeAggregateRaf (line 1472) | function makeAggregateRaf() {
  function A (line 1535) | function A (aA1, aA2) { return 1.0 - 3.0 * aA2 + 3.0 * aA1; }
  function B (line 1536) | function B (aA1, aA2) { return 3.0 * aA2 - 6.0 * aA1; }
  function C (line 1537) | function C (aA1)      { return 3.0 * aA1; }
  function calcBezier (line 1540) | function calcBezier (aT, aA1, aA2) { return ((A(aA1, aA2) * aT + B(aA1, ...
  function getSlope (line 1543) | function getSlope (aT, aA1, aA2) { return 3.0 * A(aA1, aA2) * aT * aT + ...
  function binarySubdivide (line 1545) | function binarySubdivide (aX, aA, aB, mX1, mX2) {
  function newtonRaphsonIterate (line 1559) | function newtonRaphsonIterate (aX, aGuessT, mX1, mX2) {
  function LinearEasing (line 1571) | function LinearEasing (x) {
  function getTForX (line 1590) | function getTForX (aX) {
  function createEventsStorage (line 1637) | function createEventsStorage(subject) {
  function validateSubject (line 1704) | function validateSubject(subject) {
  function addWheelListener (line 1736) | function addWheelListener(element, listener, useCapture) {
  function removeWheelListener (line 1740) | function removeWheelListener( element, listener, useCapture ) {

FILE: javascript/progressBar.js
  function setRefreshInterval (line 4) | function setRefreshInterval() {
  function pad2 (line 14) | function pad2(x) {
  function formatTime (line 18) | function formatTime(secs) {
  function checkPaused (line 24) | function checkPaused(state) {
  function setProgress (line 36) | function setProgress(res) {
  function requestInterrupt (line 73) | function requestInterrupt() {
  function randomId (line 77) | function randomId() {
  function requestProgress (line 83) | function requestProgress(id_task, progressEl, galleryEl, atEnd = null, o...

FILE: javascript/promptChecker.js
  function checkBrackets (line 6) | function checkBrackets(textArea, counterElt) {
  function setupBracketChecking (line 22) | function setupBracketChecking(idPrompt, idCounter) {
  function initPromptChecker (line 29) | async function initPromptChecker() {

FILE: javascript/script.js
  function sleep (line 1) | async function sleep(ms) {
  function gradioApp (line 5) | function gradioApp() {
  function logFn (line 12) | function logFn(func) {
  function getUICurrentTab (line 22) | function getUICurrentTab() {
  function getUICurrentTabContent (line 26) | function getUICurrentTabContent() {
  function onAfterUiUpdate (line 41) | function onAfterUiUpdate(callback) {
  function onUiUpdate (line 45) | function onUiUpdate(callback) {
  function onUiLoaded (line 49) | function onUiLoaded(callback) {
  function onUiReady (line 53) | function onUiReady(callback) {
  function onUiTabChange (line 57) | function onUiTabChange(callback) {
  function onOptionsChanged (line 61) | function onOptionsChanged(callback) {
  function executeCallbacks (line 65) | function executeCallbacks(queue, arg) {
  function scheduleAfterUiUpdateCallbacks (line 79) | function scheduleAfterUiUpdateCallbacks() {
  function mutationCallback (line 90) | async function mutationCallback(mutations) {
  function uiElementIsVisible (line 149) | function uiElementIsVisible(el) {
  function uiElementInSight (line 157) | function uiElementInSight(el) {

FILE: javascript/setHints.js
  function cycleLocale (line 19) | async function cycleLocale() {
  function resetLocale (line 35) | async function resetLocale() {
  function tooltipCreate (line 48) | async function tooltipCreate() {
  function expandTooltip (line 79) | async function expandTooltip(element, longHint) {
  function tooltipShowDelegated (line 91) | async function tooltipShowDelegated(e) { // use event delegation to hand...
  function tooltipHideDelegated (line 95) | async function tooltipHideDelegated(e) {
  function tooltipShow (line 99) | async function tooltipShow(e) {
  function tooltipHide (line 162) | async function tooltipHide(e) {
  function validateHints (line 171) | async function validateHints(json, elements, tab) {
  function addMissingHints (line 195) | async function addMissingHints(json, missingHints) {
  function removeOrphanedHints (line 206) | async function removeOrphanedHints(json, orphanedHints) {
  function replaceButtonText (line 213) | async function replaceButtonText(el) {
  function getLocaleData (line 232) | async function getLocaleData(desiredLocale = null) {
  function replaceTextContent (line 267) | async function replaceTextContent(el, text) {
  function setHint (line 280) | async function setHint(el, entry) {
  function setHints (line 292) | async function setHints(analyze = false) {
  function applyHintToElement (line 354) | async function applyHintToElement(el) {
  function initializeDOMObserver (line 377) | function initializeDOMObserver() {

FILE: javascript/settings.js
  function getSettingsTabs (line 5) | function getSettingsTabs() {
  function monitorOption (line 14) | function monitorOption(option, callback) {
  function updateOpts (line 24) | async function updateOpts(json_string) {
  function showAllSettings (line 56) | function showAllSettings() {
  function markIfModified (line 66) | function markIfModified(setting_name, value) {
  function updateAllOpts (line 100) | function updateAllOpts() {
  method set (line 120) | set(newValue) {
  method get (line 127) | get() {
  function initModels (line 159) | async function initModels() {
  function initSettings (line 193) | async function initSettings() {

FILE: javascript/startup.js
  function waitForOpts (line 5) | async function waitForOpts() {
  function initStartup (line 26) | async function initStartup() {

FILE: javascript/timesheet.js
  class Bubble (line 3) | class Bubble {
    method constructor (line 4) | constructor(min, start, end, label, scale, type) {
    method getDateLabel (line 17) | getDateLabel() {
  class Timesheet (line 22) | class Timesheet {
    method constructor (line 23) | constructor(container, data) {

FILE: javascript/trainMonitor.js
  function startTrainMonitor (line 1) | function startTrainMonitor() {

FILE: javascript/ui.js
  function rememberGallerySelection (line 13) | function rememberGallerySelection(name) {
  function set_theme (line 17) | function set_theme(theme) {
  function update_token_counter (line 22) | function update_token_counter(button_id) {
  function clip_gallery_urls (line 27) | function clip_gallery_urls(gallery) {
  function isVisible (line 35) | function isVisible(el) {
  function all_gallery_buttons (line 42) | function all_gallery_buttons() {
  function selected_gallery_button (line 52) | function selected_gallery_button() {
  function selected_gallery_index (line 62) | function selected_gallery_index() {
  function selected_gallery_files (line 74) | function selected_gallery_files(tabname) {
  function extract_image_from_gallery (line 95) | function extract_image_from_gallery(gallery) {
  function send_to_kanvas (line 103) | function send_to_kanvas(gallery) {
  function setTheme (line 113) | async function setTheme(val, old) {
  function setFontSize (line 134) | function setFontSize(val, old) {
  function switchToTab (line 149) | function switchToTab(tab) {
  function switch_to_txt2img (line 156) | function switch_to_txt2img(...args) {
  function switch_to_img2img_tab (line 161) | function switch_to_img2img_tab(no) {
  function switch_to_img2img (line 166) | function switch_to_img2img(...args) {
  function switch_to_inpaint (line 172) | function switch_to_inpaint(...args) {
  function switch_to_sketch (line 178) | function switch_to_sketch(...args) {
  function switch_to_composite (line 184) | function switch_to_composite(...args) {
  function switch_to_extras (line 190) | function switch_to_extras(...args) {
  function switch_to_control (line 195) | function switch_to_control(...args) {
  function switch_to_video (line 200) | function switch_to_video(...args) {
  function switch_to_caption (line 205) | function switch_to_caption(...args) {
  function get_tab_index (line 210) | function get_tab_index(tabId) {
  function create_tab_index_args (line 219) | function create_tab_index_args(tabId, args) {
  function get_img2img_tab_index (line 225) | function get_img2img_tab_index(...args) {
  function create_submit_args (line 232) | function create_submit_args(args) {
  function showSubmitButtons (line 238) | function showSubmitButtons(tabname, show) {}
  function clearGallery (line 240) | function clearGallery(tabname) {
  function submit_txt2img (line 248) | function submit_txt2img(...args) {
  function submit_img2img (line 260) | function submit_img2img(...args) {
  function submit_control (line 273) | function submit_control(...args) {
  function submit_video (line 291) | function submit_video(...args) {
  function submit_framepack (line 303) | function submit_framepack(...args) {
  function submit_ltx (line 312) | function submit_ltx(...args) {
  function submit_video_wrapper (line 321) | function submit_video_wrapper(...args) {
  function submit_postprocessing (line 330) | function submit_postprocessing(...args) {
  function modelmerger (line 339) | function modelmerger(...args) {
  function clearPrompts (line 346) | function clearPrompts(prompt, negative_prompt) {
  function recalculatePromptTokens (line 354) | function recalculatePromptTokens(name) {
  function recalculate_prompts_txt2img (line 360) | function recalculate_prompts_txt2img(...args) {
  function recalculate_prompts_img2img (line 366) | function recalculate_prompts_img2img(...args) {
  function recalculate_prompts_inpaint (line 372) | function recalculate_prompts_inpaint(...args) {
  function recalculate_prompts_control (line 378) | function recalculate_prompts_control(...args) {
  function registerDragDrop (line 384) | function registerDragDrop() {
  function sortUIElements (line 400) | function sortUIElements() {
  function registerTextarea (line 431) | async function registerTextarea(id, id_counter, id_button) {
  function update_txt2img_tokens (line 455) | function update_txt2img_tokens(...args) {
  function update_img2img_tokens (line 461) | function update_img2img_tokens(...args) {
  function getTranslation (line 467) | function getTranslation(...args) {
  function monitorServerStatus (line 471) | function monitorServerStatus() {
  function restartReload (line 492) | function restartReload() {
  function updateInput (line 501) | function updateInput(target) {
  function selectCheckpoint (line 508) | function selectCheckpoint(name) {
  function selectVAE (line 520) | function selectVAE(name) {
  function selectReference (line 527) | function selectReference(name) {
  function currentImageResolutionimg2img (line 534) | function currentImageResolutionimg2img(_a, _b, scaleBy) {
  function currentImageResolutioncontrol (line 539) | function currentImageResolutioncontrol(_a, _b, scaleBy) {
  function updateImg2imgResizeToTextAfterChangingImage (line 544) | function updateImg2imgResizeToTextAfterChangingImage() {
  function createThemeElement (line 550) | function createThemeElement() {
  function toggleCompact (line 559) | function toggleCompact(val, old) {
  function previewTheme (line 575) | function previewTheme() {
  function browseFolder (line 596) | async function browseFolder() {
  function reconnectUI (line 602) | async function reconnectUI() {

FILE: javascript/uiConfig.js
  function uiOpenSubmenus (line 1) | function uiOpenSubmenus() {
  function getUIDefaults (line 13) | async function getUIDefaults() {

FILE: launch.py
  function init_args (line 36) | def init_args():
  function init_paths (line 45) | def init_paths():
  function get_custom_args (line 54) | def get_custom_args():
  function commit_hash (line 76) | def commit_hash(): # compatbility function
  function run (line 89) | def run(command, desc=None, errdesc=None, custom_env=None, live=False): ...
  function check_run (line 106) | def check_run(command): # compatbility function
  function is_installed (line 112) | def is_installed(pkg): # compatbility function
  function repo_dir (line 117) | def repo_dir(name): # compatbility function
  function run_python (line 122) | def run_python(code, desc=None, errdesc=None): # compatbility function
  function run_pip (line 127) | def run_pip(pkg, desc=None): # compatbility function
  function check_run_python (line 140) | def check_run_python(code): # compatbility function
  function git_clone (line 144) | def git_clone(url, tgt, _name, commithash=None): # compatbility function
  function run_extension_installer (line 148) | def run_extension_installer(ext_dir): # compatbility function
  function get_memory_stats (line 152) | def get_memory_stats(detailed:bool=False):
  function clean_server (line 162) | def clean_server():
  function start_server (line 191) | def start_server(immediate=True, server=None):
  function main (line 229) | def main():

FILE: modules/apg/__init__.py
  class MomentumBuffer (line 10) | class MomentumBuffer:
    method __init__ (line 11) | def __init__(self, momentum_val: float):
    method update (line 14) | def update(self, update_value: torch.Tensor):
  function project (line 26) | def project(
  function normalized_guidance (line 41) | def normalized_guidance(

FILE: modules/apg/pipeline_stable_cascade_prior_apg.py
  class StableCascadePriorPipelineOutput (line 53) | class StableCascadePriorPipelineOutput(BaseOutput):
  class StableCascadePriorPipelineAPG (line 73) | class StableCascadePriorPipelineAPG(DiffusionPipeline):
    method __init__ (line 105) | def __init__(
    method prepare_latents (line 126) | def prepare_latents(
    method encode_prompt (line 146) | def encode_prompt(
    method encode_image (line 253) | def encode_image(self, images, device, dtype, batch_size, num_images_p...
    method check_inputs (line 267) | def check_inputs(
    method guidance_scale (line 345) | def guidance_scale(self):
    method do_classifier_free_guidance (line 349) | def do_classifier_free_guidance(self):
    method num_timesteps (line 353) | def num_timesteps(self):
    method get_timestep_ratio_conditioning (line 356) | def get_timestep_ratio_conditioning(self, t, alphas_cumprod):
    method __call__ (line 368) | def __call__(

FILE: modules/apg/pipeline_stable_diffision_xl_apg.py
  function rescale_noise_cfg (line 62) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 77) | def retrieve_timesteps(
  class StableDiffusionXLPipelineAPG (line 136) | class StableDiffusionXLPipelineAPG(
    method __init__ (line 208) | def __init__(
    method encode_prompt (line 248) | def encode_prompt(
    method encode_image (line 483) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 508) | def prepare_ip_adapter_image_embeds(
    method prepare_extra_step_kwargs (line 554) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 571) | def check_inputs(
    method prepare_latents (line 668) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 690) | def _get_add_time_ids(
    method upcast_vae (line 708) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 727) | def get_guidance_scale_embedding(
    method guidance_scale (line 758) | def guidance_scale(self):
    method guidance_rescale (line 762) | def guidance_rescale(self):
    method clip_skip (line 766) | def clip_skip(self):
    method do_classifier_free_guidance (line 773) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 777) | def cross_attention_kwargs(self):
    method denoising_end (line 781) | def denoising_end(self):
    method num_timesteps (line 785) | def num_timesteps(self):
    method interrupt (line 789) | def interrupt(self):
    method __call__ (line 794) | def __call__(

FILE: modules/apg/pipeline_stable_diffusion_apg.py
  function rescale_noise_cfg (line 58) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 72) | def retrieve_timesteps(
  class StableDiffusionPipelineAPG (line 131) | class StableDiffusionPipelineAPG(
    method __init__ (line 177) | def __init__(
    method _encode_prompt (line 269) | def _encode_prompt(
    method encode_prompt (line 301) | def encode_prompt(
    method encode_image (line 483) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 507) | def prepare_ip_adapter_image_embeds(
    method run_safety_checker (line 552) | def run_safety_checker(self, image, device, dtype):
    method decode_latents (line 566) | def decode_latents(self, latents):
    method prepare_extra_step_kwargs (line 577) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 594) | def check_inputs(
    method prepare_latents (line 663) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method get_guidance_scale_embedding (line 686) | def get_guidance_scale_embedding(
    method guidance_scale (line 717) | def guidance_scale(self):
    method guidance_rescale (line 721) | def guidance_rescale(self):
    method clip_skip (line 725) | def clip_skip(self):
    method do_classifier_free_guidance (line 732) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 736) | def cross_attention_kwargs(self):
    method num_timesteps (line 740) | def num_timesteps(self):
    method interrupt (line 744) | def interrupt(self):
    method __call__ (line 749) | def __call__(

FILE: modules/api/api.py
  class Api (line 14) | class Api:
    method __init__ (line 15) | def __init__(self, app: FastAPI, queue_lock: Lock):
    method register (line 39) | def register(self):
    method add_api_route (line 128) | def add_api_route(self, path: str, fn, auth: bool = True, **kwargs):
    method auth (line 137) | def auth(self, credentials: HTTPBasicCredentials = Depends(HTTPBasic())):
    method get_session_start (line 149) | def get_session_start(self, req: Request, agent: Optional[str] = None):
    method launch (line 155) | def launch(self):

FILE: modules/api/control.py
  class ItemControl (line 12) | class ItemControl(BaseModel):
  class ItemXYZ (line 21) | class ItemXYZ(BaseModel):
  class ResControl (line 57) | class ResControl(BaseModel):
  class APIControl (line 64) | class APIControl():
    method __init__ (line 65) | def __init__(self, queue_lock: Lock):
    method sanitize_args (line 70) | def sanitize_args(self, args: dict):
    method sanitize_b64 (line 82) | def sanitize_b64(self, request):
    method prepare_face_module (line 97) | def prepare_face_module(self, req):
    method prepare_xyz_grid (line 118) | def prepare_xyz_grid(self, req):
    method prepare_ip_adapter (line 133) | def prepare_ip_adapter(self, request):
    method prepare_control (line 153) | def prepare_control(self, req):
    method post_control (line 185) | def post_control(self, req: ReqControl):

FILE: modules/api/docs.py
  function get_swagger_ui_html (line 8) | def get_swagger_ui_html(*,
  function create_docs (line 59) | def create_docs(app: FastAPI):
  function create_redocs (line 83) | def create_redocs(app: FastAPI):

FILE: modules/api/endpoints.py
  function get_samplers (line 8) | def get_samplers():
  function get_sampler (line 20) | def get_sampler():
  function get_sd_vaes (line 32) | def get_sd_vaes():
  function get_upscalers (line 36) | def get_upscalers():
  function get_sd_models (line 39) | def get_sd_models():
  function get_controlnets (line 47) | def get_controlnets(model_type: Optional[str] = None):
  function get_restorers (line 51) | def get_restorers():
  function get_detailers (line 54) | def get_detailers():
  function get_prompt_styles (line 58) | def get_prompt_styles():
  function get_embeddings (line 61) | def get_embeddings():
  function get_extra_networks (line 67) | def get_extra_networks(page: Optional[str] = None, name: Optional[str] =...
  function get_interrogate (line 94) | def get_interrogate():
  function get_schedulers (line 98) | def get_schedulers():
  function post_interrogate (line 105) | def post_interrogate(req: models.ReqInterrogate):
  function post_vqa (line 128) | def post_vqa(req: models.ReqVQA):
  function post_unload_checkpoint (line 137) | def post_unload_checkpoint():
  function post_reload_checkpoint (line 143) | def post_reload_checkpoint(force:bool=False):
  function post_lock_checkpoint (line 150) | def post_lock_checkpoint(lock:bool=False):
  function get_checkpoint (line 155) | def get_checkpoint():
  function set_checkpoint (line 175) | def set_checkpoint(sd_model_checkpoint: str, dtype:str=None, force:bool=...
  function post_refresh_checkpoints (line 186) | def post_refresh_checkpoints():
  function post_refresh_vae (line 190) | def post_refresh_vae():
  function get_modules (line 194) | def get_modules():
  function get_extensions_list (line 218) | def get_extensions_list():
  function post_pnginfo (line 237) | def post_pnginfo(req: models.ReqImageInfo):
  function get_latent_history (line 251) | def get_latent_history():
  function post_latent_history (line 254) | def post_latent_history(req: models.ReqLatentHistory):

FILE: modules/api/gallery.py
  class ReqFiles (line 36) | class ReqFiles(BaseModel):
  class ConnectionManager (line 41) | class ConnectionManager:
    method __init__ (line 42) | def __init__(self):
    method connect (line 45) | async def connect(self, ws: WebSocket):
    method disconnect (line 51) | def disconnect(self, ws: WebSocket):
    method send (line 55) | async def send(self, ws: WebSocket, data: Union[str, dict, bytes]):
    method broadcast (line 68) | async def broadcast(self, data: Union[str, dict, bytes]):
  function register_api (line 74) | def register_api(app: FastAPI): # register api

FILE: modules/api/generate.py
  class APIGenerate (line 12) | class APIGenerate():
    method __init__ (line 13) | def __init__(self, queue_lock: Lock):
    method sanitize_args (line 19) | def sanitize_args(self, args: dict):
    method sanitize_b64 (line 30) | def sanitize_b64(self, request):
    method prepare_face_module (line 44) | def prepare_face_module(self, request):
    method prepare_ip_adapter (line 65) | def prepare_ip_adapter(self, request, p):
    method post_text2img (line 87) | def post_text2img(self, txt2imgreq: models.ReqTxt2Img):
    method post_img2img (line 131) | def post_img2img(self, img2imgreq: models.ReqImg2Img):

FILE: modules/api/gpu.py
  function get_gpu_status (line 8) | def get_gpu_status():

FILE: modules/api/helpers.py
  function validate_sampler_name (line 10) | def validate_sampler_name(name):
  function decode_base64_to_image (line 17) | def decode_base64_to_image(encoding, quiet=False):
  function encode_pil_to_base64 (line 36) | def encode_pil_to_base64(image):
  function upscaler_to_index (line 52) | def upscaler_to_index(name: str):
  function save_image (line 58) | def save_image(image, fn, ext):

FILE: modules/api/loras.py
  function get_lora (line 5) | def get_lora(lora: str) -> dict:
  function get_loras (line 13) | def get_loras():
  function post_refresh_loras (line 20) | def post_refresh_loras():
  function register_api (line 25) | def register_api():

FILE: modules/api/middleware.py
  function setup_middleware (line 27) | def setup_middleware(app: FastAPI, cmd_opts):

FILE: modules/api/mime.py
  function register (line 4) | def register():

FILE: modules/api/models.py
  class ModelDef (line 16) | class ModelDef(BaseModel):
  class DummyConfig (line 24) | class DummyConfig:
  class PydanticModelGenerator (line 32) | class PydanticModelGenerator:
    method __init__ (line 33) | def __init__(
    method generate_model (line 75) | def generate_model(self):
  class ItemSampler (line 87) | class ItemSampler(BaseModel):
  class ItemVae (line 91) | class ItemVae(BaseModel):
  class ItemUpscaler (line 95) | class ItemUpscaler(BaseModel):
  class ItemModel (line 102) | class ItemModel(BaseModel):
  class ItemHypernetwork (line 111) | class ItemHypernetwork(BaseModel):
  class ItemDetailer (line 115) | class ItemDetailer(BaseModel):
  class ItemGAN (line 119) | class ItemGAN(BaseModel):
  class ItemStyle (line 124) | class ItemStyle(BaseModel):
  class ItemExtraNetwork (line 132) | class ItemExtraNetwork(BaseModel):
  class ItemArtist (line 141) | class ItemArtist(BaseModel):
  class ItemEmbedding (line 146) | class ItemEmbedding(BaseModel):
  class ItemIPAdapter (line 153) | class ItemIPAdapter(BaseModel):
  class ItemFace (line 162) | class ItemFace(BaseModel):
  class ScriptArg (line 178) | class ScriptArg(BaseModel):
  class ItemScript (line 186) | class ItemScript(BaseModel):
  class ItemExtension (line 192) | class ItemExtension(BaseModel):
  class ItemScheduler (line 201) | class ItemScheduler(BaseModel):
  class ResTxt2Img (line 229) | class ResTxt2Img(BaseModel):
  class ResImg2Img (line 259) | class ResImg2Img(BaseModel):
  class FileData (line 264) | class FileData(BaseModel):
  class ReqProcess (line 268) | class ReqProcess(BaseModel):
  class ResProcess (line 282) | class ResProcess(BaseModel):
  class ReqPromptEnhance (line 286) | class ReqPromptEnhance(BaseModel):
  class ResPromptEnhance (line 295) | class ResPromptEnhance(BaseModel):
  class ReqProcessImage (line 299) | class ReqProcessImage(ReqProcess):
  class ResProcessImage (line 302) | class ResProcessImage(ResProcess):
  class ReqProcessBatch (line 305) | class ReqProcessBatch(ReqProcess):
  class ResProcessBatch (line 308) | class ResProcessBatch(ResProcess):
  class ReqImageInfo (line 311) | class ReqImageInfo(BaseModel):
  class ResImageInfo (line 314) | class ResImageInfo(BaseModel):
  class ReqGetLog (line 319) | class ReqGetLog(BaseModel):
  class ReqPostLog (line 324) | class ReqPostLog(BaseModel):
  class ReqHistory (line 329) | class ReqHistory(BaseModel):
  class ReqProgress (line 332) | class ReqProgress(BaseModel):
  class ResProgress (line 335) | class ResProgress(BaseModel):
  class ResHistory (line 343) | class ResHistory(BaseModel):
  class ResStatus (line 351) | class ResStatus(BaseModel):
  class ReqInterrogate (line 368) | class ReqInterrogate(BaseModel):
  class ResInterrogate (line 375) | class ResInterrogate(BaseModel):
  class ReqVQA (line 383) | class ReqVQA(BaseModel):
  class ReqLatentHistory (line 389) | class ReqLatentHistory(BaseModel):
  class ResVQA (line 392) | class ResVQA(BaseModel):
  class ResTrain (line 395) | class ResTrain(BaseModel):
  class ResCreate (line 398) | class ResCreate(BaseModel):
  class ResPreprocess (line 401) | class ResPreprocess(BaseModel):
  class ResEmbeddings (line 429) | class ResEmbeddings(BaseModel):
  class ResMemory (line 433) | class ResMemory(BaseModel):
  class ResScripts (line 437) | class ResScripts(BaseModel):
  class ResGPU (line 442) | class ResGPU(BaseModel): # definition of http response
  function create_model_from_signature (line 449) | def create_model_from_signature(func: Callable, model_name: str, base_mo...

FILE: modules/api/nudenet.py
  function nudenet_censor (line 5) | def nudenet_censor(
  function prompt_check (line 25) | def prompt_check(
  function image_guard (line 40) | def image_guard(
  function banned_words (line 50) | def banned_words(
  function register_api (line 59) | def register_api():

FILE: modules/api/nvml.py
  function install (line 4) | def install(*args, **kwargs): # pylint: disable=unused-argument
  function warn_once (line 14) | def warn_once(msg):
  function get_reason (line 20) | def get_reason(val):
  function get_nvml (line 36) | def get_nvml():

FILE: modules/api/process.py
  class ReqPreprocess (line 15) | class ReqPreprocess(BaseModel):
  class ResPreprocess (line 20) | class ResPreprocess(BaseModel):
  class ReqMask (line 24) | class ReqMask(BaseModel):
  class ReqFace (line 31) | class ReqFace(BaseModel):
  class ResFace (line 35) | class ResFace(BaseModel):
  class ResMask (line 42) | class ResMask(BaseModel):
  class ItemPreprocess (line 45) | class ItemPreprocess(BaseModel):
  class ItemMask (line 49) | class ItemMask(BaseModel):
  class APIProcess (line 56) | class APIProcess():
    method __init__ (line 57) | def __init__(self, queue_lock: Lock):
    method get_preprocess (line 60) | def get_preprocess(self):
    method post_preprocess (line 67) | def post_preprocess(self, req: ReqPreprocess):
    method get_mask (line 86) | def get_mask(self):
    method post_mask (line 90) | def post_mask(self, req: ReqMask):
    method post_detect (line 115) | def post_detect(self, req: ReqFace):
    method post_prompt_enhance (line 135) | def post_prompt_enhance(self, req: models.ReqPromptEnhance):
    method set_upscalers (line 179) | def set_upscalers(self, req: dict):
    method extras_single_image_api (line 185) | def extras_single_image_api(self, req: models.ReqProcessImage):
    method extras_batch_images_api (line 192) | def extras_batch_images_api(self, req: models.ReqProcessBatch):

FILE: modules/api/rocm_smi.py
  class ThrottleStatus (line 21) | class ThrottleStatus(IntFlag):
    method active (line 58) | def active(self):
    method __iter__ (line 62) | def __iter__(self):
    method __str__ (line 65) | def __str__(self):
  function get_rocm_smi (line 69) | def get_rocm_smi():

FILE: modules/api/script.py
  function script_name_to_index (line 9) | def script_name_to_index(name, scripts_list):
  function get_selectable_script (line 22) | def get_selectable_script(script_name, script_runner):
  function get_scripts_list (line 32) | def get_scripts_list():
  function get_script_info (line 39) | def get_script_info(script_name: Optional[str] = None):
  function get_script (line 48) | def get_script(script_name, script_runner):
  function init_default_script_args (line 57) | def init_default_script_args(script_runner):
  function init_script_args (line 80) | def init_script_args(p, request, default_script_args, selectable_scripts...

FILE: modules/api/server.py
  function post_shutdown (line 11) | def post_shutdown():
  function get_js (line 16) | def get_js(request: Request):
  function get_motd (line 42) | def get_motd():
  function get_version (line 61) | def get_version():
  function get_platform (line 64) | def get_platform():
  function get_log (line 69) | def get_log(req: models.ReqGetLog = Depends()):
  function post_log (line 75) | def post_log(req: models.ReqPostLog):
  function get_config (line 85) | def get_config():
  function set_config (line 98) | def set_config(req: dict[str, Any]):
  function get_cmd_flags (line 105) | def get_cmd_flags():
  function get_history (line 108) | def get_history(req: models.ReqHistory = Depends()):
  function get_progress (line 116) | def get_progress(req: models.ReqProgress = Depends()):
  function get_status (line 140) | def get_status():
  function post_interrupt (line 143) | def post_interrupt():
  function post_skip (line 147) | def post_skip():
  function get_memory (line 150) | def get_memory():

FILE: modules/api/xpu_smi.py
  function get_xpu_smi (line 8) | def get_xpu_smi():

FILE: modules/api/xyz_grid.py
  function xyz_grid_enum (line 4) | def xyz_grid_enum(option: str = "") -> List[dict]:
  function register_api (line 24) | def register_api():

FILE: modules/attention.py
  function set_dynamic_attention (line 9) | def set_dynamic_attention():
  function set_triton_flash_attention (line 20) | def set_triton_flash_attention(backend: str):
  function set_flex_attention (line 51) | def set_flex_attention():
  function set_ck_flash_attention (line 87) | def set_ck_flash_attention(backend: str, device: torch.device):
  function set_sage_attention (line 129) | def set_sage_attention(backend: str, device: torch.device):
  function set_diffusers_attention (line 183) | def set_diffusers_attention(pipe, quiet:bool=False):

FILE: modules/ben2/__init__.py
  function remove (line 4) | def remove(image, refine: bool = True):

FILE: modules/ben2/ben2_model.py
  class Mlp (line 17) | class Mlp(nn.Module):
    method __init__ (line 20) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 29) | def forward(self, x):
  function window_partition (line 38) | def window_partition(x, window_size):
  function window_reverse (line 52) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 68) | class WindowAttention(nn.Module):
    method __init__ (line 81) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 115) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 149) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 166) | def __init__(self, dim, num_heads, window_size=7, shift_size=0,
    method forward (line 190) | def forward(self, x, mask_matrix):
  class PatchMerging (line 249) | class PatchMerging(nn.Module):
    method __init__ (line 255) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 261) | def forward(self, x, H, W):
  class BasicLayer (line 290) | class BasicLayer(nn.Module):
    method __init__ (line 308) | def __init__(self,
    method forward (line 350) | def forward(self, x, H, W):
  class PatchEmbed (line 392) | class PatchEmbed(nn.Module):
    method __init__ (line 401) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 415) | def forward(self, x):
  class SwinTransformer (line 434) | class SwinTransformer(nn.Module):
    method __init__ (line 462) | def __init__(self,
    method _freeze_stages (line 541) | def _freeze_stages(self):
    method forward (line 559) | def forward(self, x):
  function get_activation_fn (line 597) | def get_activation_fn(activation):
  function make_cbr (line 605) | def make_cbr(in_dim, out_dim):
  function make_cbg (line 609) | def make_cbg(in_dim, out_dim):
  function rescale_to (line 613) | def rescale_to(x, scale_factor: float = 2, interpolation='nearest'):
  function resize_as (line 617) | def resize_as(x, y, interpolation='bilinear'):
  function image2patches (line 621) | def image2patches(x):
  function patches2image (line 627) | def patches2image(x):
  class PositionEmbeddingSine (line 634) | class PositionEmbeddingSine:
    method __init__ (line 635) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method __call__ (line 647) | def __call__(self, b, h, w):
  class MCLM (line 670) | class MCLM(nn.Module):
    method __init__ (line 671) | def __init__(self, d_model, num_heads, pool_ratios=[1, 4, 8]):
    method forward (line 696) | def forward(self, l, g):
  class MCRM (line 762) | class MCRM(nn.Module):
    method __init__ (line 763) | def __init__(self, d_model, num_heads, pool_ratios=[4, 8, 16], h=None)...
    method forward (line 783) | def forward(self, x):
  class BEN_Base (line 821) | class BEN_Base(nn.Module):
    method __init__ (line 822) | def __init__(self):
    method forward (line 871) | def forward(self, x):
    method loadcheckpoints (line 940) | def loadcheckpoints(self,model_path):
    method inference (line 945) | def inference(self,image,refine_foreground=False):
    method segment_video (line 1009) | def segment_video(self, video_path, output_path="./", fps=0, refine_fo...
  function rgb_loader_refiner (line 1118) | def rgb_loader_refiner( original_image):
  function pil_images_to_mp4 (line 1143) | def pil_images_to_mp4(images, output_path, fps=24, rgb_value=(0, 255, 0)):
  function pil_images_to_webm_alpha (line 1177) | def pil_images_to_webm_alpha(images, output_path, fps=30):
  function add_audio_to_video (line 1216) | def add_audio_to_video(video_without_audio_path, original_video_path, ou...
  function refine_foreground_process (line 1250) | def refine_foreground_process(image, mask, r=90):
  function FB_blur_fusion_foreground_estimator_2 (line 1260) | def FB_blur_fusion_foreground_estimator_2(image, alpha, r=90):
  function FB_blur_fusion_foreground_estimator (line 1267) | def FB_blur_fusion_foreground_estimator(image, F, B, alpha, r=90):
  function postprocess_image (line 1283) | def postprocess_image(result: torch.Tensor, im_size: list) -> np.ndarray:

FILE: modules/cachedit.py
  function apply_cache_dit (line 6) | def apply_cache_dit(pipe):
  function unapply_cache_dir (line 54) | def unapply_cache_dir(pipe):

FILE: modules/call_queue.py
  function get_lock (line 14) | def get_lock():
  function wrap_queued_call (line 21) | def wrap_queued_call(func):
  function wrap_gradio_gpu_call (line 29) | def wrap_gradio_gpu_call(func, extra_outputs=None, name=None):
  function wrap_gradio_call (line 55) | def wrap_gradio_call(func, extra_outputs=None, add_stats=False, name=None):

FILE: modules/cfgzero/__init__.py
  function apply (line 17) | def apply(p: processing.StableDiffusionProcessing):
  function unapply (line 58) | def unapply():

FILE: modules/cfgzero/cogview4_pipeline.py
  function optimized_scale (line 34) | def optimized_scale(positive_flat, negative_flat):
  function calculate_shift (line 73) | def calculate_shift(
  function retrieve_timesteps (line 84) | def retrieve_timesteps(
  class CogView4CFGZeroPipeline (line 151) | class CogView4CFGZeroPipeline(DiffusionPipeline, CogView4LoraLoaderMixin):
    method __init__ (line 176) | def __init__(
    method _get_glm_embeds (line 192) | def _get_glm_embeds(
    method encode_prompt (line 237) | def encode_prompt(
    method prepare_latents (line 316) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method check_inputs (line 334) | def check_inputs(
    method guidance_scale (line 392) | def guidance_scale(self):
    method do_classifier_free_guidance (line 399) | def do_classifier_free_guidance(self):
    method num_timesteps (line 403) | def num_timesteps(self):
    method attention_kwargs (line 407) | def attention_kwargs(self):
    method current_timestep (line 411) | def current_timestep(self):
    method interrupt (line 415) | def interrupt(self):
    method __call__ (line 420) | def __call__(

FILE: modules/cfgzero/flux_pipeline.py
  function optimized_scale (line 60) | def optimized_scale(positive_flat, negative_flat):
  function calculate_shift (line 74) | def calculate_shift(
  function retrieve_timesteps (line 88) | def retrieve_timesteps(
  class FluxCFGZeroPipeline (line 147) | class FluxCFGZeroPipeline(
    method __init__ (line 184) | def __init__(
    method _get_t5_prompt_embeds (line 218) | def _get_t5_prompt_embeds(
    method _get_clip_prompt_embeds (line 267) | def _get_clip_prompt_embeds(
    method encode_prompt (line 311) | def encode_prompt(
    method encode_image (line 390) | def encode_image(self, image, device, num_images_per_prompt):
    method prepare_ip_adapter_image_embeds (line 401) | def prepare_ip_adapter_image_embeds(
    method check_inputs (line 437) | def check_inputs(
    method _prepare_latent_image_ids (line 515) | def _prepare_latent_image_ids(batch_size, height, width, device, dtype):
    method _pack_latents (line 529) | def _pack_latents(latents, batch_size, num_channels_latents, height, w...
    method _unpack_latents (line 537) | def _unpack_latents(latents, height, width, vae_scale_factor):
    method enable_vae_slicing (line 552) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 559) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 566) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 574) | def disable_vae_tiling(self):
    method prepare_latents (line 581) | def prepare_latents(
    method guidance_scale (line 617) | def guidance_scale(self):
    method joint_attention_kwargs (line 621) | def joint_attention_kwargs(self):
    method num_timesteps (line 625) | def num_timesteps(self):
    method current_timestep (line 629) | def current_timestep(self):
    method interrupt (line 633) | def interrupt(self):
    method __call__ (line 638) | def __call__(

FILE: modules/cfgzero/hidream_pipeline.py
  function optimized_scale (line 82) | def optimized_scale(positive_flat, negative_flat):
  function calculate_shift (line 96) | def calculate_shift(
  function retrieve_timesteps (line 110) | def retrieve_timesteps(
  class HiDreamImageCFGZeroPipeline (line 169) | class HiDreamImageCFGZeroPipeline(DiffusionPipeline, HiDreamImageLoraLoa...
    method __init__ (line 173) | def __init__(
    method _get_t5_prompt_embeds (line 212) | def _get_t5_prompt_embeds(
    method _get_clip_prompt_embeds (line 249) | def _get_clip_prompt_embeds(
    method _get_llama3_prompt_embeds (line 286) | def _get_llama3_prompt_embeds(
    method encode_prompt (line 330) | def encode_prompt(
    method _encode_prompt (line 414) | def _encode_prompt(
    method enable_vae_slicing (line 470) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 477) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 484) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 492) | def disable_vae_tiling(self):
    method prepare_latents (line 499) | def prepare_latents(
    method guidance_scale (line 526) | def guidance_scale(self):
    method do_classifier_free_guidance (line 530) | def do_classifier_free_guidance(self):
    method attention_kwargs (line 534) | def attention_kwargs(self):
    method num_timesteps (line 538) | def num_timesteps(self):
    method interrupt (line 542) | def interrupt(self):
    method __call__ (line 546) | def __call__(

FILE: modules/cfgzero/hunyuan_t2v_pipeline.py
  function optimized_scale (line 70) | def optimized_scale(positive_flat, negative_flat):
  function retrieve_timesteps (line 98) | def retrieve_timesteps(
  class HunyuanVideoCFGZeroPipeline (line 157) | class HunyuanVideoCFGZeroPipeline(DiffusionPipeline, HunyuanVideoLoraLoa...
    method __init__ (line 186) | def __init__(
    method _get_llama_prompt_embeds (line 212) | def _get_llama_prompt_embeds(
    method _get_clip_prompt_embeds (line 278) | def _get_clip_prompt_embeds(
    method encode_prompt (line 317) | def encode_prompt(
    method check_inputs (line 353) | def check_inputs(
    method prepare_latents (line 400) | def prepare_latents(
    method enable_vae_slicing (line 431) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 438) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 445) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 453) | def disable_vae_tiling(self):
    method guidance_scale (line 461) | def guidance_scale(self):
    method num_timesteps (line 465) | def num_timesteps(self):
    method attention_kwargs (line 469) | def attention_kwargs(self):
    method current_timestep (line 473) | def current_timestep(self):
    method interrupt (line 477) | def interrupt(self):
    method __call__ (line 482) | def __call__(

FILE: modules/cfgzero/sd3_pipeline.py
  function optimized_scale (line 73) | def optimized_scale(positive_flat, negative_flat):
  function calculate_shift (line 87) | def calculate_shift(
  function retrieve_timesteps (line 101) | def retrieve_timesteps(
  class StableDiffusion3CFGZeroPipeline (line 160) | class StableDiffusion3CFGZeroPipeline(DiffusionPipeline, SD3LoraLoaderMi...
    method __init__ (line 202) | def __init__(
    method _get_t5_prompt_embeds (line 247) | def _get_t5_prompt_embeds(
    method _get_clip_prompt_embeds (line 303) | def _get_clip_prompt_embeds(
    method encode_prompt (line 358) | def encode_prompt(
    method check_inputs (line 550) | def check_inputs(
    method prepare_latents (line 646) | def prepare_latents(
    method guidance_scale (line 678) | def guidance_scale(self):
    method skip_guidance_layers (line 682) | def skip_guidance_layers(self):
    method clip_skip (line 686) | def clip_skip(self):
    method do_classifier_free_guidance (line 693) | def do_classifier_free_guidance(self):
    method joint_attention_kwargs (line 697) | def joint_attention_kwargs(self):
    method num_timesteps (line 701) | def num_timesteps(self):
    method interrupt (line 705) | def interrupt(self):
    method encode_image (line 709) | def encode_image(self, image: PipelineImageInput, device: torch.device...
    method prepare_ip_adapter_image_embeds (line 729) | def prepare_ip_adapter_image_embeds(
    method enable_sequential_cpu_offload (line 775) | def enable_sequential_cpu_offload(self, *args, **kwargs):
    method __call__ (line 787) | def __call__(

FILE: modules/cfgzero/wan_t2v_pipeline.py
  function optimized_scale (line 75) | def optimized_scale(positive_flat, negative_flat):
  function basic_clean (line 88) | def basic_clean(text):
  function whitespace_clean (line 94) | def whitespace_clean(text):
  function prompt_clean (line 100) | def prompt_clean(text):
  class WanCFGZeroPipeline (line 105) | class WanCFGZeroPipeline(DiffusionPipeline, WanLoraLoaderMixin):
    method __init__ (line 130) | def __init__(
    method _get_t5_prompt_embeds (line 152) | def _get_t5_prompt_embeds(
    method encode_prompt (line 193) | def encode_prompt(
    method check_inputs (line 274) | def check_inputs(
    method prepare_latents (line 315) | def prepare_latents(
    method guidance_scale (line 348) | def guidance_scale(self):
    method do_classifier_free_guidance (line 352) | def do_classifier_free_guidance(self):
    method num_timesteps (line 356) | def num_timesteps(self):
    method current_timestep (line 360) | def current_timestep(self):
    method interrupt (line 364) | def interrupt(self):
    method attention_kwargs (line 368) | def attention_kwargs(self):
    method __call__ (line 373) | def __call__(

FILE: modules/civitai/api_civitai.py
  function models_to_json (line 4) | def models_to_json(all_models:list, model_id:int=None):
  function get_civitai (line 22) | def get_civitai(
  function post_civitai (line 57) | def post_civitai(page:str=None):
  function register_api (line 65) | def register_api():

FILE: modules/civitai/download_civitai.py
  function save_video_frame (line 11) | def save_video_frame(filepath: str):
  function download_civit_meta (line 28) | def download_civit_meta(model_path: str, model_id):
  function download_civit_preview (line 45) | def download_civit_preview(model_path: str, preview_url: str):
  function download_civit_model_thread (line 95) | def download_civit_model_thread(model_name: str, model_url: str, model_p...
  function download_civit_model (line 183) | def download_civit_model(model_url: str, model_name: str = '', model_pat...

FILE: modules/civitai/metadata_civitai.py
  class CivitModel (line 12) | class CivitModel:
    method __init__ (line 13) | def __init__(self, name, fn, sha = None, meta = {}):
  function civit_update_metadata (line 29) | def civit_update_metadata(raw:bool=False):
  function civit_search_model (line 109) | def civit_search_model(name, tag, model_type):
  function atomic_civit_search_metadata (line 161) | def atomic_civit_search_metadata(item, results):
  function civit_search_metadata (line 227) | def civit_search_metadata(title: str = None, raw: bool = False):

FILE: modules/civitai/search_civitai.py
  class ModelImage (line 13) | class ModelImage():
    method __init__ (line 14) | def __init__(self, dct: dict):
    method __str__ (line 24) | def __str__(self):
  class ModelFile (line 29) | class ModelFile():
    method __init__ (line 30) | def __init__(self, dct: dict):
    method __str__ (line 41) | def __str__(self):
  class ModelVersion (line 46) | class ModelVersion():
    method __init__ (line 47) | def __init__(self, dct: dict):
    method __str__ (line 63) | def __str__(self):
  class Model (line 68) | class Model():
    method __init__ (line 69) | def __init__(self, dct: dict):
    method __str__ (line 88) | def __str__(self):
  function search_civitai (line 95) | def search_civitai(
  function create_model_cards (line 177) | def create_model_cards(all_models: list[Model]) -> str:
  function print_models (line 208) | def print_models(all_models: list[Model]):

FILE: modules/cmd_args.py
  function parse_args (line 12) | def parse_args():
  function main_args (line 19) | def main_args():
  function compatibility_args (line 30) | def compatibility_args():
  function settings_args (line 55) | def settings_args(opts, args):

FILE: modules/control/proc/canny.py
  class CannyDetector (line 7) | class CannyDetector:
    method __call__ (line 8) | def __call__(self, input_image=None, low_threshold=100, high_threshold...

FILE: modules/control/proc/depth_anything/__init__.py
  class DepthAnythingDetector (line 10) | class DepthAnythingDetector:
    method __init__ (line 12) | def __init__(self, model):
    method from_pretrained (line 30) | def from_pretrained(cls, pretrained_model_or_path: str, cache_dir: str...
    method __call__ (line 48) | def __call__(self, image, color_map: str = "none", output_type: str = ...

FILE: modules/control/proc/depth_anything/blocks.py
  function _make_scratch (line 4) | def _make_scratch(in_shape, out_shape, groups=1, expand=False):
  class ResidualConvUnit (line 37) | class ResidualConvUnit(nn.Module):
    method __init__ (line 41) | def __init__(self, features, activation, bn):
    method forward (line 69) | def forward(self, x):
  class FeatureFusionBlock (line 95) | class FeatureFusionBlock(nn.Module):
    method __init__ (line 99) | def __init__(self, features, activation, deconv=False, bn=False, expan...
    method forward (line 126) | def forward(self, *xs, size=None):

FILE: modules/control/proc/depth_anything/dpt.py
  function _make_fusion_block (line 8) | def _make_fusion_block(features, use_bn, size = None):
  class DPTHead (line 20) | class DPTHead(nn.Module):
    method __init__ (line 21) | def __init__(self, nclass, in_channels, features=256, use_bn=False, ou...
    method forward (line 103) | def forward(self, out_features, patch_h, patch_w):
  class DPT_DINOv2 (line 139) | class DPT_DINOv2(nn.Module):
    method __init__ (line 140) | def __init__(self, encoder='vitl', features=256, out_channels=None, us...
    method forward (line 157) | def forward(self, x):
  class DepthAnything (line 171) | class DepthAnything(DPT_DINOv2, PyTorchModelHubMixin):
    method __init__ (line 172) | def __init__(self, config):

FILE: modules/control/proc/depth_anything/util/transform.py
  function apply_min_size (line 12) | def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AR...
  class Resize (line 54) | class Resize(object):
    method __init__ (line 58) | def __init__(
    method constrain_to_multiple_of (line 100) | def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
    method get_size (line 111) | def get_size(self, width, height):
    method __call__ (line 168) | def __call__(self, sample):
  class NormalizeImage (line 211) | class NormalizeImage(object):
    method __init__ (line 215) | def __init__(self, mean, std):
    method __call__ (line 219) | def __call__(self, sample):
  class PrepareForNet (line 225) | class PrepareForNet(object):
    method __init__ (line 229) | def __init__(self):
    method __call__ (line 232) | def __call__(self, sample):

FILE: modules/control/proc/depth_pro/__init__.py
  class DepthProDetector (line 11) | class DepthProDetector:
    method __init__ (line 14) | def __init__(self, model, processor):
    method from_pretrained (line 19) | def from_pretrained(cls, pretrained_model_or_path: str = "apple/DepthP...
    method __call__ (line 30) | def __call__(self, image, color_map: str = "none", output_type: str = ...

FILE: modules/control/proc/dpt.py
  class DPTDetector (line 12) | class DPTDetector:
    method __init__ (line 13) | def __init__(self, model=None, processor=None, model_path=None):
    method __call__ (line 18) | def __call__(self, input_image=None, model_path=None):

FILE: modules/control/proc/dwpose/__init__.py
  function _register_module (line 20) | def _register_module(self, module: Type, module_name: Optional[Union[str...
  function check_dependencies (line 33) | def check_dependencies():
  function draw_pose (line 78) | def draw_pose(pose, H, W):
  class DWposeDetector (line 92) | class DWposeDetector:
    method __init__ (line 93) | def __init__(self, det_config=None, det_ckpt=None, pose_config=None, p...
    method to (line 106) | def to(self, device):
    method __call__ (line 110) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/dwpose/draw.py
  function smart_resize (line 9) | def smart_resize(x, s):
  function smart_resize_k (line 23) | def smart_resize_k(x, fx, fy):
  function padRightDownCorner (line 37) | def padRightDownCorner(img, stride, padValue):
  function transfer (line 60) | def transfer(model, model_weights):
  function draw_bodypose (line 67) | def draw_bodypose(canvas, candidate, subset):
  function draw_handpose (line 111) | def draw_handpose(canvas, all_hand_peaks):
  function draw_facepose (line 146) | def draw_facepose(canvas, all_lmks):
  function handDetect (line 161) | def handDetect(candidate, subset, oriImg):
  function faceDetect (line 231) | def faceDetect(candidate, subset, oriImg):
  function npmax (line 302) | def npmax(array):

FILE: modules/control/proc/dwpose/wholebody.py
  function inference_detector (line 29) | def inference_detector(*args, **kwargs):
  class Wholebody (line 36) | class Wholebody:
    method __init__ (line 37) | def __init__(self, det_config=None, det_ckpt=None, pose_config=None, p...
    method to (line 63) | def to(self, device):
    method __call__ (line 68) | def __call__(self, oriImg):

FILE: modules/control/proc/edge.py
  class EdgeDetector (line 24) | class EdgeDetector:
    method __call__ (line 25) | def __call__(self, input_image=None, pf=True, mode='edge', detect_reso...

FILE: modules/control/proc/glpn.py
  class GLPNDetector (line 9) | class GLPNDetector:
    method __init__ (line 10) | def __init__(self, model=None, processor=None):
    method __call__ (line 14) | def __call__(self, input_image=None):

FILE: modules/control/proc/hed.py
  class DoubleConvBlock (line 20) | class DoubleConvBlock(torch.nn.Module): # pylint: disable=abstract-method
    method __init__ (line 21) | def __init__(self, input_channel, output_channel, layer_number):
    method __call__ (line 29) | def __call__(self, x, down_sampling=False):
  class ControlNetHED_Apache2 (line 39) | class ControlNetHED_Apache2(torch.nn.Module): # pylint: disable=abstract...
    method __init__ (line 40) | def __init__(self):
    method __call__ (line 49) | def __call__(self, x):
  class HEDdetector (line 58) | class HEDdetector:
    method __init__ (line 59) | def __init__(self, model):
    method from_pretrained (line 63) | def from_pretrained(cls, pretrained_model_or_path, filename=None, cach...
    method to (line 74) | def to(self, device):
    method __call__ (line 78) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/leres/__init__.py
  class LeresDetector (line 17) | class LeresDetector:
    method __init__ (line 18) | def __init__(self, model, pix2pixmodel):
    method from_pretrained (line 23) | def from_pretrained(cls, pretrained_model_or_path, filename=None, pix2...
    method to (line 47) | def to(self, device):
    method __call__ (line 51) | def __call__(self, input_image, thr_a=0, thr_b=0, boost=False, detect_...

FILE: modules/control/proc/leres/leres/Resnet.py
  function conv3x3 (line 17) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 23) | class BasicBlock(nn.Module):
    method __init__ (line 26) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 36) | def forward(self, x):
  class Bottleneck (line 55) | class Bottleneck(nn.Module):
    method __init__ (line 58) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 71) | def forward(self, x):
  class ResNet (line 94) | class ResNet(nn.Module):
    method __init__ (line 96) | def __init__(self, block, layers, num_classes=1000):
    method _make_layer (line 118) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 135) | def forward(self, x):
  function resnet18 (line 155) | def resnet18(pretrained=True, **kwargs):
  function resnet34 (line 164) | def resnet34(pretrained=True, **kwargs):
  function resnet50 (line 173) | def resnet50(pretrained=True, **kwargs):
  function resnet101 (line 183) | def resnet101(pretrained=True, **kwargs):
  function resnet152 (line 193) | def resnet152(pretrained=True, **kwargs):

FILE: modules/control/proc/leres/leres/Resnext_torch.py
  function conv3x3 (line 19) | def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
  function conv1x1 (line 25) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 30) | class BasicBlock(nn.Module):
    method __init__ (line 33) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 51) | def forward(self, x):
  class Bottleneck (line 70) | class Bottleneck(nn.Module):
    method __init__ (line 79) | def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
    method forward (line 96) | def forward(self, x):
  class ResNet (line 119) | class ResNet(nn.Module):
    method __init__ (line 121) | def __init__(self, block, layers, num_classes=1000, zero_init_residual...
    method _make_layer (line 172) | def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
    method _forward_impl (line 196) | def _forward_impl(self, x):
    method forward (line 222) | def forward(self, x):
  function resnext101_32x8d (line 227) | def resnext101_32x8d(pretrained=True, **kwargs):

FILE: modules/control/proc/leres/leres/depthmap.py
  function scale_torch (line 18) | def scale_torch(img):
  function estimateleres (line 35) | def estimateleres(img, model, w, h):
  function generatemask (line 51) | def generatemask(size):
  function resizewithpool (line 62) | def resizewithpool(img, size):
  function rgb2gray (line 69) | def rgb2gray(rgb):
  function calculateprocessingres (line 73) | def calculateprocessingres(img, basesize, confidence=0.1, scale_threshol...
  function doubleestimate (line 131) | def doubleestimate(img, size1, size2, pix2pixsize, model, net_type, pix2...
  function singleestimate (line 155) | def singleestimate(img, msize, model, net_type):
  function applyGridpatch (line 161) | def applyGridpatch(blsize, stride, img, box):
  function generatepatchs (line 177) | def generatepatchs(img, base_size):
  function getGF_fromintegral (line 208) | def getGF_fromintegral(integralimage, rect):
  function adaptiveselection (line 218) | def adaptiveselection(integral_grad, patch_bound_list, gf):
  function impatch (line 268) | def impatch(image, rect):
  class ImageandPatchs (line 277) | class ImageandPatchs:
    method __init__ (line 278) | def __init__(self, root_dir, name, patchsinfo, rgb_image, scale=1):
    method __len__ (line 292) | def __len__(self):
    method set_base_estimate (line 295) | def set_base_estimate(self, est):
    method set_updated_estimate (line 300) | def set_updated_estimate(self, est):
    method __getitem__ (line 305) | def __getitem__(self, index):
    method print_options (line 325) | def print_options(self, opt):
    method parse (line 352) | def parse(self):
  function estimateboost (line 378) | def estimateboost(img, model, model_type, pix2pixmodel, max_res=512, dep...

FILE: modules/control/proc/leres/leres/multi_depth_model_woauxi.py
  class RelDepthModel (line 8) | class RelDepthModel(nn.Module):
    method __init__ (line 9) | def __init__(self, backbone='resnet50'):
    method inference (line 17) | def inference(self, rgb):
  class DepthModel (line 24) | class DepthModel(nn.Module):
    method __init__ (line 25) | def __init__(self, encoder):
    method forward (line 31) | def forward(self, x):

FILE: modules/control/proc/leres/leres/net_tools.py
  function get_func (line 7) | def get_func(func_name):
  function load_ckpt (line 27) | def load_ckpt(args, depth_model, shift_model, focal_model):
  function strip_prefix_if_present (line 47) | def strip_prefix_if_present(state_dict, prefix):

FILE: modules/control/proc/leres/leres/network_auxi.py
  function resnet50_stride32 (line 8) | def resnet50_stride32():
  function resnext101_stride32x8d (line 11) | def resnext101_stride32x8d():
  class Decoder (line 15) | class Decoder(nn.Module):
    method __init__ (line 16) | def __init__(self):
    method _init_params (line 34) | def _init_params(self):
    method forward (line 52) | def forward(self, features):
  class DepthNet (line 64) | class DepthNet(nn.Module):
    method __init__ (line 72) | def __init__(self,
    method forward (line 97) | def forward(self, x):
  class FTB (line 102) | class FTB(nn.Module):
    method __init__ (line 103) | def __init__(self, inchannels, midchannels=512):
    method forward (line 121) | def forward(self, x):
    method init_params (line 128) | def init_params(self):
  class ATA (line 149) | class ATA(nn.Module):
    method __init__ (line 150) | def __init__(self, inchannels, reduction=8):
    method forward (line 160) | def forward(self, low_x, high_x):
    method init_params (line 170) | def init_params(self):
  class FFM (line 193) | class FFM(nn.Module):
    method __init__ (line 194) | def __init__(self, inchannels, midchannels, outchannels, upfactor=2):
    method forward (line 209) | def forward(self, low_x, high_x):
    method init_params (line 217) | def init_params(self):
  class AO (line 240) | class AO(nn.Module):
    method __init__ (line 242) | def __init__(self, inchannels, outchannels, upfactor=2):
    method forward (line 259) | def forward(self, x):
    method init_params (line 263) | def init_params(self):
  class ResidualConv (line 290) | class ResidualConv(nn.Module):
    method __init__ (line 291) | def __init__(self, inchannels):
    method forward (line 308) | def forward(self, x):
    method init_params (line 312) | def init_params(self):
  class FeatureFusion (line 335) | class FeatureFusion(nn.Module):
    method __init__ (line 336) | def __init__(self, inchannels, outchannels):
    method forward (line 346) | def forward(self, lowfeat, highfeat):
    method init_params (line 349) | def init_params(self):
  class SenceUnderstand (line 372) | class SenceUnderstand(nn.Module):
    method __init__ (line 373) | def __init__(self, channels):
    method forward (line 386) | def forward(self, x):
    method initial_params (line 397) | def initial_params(self, dev=0.01):

FILE: modules/control/proc/leres/pix2pix/models/__init__.py
  function find_model_using_name (line 25) | def find_model_using_name(model_name):
  function get_option_setter (line 48) | def get_option_setter(model_name):
  function create_model (line 54) | def create_model(opt):

FILE: modules/control/proc/leres/pix2pix/models/base_model.py
  class BaseModel (line 12) | class BaseModel(ABC):
    method __init__ (line 22) | def __init__(self, opt):
    method modify_commandline_options (line 51) | def modify_commandline_options(parser, is_train):
    method set_input (line 64) | def set_input(self, input):
    method forward (line 73) | def forward(self):
    method optimize_parameters (line 78) | def optimize_parameters(self):
    method setup (line 82) | def setup(self, opt):
    method eval (line 95) | def eval(self):
    method test (line 102) | def test(self):
    method compute_visuals (line 110) | def compute_visuals(self): # noqa
    method get_image_paths (line 114) | def get_image_paths(self):
    method update_learning_rate (line 118) | def update_learning_rate(self):
    method get_current_visuals (line 130) | def get_current_visuals(self):
    method get_current_losses (line 138) | def get_current_losses(self):
    method save_networks (line 146) | def save_networks(self, epoch):
    method unload_network (line 164) | def unload_network(self, name):
    method __patch_instance_norm_state_dict (line 174) | def __patch_instance_norm_state_dict(self, state_dict, module, keys, i...
    method load_networks (line 188) | def load_networks(self, epoch):
    method print_networks (line 213) | def print_networks(self, verbose):
    method set_requires_grad (line 231) | def set_requires_grad(self, nets, requires_grad=False):

FILE: modules/control/proc/leres/pix2pix/models/base_model_hg.py
  class BaseModelHG (line 4) | class BaseModelHG():
    method name (line 5) | def name(self):
    method initialize (line 8) | def initialize(self, opt):
    method set_input (line 15) | def set_input(self, input):
    method forward (line 18) | def forward(self):
    method test (line 22) | def test(self):
    method get_image_paths (line 25) | def get_image_paths(self):
    method optimize_parameters (line 28) | def optimize_parameters(self):
    method get_current_visuals (line 31) | def get_current_visuals(self):
    method get_current_errors (line 34) | def get_current_errors(self):
    method save (line 37) | def save(self, label):
    method save_network (line 41) | def save_network(self, network, network_label, epoch_label, gpu_ids):
    method load_network (line 49) | def load_network(self, network, network_label, epoch_label):
    method update_learning_rate (line 57) | def update_learning_rate():

FILE: modules/control/proc/leres/pix2pix/models/networks.py
  class Identity (line 13) | class Identity(nn.Module):
    method forward (line 14) | def forward(self, x):
  function get_norm_layer (line 18) | def get_norm_layer(norm_type='instance'):
  function get_scheduler (line 38) | def get_scheduler(optimizer, opt):
  function init_weights (line 67) | def init_weights(net, init_type='normal', init_gain=0.02):
  function init_net (line 101) | def init_net(net, init_type='normal', init_gain=0.02, gpu_ids=None):
  function define_G (line 121) | def define_G(input_nc, output_nc, ngf, netG, norm='batch', use_dropout=F...
  function define_D (line 174) | def define_D(input_nc, ndf, netD, n_layers_D=3, norm='batch', init_type=...
  class GANLoss (line 223) | class GANLoss(nn.Module):
    method __init__ (line 230) | def __init__(self, gan_mode, target_real_label=1.0, target_fake_label=...
    method get_target_tensor (line 254) | def get_target_tensor(self, prediction, target_is_real):
    method __call__ (line 271) | def __call__(self, prediction, target_is_real):
  function cal_gradient_penalty (line 292) | def cal_gradient_penalty(netD, real_data, fake_data, device, type='mixed...
  class ResnetGenerator (line 329) | class ResnetGenerator(nn.Module):
    method __init__ (line 335) | def __init__(self, input_nc, output_nc, ngf=64, norm_layer=nn.BatchNor...
    method forward (line 384) | def forward(self, input):
  class ResnetBlock (line 389) | class ResnetBlock(nn.Module):
    method __init__ (line 392) | def __init__(self, dim, padding_type, norm_layer, use_dropout, use_bias):
    method build_conv_block (line 403) | def build_conv_block(self, dim, padding_type, norm_layer, use_dropout,...
    method forward (line 443) | def forward(self, x):
  class UnetGenerator (line 449) | class UnetGenerator(nn.Module):
    method __init__ (line 452) | def __init__(self, input_nc, output_nc, num_downs, ngf=64, norm_layer=...
    method forward (line 476) | def forward(self, input):
  class UnetSkipConnectionBlock (line 481) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 487) | def __init__(self, outer_nc, inner_nc, input_nc=None,
    method forward (line 544) | def forward(self, x):
  class NLayerDiscriminator (line 551) | class NLayerDiscriminator(nn.Module):
    method __init__ (line 554) | def __init__(self, input_nc, ndf=64, n_layers=3, norm_layer=nn.BatchNo...
    method forward (line 594) | def forward(self, input):
  class PixelDiscriminator (line 599) | class PixelDiscriminator(nn.Module):
    method __init__ (line 602) | def __init__(self, input_nc, ndf=64, norm_layer=nn.BatchNorm2d):
    method forward (line 626) | def forward(self, input):

FILE: modules/control/proc/leres/pix2pix/models/pix2pix4depth_model.py
  class Pix2Pix4DepthModel (line 6) | class Pix2Pix4DepthModel(BaseModel):
    method modify_commandline_options (line 17) | def modify_commandline_options(parser, is_train=True):
    method __init__ (line 38) | def __init__(self, opt):
    method set_input_train (line 80) | def set_input_train(self, input):
    method set_input (line 96) | def set_input(self, outer, inner):
    method normalize (line 109) | def normalize(self, input):
    method forward (line 114) | def forward(self):
    method backward_D (line 118) | def backward_D(self):
    method backward_G (line 132) | def backward_G(self):
    method optimize_parameters (line 144) | def optimize_parameters(self):

FILE: modules/control/proc/leres/pix2pix/options/base_options.py
  class BaseOptions (line 9) | class BaseOptions():
    method __init__ (line 16) | def __init__(self):
    method initialize (line 20) | def initialize(self, parser):
    method gather_options (line 79) | def gather_options(self):
    method print_options (line 108) | def print_options(self, opt):
    method parse (line 133) | def parse(self):

FILE: modules/control/proc/leres/pix2pix/options/test_options.py
  class TestOptions (line 4) | class TestOptions(BaseOptions):
    method initialize (line 10) | def initialize(self, parser):

FILE: modules/control/proc/leres/pix2pix/util/util.py
  function tensor2im (line 9) | def tensor2im(input_image, imtype=np.uint16):
  function diagnose_network (line 28) | def diagnose_network(net, name='network'):
  function save_image (line 47) | def save_image(image_numpy, image_path, aspect_ratio=1.0):
  function print_numpy (line 69) | def print_numpy(x, val=True, shp=False):
  function mkdirs (line 85) | def mkdirs(paths):
  function mkdir (line 98) | def mkdir(path):

FILE: modules/control/proc/lineart.py
  class ResidualBlock (line 15) | class ResidualBlock(nn.Module):
    method __init__ (line 16) | def __init__(self, in_features):
    method forward (line 30) | def forward(self, x):
  class Generator (line 34) | class Generator(nn.Module):
    method __init__ (line 35) | def __init__(self, input_nc, output_nc, n_residual_blocks=9, sigmoid=T...
    method forward (line 82) | def forward(self, x, cond=None): # pylint: disable=unused-argument
  class LineartDetector (line 92) | class LineartDetector:
    method __init__ (line 93) | def __init__(self, model, coarse_model):
    method from_pretrained (line 98) | def from_pretrained(cls, pretrained_model_or_path, filename=None, coar...
    method to (line 119) | def to(self, device):
    method __call__ (line 124) | def __call__(self, input_image, coarse=False, detect_resolution=512, i...

FILE: modules/control/proc/lineart_anime.py
  class UnetGenerator (line 15) | class UnetGenerator(nn.Module):
    method __init__ (line 18) | def __init__(self, input_nc, output_nc, num_downs, ngf=64, norm_layer=...
    method forward (line 41) | def forward(self, input): # pylint: disable=redefined-builtin
  class UnetSkipConnectionBlock (line 46) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 52) | def __init__(self, outer_nc, inner_nc, input_nc=None,
    method forward (line 108) | def forward(self, x):
  class LineartAnimeDetector (line 115) | class LineartAnimeDetector:
    method __init__ (line 116) | def __init__(self, model):
    method from_pretrained (line 120) | def from_pretrained(cls, pretrained_model_or_path, filename=None, cach...
    method to (line 137) | def to(self, device):
    method __call__ (line 141) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/marigold/__init__.py
  class MarigoldDetector (line 9) | class MarigoldDetector:
    method __init__ (line 10) | def __init__(self, model):
    method from_pretrained (line 14) | def from_pretrained(cls, pretrained_model_or_path, cache_dir=None, **l...
    method to (line 18) | def to(self, device):
    method __call__ (line 22) | def __call__(

FILE: modules/control/proc/marigold/marigold_pipeline.py
  class MarigoldDepthOutput (line 43) | class MarigoldDepthOutput(BaseOutput):
  class MarigoldPipeline (line 61) | class MarigoldPipeline(DiffusionPipeline):
    method __init__ (line 85) | def __init__(
    method __call__ (line 106) | def __call__(
    method __encode_empty_text (line 255) | def __encode_empty_text(self):
    method single_infer (line 271) | def single_infer(
    method encode_rgb (line 341) | def encode_rgb(self, rgb_in: torch.Tensor) -> torch.Tensor:
    method decode_depth (line 360) | def decode_depth(self, depth_latent: torch.Tensor) -> torch.Tensor:

FILE: modules/control/proc/marigold/util/batchsize.py
  function find_batch_size (line 51) | def find_batch_size(ensemble_size: int, input_res: int, dtype: torch.dty...

FILE: modules/control/proc/marigold/util/ensemble.py
  function inter_distances (line 27) | def inter_distances(tensors: torch.Tensor):
  function ensemble_depths (line 40) | def ensemble_depths(

FILE: modules/control/proc/marigold/util/image_util.py
  function colorize_depth_maps (line 27) | def colorize_depth_maps(
  function chw2hwc (line 68) | def chw2hwc(chw):
  function resize_max_res (line 77) | def resize_max_res(img: Image.Image, max_edge_resolution: int) -> Image....

FILE: modules/control/proc/marigold/util/seed_all.py
  function seed_all (line 26) | def seed_all(seed: int = 0):

FILE: modules/control/proc/mediapipe_face.py
  function check_dependencies (line 10) | def check_dependencies():
  class MediapipeFaceDetector (line 26) | class MediapipeFaceDetector:
    method __call__ (line 27) | def __call__(self,

FILE: modules/control/proc/mediapipe_face_util.py
  function draw_pupils (line 56) | def draw_pupils(image, landmark_list, drawing_spec, halfwidth: int = 2):
  function reverse_channels (line 85) | def reverse_channels(image):
  function generate_annotation (line 92) | def generate_annotation(

FILE: modules/control/proc/midas/__init__.py
  class MidasDetector (line 15) | class MidasDetector:
    method __init__ (line 16) | def __init__(self, model):
    method from_pretrained (line 20) | def from_pretrained(cls, pretrained_model_or_path, model_type="dpt_hyb...
    method to (line 33) | def to(self, device):
    method __call__ (line 37) | def __call__(self, input_image, a=np.pi * 2.0, bg_th=0.1, depth_and_no...

FILE: modules/control/proc/midas/api.py
  function disabled_train (line 26) | def disabled_train(self, mode=True):
  function load_midas_transform (line 32) | def load_midas_transform(model_type):
  function load_model (line 77) | def load_model(model_type, model_path=None):
  class MiDaSInference (line 145) | class MiDaSInference(nn.Module):
    method __init__ (line 158) | def __init__(self, model_type, model_path):
    method forward (line 165) | def forward(self, x):

FILE: modules/control/proc/midas/midas/base_model.py
  class BaseModel (line 4) | class BaseModel(torch.nn.Module):
    method load (line 5) | def load(self, path):

FILE: modules/control/proc/midas/midas/blocks.py
  function _make_encoder (line 11) | def _make_encoder(backbone, features, use_pretrained, groups=1, expand=F...
  function _make_scratch (line 49) | def _make_scratch(in_shape, out_shape, groups=1, expand=False):
  function _make_pretrained_efficientnet_lite3 (line 78) | def _make_pretrained_efficientnet_lite3(use_pretrained, exportable=False):
  function _make_efficientnet_backbone (line 88) | def _make_efficientnet_backbone(effnet):
  function _make_resnet_backbone (line 101) | def _make_resnet_backbone(resnet):
  function _make_pretrained_resnext101_wsl (line 114) | def _make_pretrained_resnext101_wsl(use_pretrained):
  class Interpolate (line 120) | class Interpolate(nn.Module):
    method __init__ (line 124) | def __init__(self, scale_factor, mode, align_corners=False):
    method forward (line 138) | def forward(self, x):
  class ResidualConvUnit (line 155) | class ResidualConvUnit(nn.Module):
    method __init__ (line 159) | def __init__(self, features):
    method forward (line 177) | def forward(self, x):
  class FeatureFusionBlock (line 194) | class FeatureFusionBlock(nn.Module):
    method __init__ (line 198) | def __init__(self, features):
    method forward (line 209) | def forward(self, *xs):
  class ResidualConvUnit_custom (line 231) | class ResidualConvUnit_custom(nn.Module):
    method __init__ (line 235) | def __init__(self, features, activation, bn):
    method forward (line 263) | def forward(self, x):
  class FeatureFusionBlock_custom (line 291) | class FeatureFusionBlock_custom(nn.Module):
    method __init__ (line 295) | def __init__(self, features, activation, deconv=False, bn=False, expan...
    method forward (line 320) | def forward(self, *xs):

FILE: modules/control/proc/midas/midas/dpt_depth.py
  function _make_fusion_block (line 15) | def _make_fusion_block(features, use_bn):
  class DPT (line 26) | class DPT(BaseModel):
    method __init__ (line 27) | def __init__(
    method forward (line 67) | def forward(self, x):
  class DPTDepthModel (line 88) | class DPTDepthModel(DPT):
    method __init__ (line 89) | def __init__(self, path=None, non_negative=True, **kwargs):
    method forward (line 107) | def forward(self, x):

FILE: modules/control/proc/midas/midas/midas_net.py
  class MidasNet (line 12) | class MidasNet(BaseModel):
    method __init__ (line 16) | def __init__(self, path=None, features=256, non_negative=True):
    method forward (line 49) | def forward(self, x):

FILE: modules/control/proc/midas/midas/midas_net_custom.py
  class MidasNet_small (line 12) | class MidasNet_small(BaseModel):
    method __init__ (line 16) | def __init__(self, path=None, features=64, backbone="efficientnet_lite...
    method forward (line 75) | def forward(self, x):
  function fuse_model (line 111) | def fuse_model(m):

FILE: modules/control/proc/midas/midas/transforms.py
  function apply_min_size (line 6) | def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AR...
  class Resize (line 48) | class Resize(object):
    method __init__ (line 52) | def __init__(
    method constrain_to_multiple_of (line 94) | def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
    method get_size (line 105) | def get_size(self, width, height):
    method __call__ (line 162) | def __call__(self, sample):
  class NormalizeImage (line 197) | class NormalizeImage(object):
    method __init__ (line 201) | def __init__(self, mean, std):
    method __call__ (line 205) | def __call__(self, sample):
  class PrepareForNet (line 211) | class PrepareForNet(object):
    method __init__ (line 215) | def __init__(self):
    method __call__ (line 218) | def __call__(self, sample):

FILE: modules/control/proc/midas/midas/vit.py
  class Slice (line 9) | class Slice(nn.Module):
    method __init__ (line 10) | def __init__(self, start_index=1):
    method forward (line 14) | def forward(self, x):
  class AddReadout (line 18) | class AddReadout(nn.Module):
    method __init__ (line 19) | def __init__(self, start_index=1):
    method forward (line 23) | def forward(self, x):
  class ProjectReadout (line 31) | class ProjectReadout(nn.Module):
    method __init__ (line 32) | def __init__(self, in_features, start_index=1):
    method forward (line 38) | def forward(self, x):
  class Transpose (line 45) | class Transpose(nn.Module):
    method __init__ (line 46) | def __init__(self, dim0, dim1):
    method forward (line 51) | def forward(self, x):
  function forward_vit (line 56) | def forward_vit(pretrained, x):
  function _resize_pos_embed (line 100) | def _resize_pos_embed(self, posemb, gs_h, gs_w):
  function forward_flex (line 117) | def forward_flex(self, x):
  function get_activation (line 159) | def get_activation(name):
  function get_readout_oper (line 166) | def get_readout_oper(vit_features, features, use_readout, start_index=1):
  function _make_vit_b16_backbone (line 181) | def _make_vit_b16_backbone(
  function _make_pretrained_vitl16_384 (line 301) | def _make_pretrained_vitl16_384(pretrained, use_readout="ignore", hooks=...
  function _make_pretrained_vitb16_384 (line 314) | def _make_pretrained_vitb16_384(pretrained, use_readout="ignore", hooks=...
  function _make_pretrained_deitb16_384 (line 323) | def _make_pretrained_deitb16_384(pretrained, use_readout="ignore", hooks...
  function _make_pretrained_deitb16_distil_384 (line 332) | def _make_pretrained_deitb16_distil_384(pretrained, use_readout="ignore"...
  function _make_vit_b_rn50_backbone (line 347) | def _make_vit_b_rn50_backbone(
  function _make_pretrained_vitb_rn50_384 (line 488) | def _make_pretrained_vitb_rn50_384(

FILE: modules/control/proc/midas/utils.py
  function read_pfm (line 9) | def read_pfm(path):
  function write_pfm (line 58) | def write_pfm(path, image, scale=1):
  function read_image (line 97) | def read_image(path):
  function resize_image (line 116) | def resize_image(img):
  function resize_depth (line 146) | def resize_depth(depth, width, height):
  function write_depth (line 165) | def write_depth(path, depth, bits=1):

FILE: modules/control/proc/mlsd/__init__.py
  class MLSDdetector (line 14) | class MLSDdetector:
    method __init__ (line 15) | def __init__(self, model):
    method from_pretrained (line 19) | def from_pretrained(cls, pretrained_model_or_path, filename=None, cach...
    method to (line 33) | def to(self, device):
    method __call__ (line 37) | def __call__(self, input_image, thr_v=0.1, thr_d=0.1, detect_resolutio...

FILE: modules/control/proc/mlsd/models/mbv2_mlsd_large.py
  class BlockTypeA (line 9) | class BlockTypeA(nn.Module):
    method __init__ (line 10) | def __init__(self, in_c1, in_c2, out_c1, out_c2, upscale = True):
    method forward (line 24) | def forward(self, a, b):
  class BlockTypeB (line 32) | class BlockTypeB(nn.Module):
    method __init__ (line 33) | def __init__(self, in_c, out_c):
    method forward (line 46) | def forward(self, x):
  class BlockTypeC (line 51) | class BlockTypeC(nn.Module):
    method __init__ (line 52) | def __init__(self, in_c, out_c):
    method forward (line 66) | def forward(self, x):
  function _make_divisible (line 72) | def _make_divisible(v, divisor, min_value=None):
  class ConvBNReLU (line 92) | class ConvBNReLU(nn.Sequential):
    method __init__ (line 93) | def __init__(self, in_planes, out_planes, kernel_size=3, stride=1, gro...
    method forward (line 112) | def forward(self, x):
  class InvertedResidual (line 124) | class InvertedResidual(nn.Module):
    method __init__ (line 125) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 146) | def forward(self, x):
  class MobileNetV2 (line 153) | class MobileNetV2(nn.Module):
    method __init__ (line 154) | def __init__(self, pretrained=True):
    method _forward_impl (line 218) | def _forward_impl(self, x):
    method forward (line 233) | def forward(self, x):
    method _load_pretrained_model (line 236) | def _load_pretrained_model(self):
  class MobileV2_MLSD_Large (line 247) | class MobileV2_MLSD_Large(nn.Module):
    method __init__ (line 248) | def __init__(self):
    method forward (line 275) | def forward(self, x):

FILE: modules/control/proc/mlsd/models/mbv2_mlsd_tiny.py
  class BlockTypeA (line 9) | class BlockTypeA(nn.Module):
    method __init__ (line 10) | def __init__(self, in_c1, in_c2, out_c1, out_c2, upscale = True):
    method forward (line 24) | def forward(self, a, b):
  class BlockTypeB (line 31) | class BlockTypeB(nn.Module):
    method __init__ (line 32) | def __init__(self, in_c, out_c):
    method forward (line 45) | def forward(self, x):
  class BlockTypeC (line 50) | class BlockTypeC(nn.Module):
    method __init__ (line 51) | def __init__(self, in_c, out_c):
    method forward (line 65) | def forward(self, x):
  function _make_divisible (line 71) | def _make_divisible(v, divisor, min_value=None):
  class ConvBNReLU (line 91) | class ConvBNReLU(nn.Sequential):
    method __init__ (line 92) | def __init__(self, in_planes, out_planes, kernel_size=3, stride=1, gro...
    method forward (line 111) | def forward(self, x):
  class InvertedResidual (line 123) | class InvertedResidual(nn.Module):
    method __init__ (line 124) | def __init__(self, inp, oup, stride, expand_ratio):
    method forward (line 145) | def forward(self, x):
  class MobileNetV2 (line 152) | class MobileNetV2(nn.Module):
    method __init__ (line 153) | def __init__(self, pretrained=True):
    method _forward_impl (line 218) | def _forward_impl(self, x):
    method forward (line 233) | def forward(self, x):
    method _load_pretrained_model (line 236) | def _load_pretrained_model(self):
  class MobileV2_MLSD_Tiny (line 247) | class MobileV2_MLSD_Tiny(nn.Module):
    method __init__ (line 248) | def __init__(self):
    method forward (line 263) | def forward(self, x):

FILE: modules/control/proc/mlsd/utils.py
  function deccode_output_score_and_ptss (line 19) | def deccode_output_score_and_ptss(tpMap, topk_n = 200, ksize = 5):
  function pred_lines (line 47) | def pred_lines(image, model,
  function pred_squares (line 94) | def pred_squares(image,

FILE: modules/control/proc/normalbae/__init__.py
  function load_checkpoint (line 17) | def load_checkpoint(fpath, model):
  class NormalBaeDetector (line 30) | class NormalBaeDetector:
    method __init__ (line 31) | def __init__(self, model):
    method from_pretrained (line 36) | def from_pretrained(cls, pretrained_model_or_path, filename=None, cach...
    method to (line 53) | def to(self, device):
    method __call__ (line 58) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/normalbae/nets/NNET.py
  class NNET (line 6) | class NNET(nn.Module):
    method __init__ (line 7) | def __init__(self, args):
    method get_1x_lr_params (line 12) | def get_1x_lr_params(self):  # lr/10 learning rate
    method get_10x_lr_params (line 15) | def get_10x_lr_params(self):  # lr learning rate
    method forward (line 18) | def forward(self, img, **kwargs):

FILE: modules/control/proc/normalbae/nets/baseline.py
  class NNET (line 9) | class NNET(nn.Module):
    method __init__ (line 10) | def __init__(self, args=None):
    method forward (line 15) | def forward(self, x, **kwargs):
    method get_1x_lr_params (line 25) | def get_1x_lr_params(self):  # lr/10 learning rate
    method get_10x_lr_params (line 28) | def get_10x_lr_params(self):  # lr learning rate
  class Encoder (line 35) | class Encoder(nn.Module):
    method __init__ (line 36) | def __init__(self):
    method forward (line 48) | def forward(self, x):
  class Decoder (line 60) | class Decoder(nn.Module):
    method __init__ (line 61) | def __init__(self, num_classes=4):
    method forward (line 70) | def forward(self, features):

FILE: modules/control/proc/normalbae/nets/submodules/decoder.py
  class Decoder (line 7) | class Decoder(nn.Module):
    method __init__ (line 8) | def __init__(self, args):
    method forward (line 59) | def forward(self, features, gt_norm_mask=None, mode='test'):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/activations/__init__.py
  function add_override_act_fn (line 65) | def add_override_act_fn(name, fn):
  function update_override_act_fn (line 70) | def update_override_act_fn(overrides):
  function clear_override_act_fn (line 76) | def clear_override_act_fn():
  function add_override_act_layer (line 81) | def add_override_act_layer(name, fn):
  function update_override_act_layer (line 85) | def update_override_act_layer(overrides):
  function clear_override_act_layer (line 91) | def clear_override_act_layer():
  function get_act_fn (line 96) | def get_act_fn(name='relu'):
  function get_act_layer (line 118) | def get_act_layer(name='relu'):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/activations/activations.py
  function swish (line 12) | def swish(x, inplace: bool = False):
  class Swish (line 19) | class Swish(nn.Module):
    method __init__ (line 20) | def __init__(self, inplace: bool = False):
    method forward (line 24) | def forward(self, x):
  function mish (line 28) | def mish(x, inplace: bool = False):
  class Mish (line 34) | class Mish(nn.Module):
    method __init__ (line 35) | def __init__(self, inplace: bool = False):
    method forward (line 39) | def forward(self, x):
  function sigmoid (line 43) | def sigmoid(x, inplace: bool = False):
  class Sigmoid (line 48) | class Sigmoid(nn.Module):
    method __init__ (line 49) | def __init__(self, inplace: bool = False):
    method forward (line 53) | def forward(self, x):
  function tanh (line 57) | def tanh(x, inplace: bool = False):
  class Tanh (line 62) | class Tanh(nn.Module):
    method __init__ (line 63) | def __init__(self, inplace: bool = False):
    method forward (line 67) | def forward(self, x):
  function hard_swish (line 71) | def hard_swish(x, inplace: bool = False):
  class HardSwish (line 76) | class HardSwish(nn.Module):
    method __init__ (line 77) | def __init__(self, inplace: bool = False):
    method forward (line 81) | def forward(self, x):
  function hard_sigmoid (line 85) | def hard_sigmoid(x, inplace: bool = False):
  class HardSigmoid (line 92) | class HardSigmoid(nn.Module):
    method __init__ (line 93) | def __init__(self, inplace: bool = False):
    method forward (line 97) | def forward(self, x):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/activations/activations_jit.py
  function swish_jit (line 22) | def swish_jit(x, inplace: bool = False):
  function mish_jit (line 30) | def mish_jit(x, _inplace: bool = False):
  class SwishJit (line 36) | class SwishJit(nn.Module):
    method __init__ (line 37) | def __init__(self, inplace: bool = False):
    method forward (line 40) | def forward(self, x):
  class MishJit (line 44) | class MishJit(nn.Module):
    method __init__ (line 45) | def __init__(self, inplace: bool = False):
    method forward (line 48) | def forward(self, x):
  function hard_sigmoid_jit (line 53) | def hard_sigmoid_jit(x, inplace: bool = False):
  class HardSigmoidJit (line 58) | class HardSigmoidJit(nn.Module):
    method __init__ (line 59) | def __init__(self, inplace: bool = False):
    method forward (line 62) | def forward(self, x):
  function hard_swish_jit (line 67) | def hard_swish_jit(x, inplace: bool = False):
  class HardSwishJit (line 72) | class HardSwishJit(nn.Module):
    method __init__ (line 73) | def __init__(self, inplace: bool = False):
    method forward (line 76) | def forward(self, x):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/activations/activations_me.py
  function swish_jit_fwd (line 22) | def swish_jit_fwd(x):
  function swish_jit_bwd (line 27) | def swish_jit_bwd(x, grad_output):
  class SwishJitAutoFn (line 32) | class SwishJitAutoFn(torch.autograd.Function):
    method forward (line 42) | def forward(ctx, x):
    method backward (line 47) | def backward(ctx, grad_output):
  function swish_me (line 52) | def swish_me(x, inplace=False):
  class SwishMe (line 56) | class SwishMe(nn.Module):
    method __init__ (line 57) | def __init__(self, inplace: bool = False):
    method forward (line 60) | def forward(self, x):
  function mish_jit_fwd (line 65) | def mish_jit_fwd(x):
  function mish_jit_bwd (line 70) | def mish_jit_bwd(x, grad_output):
  class MishJitAutoFn (line 76) | class MishJitAutoFn(torch.autograd.Function):
    method forward (line 81) | def forward(ctx, x):
    method backward (line 86) | def backward(ctx, grad_output):
  function mish_me (line 91) | def mish_me(x, inplace=False):
  class MishMe (line 95) | class MishMe(nn.Module):
    method __init__ (line 96) | def __init__(self, inplace: bool = False):
    method forward (line 99) | def forward(self, x):
  function hard_sigmoid_jit_fwd (line 104) | def hard_sigmoid_jit_fwd(x, inplace: bool = False):
  function hard_sigmoid_jit_bwd (line 109) | def hard_sigmoid_jit_bwd(x, grad_output):
  class HardSigmoidJitAutoFn (line 114) | class HardSigmoidJitAutoFn(torch.autograd.Function):
    method forward (line 116) | def forward(ctx, x):
    method backward (line 121) | def backward(ctx, grad_output):
  function hard_sigmoid_me (line 126) | def hard_sigmoid_me(x, inplace: bool = False):
  class HardSigmoidMe (line 130) | class HardSigmoidMe(nn.Module):
    method __init__ (line 131) | def __init__(self, inplace: bool = False):
    method forward (line 134) | def forward(self, x):
  function hard_swish_jit_fwd (line 139) | def hard_swish_jit_fwd(x):
  function hard_swish_jit_bwd (line 144) | def hard_swish_jit_bwd(x, grad_output):
  class HardSwishJitAutoFn (line 150) | class HardSwishJitAutoFn(torch.autograd.Function):
    method forward (line 153) | def forward(ctx, x):
    method backward (line 158) | def backward(ctx, grad_output):
  function hard_swish_me (line 163) | def hard_swish_me(x, inplace=False):
  class HardSwishMe (line 167) | class HardSwishMe(nn.Module):
    method __init__ (line 168) | def __init__(self, inplace: bool = False):
    method forward (line 171) | def forward(self, x):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/config.py
  function is_no_jit (line 25) | def is_no_jit():
  class set_no_jit (line 29) | class set_no_jit:
    method __init__ (line 30) | def __init__(self, mode: bool) -> None:
    method __enter__ (line 35) | def __enter__(self) -> None:
    method __exit__ (line 38) | def __exit__(self, *args: Any) -> bool:
  function is_exportable (line 44) | def is_exportable():
  class set_exportable (line 48) | class set_exportable:
    method __init__ (line 49) | def __init__(self, mode: bool) -> None:
    method __enter__ (line 54) | def __enter__(self) -> None:
    method __exit__ (line 57) | def __exit__(self, *args: Any) -> bool:
  function is_scriptable (line 63) | def is_scriptable():
  class set_scriptable (line 67) | class set_scriptable:
    method __init__ (line 68) | def __init__(self, mode: bool) -> None:
    method __enter__ (line 73) | def __enter__(self) -> None:
    method __exit__ (line 76) | def __exit__(self, *args: Any) -> bool:
  class set_layer_config (line 82) | class set_layer_config:
    method __init__ (line 86) | def __init__(
    method __enter__ (line 106) | def __enter__(self) -> None:
    method __exit__ (line 109) | def __exit__(self, *args: Any) -> bool:
  function layer_config_kwargs (line 118) | def layer_config_kwargs(kwargs):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/conv2d_layers.py
  function _ntuple (line 23) | def _ntuple(n):
  function _is_static_pad (line 37) | def _is_static_pad(kernel_size, stride=1, dilation=1, **_):
  function _get_padding (line 41) | def _get_padding(kernel_size, stride=1, dilation=1, **_):
  function _calc_same_pad (line 46) | def _calc_same_pad(i: int, k: int, s: int, d: int):
  function _same_pad_arg (line 50) | def _same_pad_arg(input_size, kernel_size, stride, dilation):
  function _split_channels (line 58) | def _split_channels(num_chan, num_groups):
  function conv2d_same (line 64) | def conv2d_same(
  class Conv2dSame (line 75) | class Conv2dSame(nn.Conv2d):
    method __init__ (line 80) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 85) | def forward(self, x):
  class Conv2dSameExport (line 89) | class Conv2dSameExport(nn.Conv2d):
    method __init__ (line 96) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 103) | def forward(self, x):
  function get_padding_value (line 116) | def get_padding_value(padding, kernel_size, **kwargs):
  function create_conv2d_pad (line 139) | def create_conv2d_pad(in_chs, out_chs, kernel_size, **kwargs):
  class MixedConv2d (line 153) | class MixedConv2d(nn.ModuleDict):
    method __init__ (line 159) | def __init__(self, in_channels, out_channels, kernel_size=3,
    method forward (line 179) | def forward(self, x):
  function get_condconv_initializer (line 186) | def get_condconv_initializer(initializer, num_experts, expert_shape):
  class CondConv2d (line 199) | class CondConv2d(nn.Module):
    method __init__ (line 208) | def __init__(self, in_channels, out_channels, kernel_size=3,
    method reset_parameters (line 238) | def reset_parameters(self):
    method forward (line 249) | def forward(self, x, routing_weights):
  function select_conv2d (line 290) | def select_conv2d(in_chs, out_chs, kernel_size, **kwargs):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/efficientnet_builder.py
  function get_bn_args_tf (line 30) | def get_bn_args_tf():
  function resolve_bn_args (line 34) | def resolve_bn_args(kwargs):
  function resolve_se_args (line 52) | def resolve_se_args(kwargs, in_chs, act_layer=None):
  function resolve_act_layer (line 67) | def resolve_act_layer(kwargs, default='relu'):
  function make_divisible (line 74) | def make_divisible(v: int, divisor: int = 8, min_value: int = None):
  function round_channels (line 82) | def round_channels(channels, multiplier=1.0, divisor=8, channel_min=None):
  function drop_connect (line 90) | def drop_connect(inputs, training: bool = False, drop_connect_rate: floa...
  class SqueezeExcite (line 103) | class SqueezeExcite(nn.Module):
    method __init__ (line 105) | def __init__(self, in_chs, se_ratio=0.25, reduced_base_chs=None, act_l...
    method forward (line 113) | def forward(self, x):
  class ConvBnAct (line 122) | class ConvBnAct(nn.Module):
    method __init__ (line 123) | def __init__(self, in_chs, out_chs, kernel_size,
    method forward (line 132) | def forward(self, x):
  class DepthwiseSeparableConv (line 139) | class DepthwiseSeparableConv(nn.Module):
    method __init__ (line 144) | def __init__(self, in_chs, out_chs, dw_kernel_size=3,
    method forward (line 170) | def forward(self, x):
  class InvertedResidual (line 190) | class InvertedResidual(nn.Module):
    method __init__ (line 193) | def __init__(self, in_chs, out_chs, dw_kernel_size=3,
    method forward (line 227) | def forward(self, x):
  class CondConvResidual (line 254) | class CondConvResidual(InvertedResidual):
    method __init__ (line 257) | def __init__(self, in_chs, out_chs, dw_kernel_size=3,
    method forward (line 275) | def forward(self, x):
  class EdgeResidual (line 306) | class EdgeResidual(nn.Module):
    method __init__ (line 309) | def __init__(self, in_chs, out_chs, exp_kernel_size=3, exp_ratio=1.0, ...
    method forward (line 334) | def forward(self, x):
  class EfficientNetBuilder (line 357) | class EfficientNetBuilder:
    method __init__ (line 367) | def __init__(self, channel_multiplier=1.0, channel_divisor=8, channel_...
    method _round_channels (line 385) | def _round_channels(self, chs):
    method _make_block (line 388) | def _make_block(self, ba):
    method _make_stack (line 423) | def _make_stack(self, stack_args):
    method __call__ (line 435) | def __call__(self, in_chs, block_args):
  function _parse_ksize (line 456) | def _parse_ksize(ss):
  function _decode_block_str (line 463) | def _decode_block_str(block_str):
  function _scale_stage_depth (line 582) | def _scale_stage_depth(stack_args, repeats, depth_multiplier=1.0, depth_...
  function decode_arch_def (line 620) | def decode_arch_def(arch_def, depth_multiplier=1.0, depth_trunc='ceil', ...
  function initialize_weight_goog (line 640) | def initialize_weight_goog(m, n='', fix_group_fanout=True):
  function initialize_weight_default (line 672) | def initialize_weight_default(m, n=''):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/gen_efficientnet.py
  class GenEfficientNet (line 215) | class GenEfficientNet(nn.Module):
    method __init__ (line 226) | def __init__(self, block_args, num_classes=1000, in_chans=3, num_featu...
    method features (line 259) | def features(self, x):
    method as_sequential (line 269) | def as_sequential(self):
    method forward (line 277) | def forward(self, x):
  function _create_model (line 286) | def _create_model(model_kwargs, variant, pretrained=False):
  function _gen_mnasnet_a1 (line 296) | def _gen_mnasnet_a1(variant, channel_multiplier=1.0, pretrained=False, *...
  function _gen_mnasnet_b1 (line 334) | def _gen_mnasnet_b1(variant, channel_multiplier=1.0, pretrained=False, *...
  function _gen_mnasnet_small (line 372) | def _gen_mnasnet_small(variant, channel_multiplier=1.0, pretrained=False...
  function _gen_mobilenet_v2 (line 403) | def _gen_mobilenet_v2(
  function _gen_fbnetc (line 433) | def _gen_fbnetc(variant, channel_multiplier=1.0, pretrained=False, **kwa...
  function _gen_spnasnet (line 465) | def _gen_spnasnet(variant, channel_multiplier=1.0, pretrained=False, **k...
  function _gen_efficientnet (line 502) | def _gen_efficientnet(variant, channel_multiplier=1.0, depth_multiplier=...
  function _gen_efficientnet_edge (line 548) | def _gen_efficientnet_edge(variant, channel_multiplier=1.0, depth_multip...
  function _gen_efficientnet_condconv (line 573) | def _gen_efficientnet_condconv(
  function _gen_efficientnet_lite (line 599) | def _gen_efficientnet_lite(variant, channel_multiplier=1.0, depth_multip...
  function _gen_mixnet_s (line 641) | def _gen_mixnet_s(variant, channel_multiplier=1.0, pretrained=False, **k...
  function _gen_mixnet_m (line 676) | def _gen_mixnet_m(variant, channel_multiplier=1.0, depth_multiplier=1.0,...
  function mnasnet_050 (line 711) | def mnasnet_050(pretrained=False, **kwargs):
  function mnasnet_075 (line 717) | def mnasnet_075(pretrained=False, **kwargs):
  function mnasnet_100 (line 723) | def mnasnet_100(pretrained=False, **kwargs):
  function mnasnet_b1 (line 729) | def mnasnet_b1(pretrained=False, **kwargs):
  function mnasnet_140 (line 734) | def mnasnet_140(pretrained=False, **kwargs):
  function semnasnet_050 (line 740) | def semnasnet_050(pretrained=False, **kwargs):
  function semnasnet_075 (line 746) | def semnasnet_075(pretrained=False, **kwargs):
  function semnasnet_100 (line 752) | def semnasnet_100(pretrained=False, **kwargs):
  function mnasnet_a1 (line 758) | def mnasnet_a1(pretrained=False, **kwargs):
  function semnasnet_140 (line 763) | def semnasnet_140(pretrained=False, **kwargs):
  function mnasnet_small (line 769) | def mnasnet_small(pretrained=False, **kwargs):
  function mobilenetv2_100 (line 775) | def mobilenetv2_100(pretrained=False, **kwargs):
  function mobilenetv2_140 (line 781) | def mobilenetv2_140(pretrained=False, **kwargs):
  function mobilenetv2_110d (line 787) | def mobilenetv2_110d(pretrained=False, **kwargs):
  function mobilenetv2_120d (line 794) | def mobilenetv2_120d(pretrained=False, **kwargs):
  function fbnetc_100 (line 801) | def fbnetc_100(pretrained=False, **kwargs):
  function spnasnet_100 (line 810) | def spnasnet_100(pretrained=False, **kwargs):
  function efficientnet_b0 (line 816) | def efficientnet_b0(pretrained=False, **kwargs):
  function efficientnet_b1 (line 824) | def efficientnet_b1(pretrained=False, **kwargs):
  function efficientnet_b2 (line 832) | def efficientnet_b2(pretrained=False, **kwargs):
  function efficientnet_b3 (line 840) | def efficientnet_b3(pretrained=False, **kwargs):
  function efficientnet_b4 (line 848) | def efficientnet_b4(pretrained=False, **kwargs):
  function efficientnet_b5 (line 856) | def efficientnet_b5(pretrained=False, **kwargs):
  function efficientnet_b6 (line 864) | def efficientnet_b6(pretrained=False, **kwargs):
  function efficientnet_b7 (line 872) | def efficientnet_b7(pretrained=False, **kwargs):
  function efficientnet_b8 (line 880) | def efficientnet_b8(pretrained=False, **kwargs):
  function efficientnet_l2 (line 888) | def efficientnet_l2(pretrained=False, **kwargs):
  function efficientnet_es (line 896) | def efficientnet_es(pretrained=False, **kwargs):
  function efficientnet_em (line 903) | def efficientnet_em(pretrained=False, **kwargs):
  function efficientnet_el (line 910) | def efficientnet_el(pretrained=False, **kwargs):
  function efficientnet_cc_b0_4e (line 917) | def efficientnet_cc_b0_4e(pretrained=False, **kwargs):
  function efficientnet_cc_b0_8e (line 925) | def efficientnet_cc_b0_8e(pretrained=False, **kwargs):
  function efficientnet_cc_b1_8e (line 934) | def efficientnet_cc_b1_8e(pretrained=False, **kwargs):
  function efficientnet_lite0 (line 943) | def efficientnet_lite0(pretrained=False, **kwargs):
  function efficientnet_lite1 (line 950) | def efficientnet_lite1(pretrained=False, **kwargs):
  function efficientnet_lite2 (line 957) | def efficientnet_lite2(pretrained=False, **kwargs):
  function efficientnet_lite3 (line 964) | def efficientnet_lite3(pretrained=False, **kwargs):
  function efficientnet_lite4 (line 971) | def efficientnet_lite4(pretrained=False, **kwargs):
  function tf_efficientnet_b0 (line 978) | def tf_efficientnet_b0(pretrained=False, **kwargs):
  function tf_efficientnet_b1 (line 987) | def tf_efficientnet_b1(pretrained=False, **kwargs):
  function tf_efficientnet_b2 (line 996) | def tf_efficientnet_b2(pretrained=False, **kwargs):
  function tf_efficientnet_b3 (line 1005) | def tf_efficientnet_b3(pretrained=False, **kwargs):
  function tf_efficientnet_b4 (line 1014) | def tf_efficientnet_b4(pretrained=False, **kwargs):
  function tf_efficientnet_b5 (line 1023) | def tf_efficientnet_b5(pretrained=False, **kwargs):
  function tf_efficientnet_b6 (line 1032) | def tf_efficientnet_b6(pretrained=False, **kwargs):
  function tf_efficientnet_b7 (line 1041) | def tf_efficientnet_b7(pretrained=False, **kwargs):
  function tf_efficientnet_b8 (line 1050) | def tf_efficientnet_b8(pretrained=False, **kwargs):
  function tf_efficientnet_b0_ap (line 1059) | def tf_efficientnet_b0_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b1_ap (line 1070) | def tf_efficientnet_b1_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b2_ap (line 1081) | def tf_efficientnet_b2_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b3_ap (line 1092) | def tf_efficientnet_b3_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b4_ap (line 1103) | def tf_efficientnet_b4_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b5_ap (line 1114) | def tf_efficientnet_b5_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b6_ap (line 1125) | def tf_efficientnet_b6_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b7_ap (line 1137) | def tf_efficientnet_b7_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b8_ap (line 1149) | def tf_efficientnet_b8_ap(pretrained=False, **kwargs):
  function tf_efficientnet_b0_ns (line 1161) | def tf_efficientnet_b0_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b1_ns (line 1172) | def tf_efficientnet_b1_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b2_ns (line 1183) | def tf_efficientnet_b2_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b3_ns (line 1194) | def tf_efficientnet_b3_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b4_ns (line 1205) | def tf_efficientnet_b4_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b5_ns (line 1216) | def tf_efficientnet_b5_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b6_ns (line 1227) | def tf_efficientnet_b6_ns(pretrained=False, **kwargs):
  function tf_efficientnet_b7_ns (line 1239) | def tf_efficientnet_b7_ns(pretrained=False, **kwargs):
  function tf_efficientnet_l2_ns_475 (line 1251) | def tf_efficientnet_l2_ns_475(pretrained=False, **kwargs):
  function tf_efficientnet_l2_ns (line 1263) | def tf_efficientnet_l2_ns(pretrained=False, **kwargs):
  function tf_efficientnet_es (line 1275) | def tf_efficientnet_es(pretrained=False, **kwargs):
  function tf_efficientnet_em (line 1284) | def tf_efficientnet_em(pretrained=False, **kwargs):
  function tf_efficientnet_el (line 1293) | def tf_efficientnet_el(pretrained=False, **kwargs):
  function tf_efficientnet_cc_b0_4e (line 1302) | def tf_efficientnet_cc_b0_4e(pretrained=False, **kwargs):
  function tf_efficientnet_cc_b0_8e (line 1311) | def tf_efficientnet_cc_b0_8e(pretrained=False, **kwargs):
  function tf_efficientnet_cc_b1_8e (line 1321) | def tf_efficientnet_cc_b1_8e(pretrained=False, **kwargs):
  function tf_efficientnet_lite0 (line 1331) | def tf_efficientnet_lite0(pretrained=False, **kwargs):
  function tf_efficientnet_lite1 (line 1340) | def tf_efficientnet_lite1(pretrained=False, **kwargs):
  function tf_efficientnet_lite2 (line 1349) | def tf_efficientnet_lite2(pretrained=False, **kwargs):
  function tf_efficientnet_lite3 (line 1358) | def tf_efficientnet_lite3(pretrained=False, **kwargs):
  function tf_efficientnet_lite4 (line 1367) | def tf_efficientnet_lite4(pretrained=False, **kwargs):
  function mixnet_s (line 1376) | def mixnet_s(pretrained=False, **kwargs):
  function mixnet_m (line 1385) | def mixnet_m(pretrained=False, **kwargs):
  function mixnet_l (line 1394) | def mixnet_l(pretrained=False, **kwargs):
  function mixnet_xl (line 1403) | def mixnet_xl(pretrained=False, **kwargs):
  function mixnet_xxl (line 1413) | def mixnet_xxl(pretrained=False, **kwargs):
  function tf_mixnet_s (line 1423) | def tf_mixnet_s(pretrained=False, **kwargs):
  function tf_mixnet_m (line 1433) | def tf_mixnet_m(pretrained=False, **kwargs):
  function tf_mixnet_l (line 1443) | def tf_mixnet_l(pretrained=False, **kwargs):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/helpers.py
  function load_checkpoint (line 13) | def load_checkpoint(model, checkpoint_path):
  function load_pretrained (line 34) | def load_pretrained(model, url, filter_fn=None, strict=True):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/mobilenetv3.py
  class MobileNetV3 (line 48) | class MobileNetV3(nn.Module):
    method __init__ (line 57) | def __init__(self, block_args, num_classes=1000, in_chans=3, stem_size...
    method as_sequential (line 86) | def as_sequential(self):
    method features (line 94) | def features(self, x):
    method forward (line 104) | def forward(self, x):
  function _create_model (line 112) | def _create_model(model_kwargs, variant, pretrained=False):
  function _gen_mobilenet_v3_rw (line 122) | def _gen_mobilenet_v3_rw(variant, channel_multiplier=1.0, pretrained=Fal...
  function _gen_mobilenet_v3 (line 171) | def _gen_mobilenet_v3(variant, channel_multiplier=1.0, pretrained=False,...
  function mobilenetv3_rw (line 268) | def mobilenetv3_rw(pretrained=False, **kwargs):
  function mobilenetv3_large_075 (line 280) | def mobilenetv3_large_075(pretrained=False, **kwargs):
  function mobilenetv3_large_100 (line 287) | def mobilenetv3_large_100(pretrained=False, **kwargs):
  function mobilenetv3_large_minimal_100 (line 294) | def mobilenetv3_large_minimal_100(pretrained=False, **kwargs):
  function mobilenetv3_small_075 (line 301) | def mobilenetv3_small_075(pretrained=False, **kwargs):
  function mobilenetv3_small_100 (line 307) | def mobilenetv3_small_100(pretrained=False, **kwargs):
  function mobilenetv3_small_minimal_100 (line 313) | def mobilenetv3_small_minimal_100(pretrained=False, **kwargs):
  function tf_mobilenetv3_large_075 (line 319) | def tf_mobilenetv3_large_075(pretrained=False, **kwargs):
  function tf_mobilenetv3_large_100 (line 327) | def tf_mobilenetv3_large_100(pretrained=False, **kwargs):
  function tf_mobilenetv3_large_minimal_100 (line 335) | def tf_mobilenetv3_large_minimal_100(pretrained=False, **kwargs):
  function tf_mobilenetv3_small_075 (line 343) | def tf_mobilenetv3_small_075(pretrained=False, **kwargs):
  function tf_mobilenetv3_small_100 (line 351) | def tf_mobilenetv3_small_100(pretrained=False, **kwargs):
  function tf_mobilenetv3_small_minimal_100 (line 359) | def tf_mobilenetv3_small_minimal_100(pretrained=False, **kwargs):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/geffnet/model_factory.py
  function create_model (line 8) | def create_model(

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/utils.py
  class AverageMeter (line 4) | class AverageMeter:
    method __init__ (line 6) | def __init__(self):
    method reset (line 9) | def reset(self):
    method update (line 15) | def update(self, val, n=1):
  function accuracy (line 22) | def accuracy(output, target, topk=(1,)):
  function get_outdir (line 38) | def get_outdir(path, *paths, inc=False):

FILE: modules/control/proc/normalbae/nets/submodules/efficientnet_repo/validate.py
  function main (line 66) | def main():

FILE: modules/control/proc/normalbae/nets/submodules/encoder.py
  class Encoder (line 6) | class Encoder(nn.Module):
    method __init__ (line 7) | def __init__(self):
    method forward (line 20) | def forward(self, x):

FILE: modules/control/proc/normalbae/nets/submodules/submodules.py
  class UpSampleBN (line 10) | class UpSampleBN(nn.Module):
    method __init__ (line 11) | def __init__(self, skip_input, output_features):
    method forward (line 21) | def forward(self, x, concat_with):
  class UpSampleGN (line 28) | class UpSampleGN(nn.Module):
    method __init__ (line 29) | def __init__(self, skip_input, output_features):
    method forward (line 39) | def forward(self, x, concat_with):
  class Conv2d (line 46) | class Conv2d(nn.Conv2d):
    method __init__ (line 47) | def __init__(self, in_channels, out_channels, kernel_size, stride=1,
    method forward (line 52) | def forward(self, x):
  function norm_normalize (line 64) | def norm_normalize(norm_out):
  function sample_points (line 74) | def sample_points(init_normal, gt_norm_mask, sampling_ratio, beta):

FILE: modules/control/proc/openpose/__init__.py
  class PoseResult (line 29) | class PoseResult(NamedTuple):
  function draw_poses (line 35) | def draw_poses(poses: List[PoseResult], H, W, draw_body=True, draw_hand=...
  class OpenposeDetector (line 66) | class OpenposeDetector:
    method __init__ (line 73) | def __init__(self, body_estimation, hand_estimation=None, face_estimat...
    method from_pretrained (line 79) | def from_pretrained(cls, pretrained_model_or_path, filename=None, hand...
    method to (line 109) | def to(self, device):
    method detect_hands (line 115) | def detect_hands(self, body: BodyResult, oriImg) -> Tuple[Union[HandRe...
    method detect_face (line 137) | def detect_face(self, body: BodyResult, oriImg) -> Union[FaceResult, N...
    method detect_poses (line 156) | def detect_poses(self, oriImg, include_hand=False, include_face=False)...
    method __call__ (line 194) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/openpose/body.py
  class Keypoint (line 10) | class Keypoint(NamedTuple):
  class BodyResult (line 17) | class BodyResult(NamedTuple):
  class Body (line 28) | class Body(object):
    method __init__ (line 29) | def __init__(self, model_path):
    method to (line 35) | def to(self, device):
    method __call__ (line 39) | def __call__(self, oriImg):
    method format_body_result (line 224) | def format_body_result(candidate: np.ndarray, subset: np.ndarray) -> L...

FILE: modules/control/proc/openpose/face.py
  class FaceNet (line 10) | class FaceNet(Module):
    method __init__ (line 12) | def __init__(self):
    method forward (line 189) | def forward(self, x):
  class Face (line 303) | class Face(object):
    method __init__ (line 314) | def __init__(self, face_model_path,
    method to (line 325) | def to(self, device):
    method __call__ (line 329) | def __call__(self, face_img):
    method compute_peaks_from_heatmaps (line 345) | def compute_peaks_from_heatmaps(self, heatmaps):

FILE: modules/control/proc/openpose/hand.py
  class Hand (line 11) | class Hand(object):
    method __init__ (line 12) | def __init__(self, model_path):
    method to (line 18) | def to(self, device):
    method __call__ (line 22) | def __call__(self, oriImgRaw):

FILE: modules/control/proc/openpose/model.py
  function make_layers (line 5) | def make_layers(block, no_relu_layers):
  class bodypose_model (line 22) | class bodypose_model(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 112) | def forward(self, x):
  class handpose_model (line 141) | class handpose_model(nn.Module):
    method __init__ (line 142) | def __init__(self):
    method forward (line 202) | def forward(self, x):

FILE: modules/control/proc/openpose/util.py
  function smart_resize (line 10) | def smart_resize(x, s):
  function smart_resize_k (line 24) | def smart_resize_k(x, fx, fy):
  function padRightDownCorner (line 38) | def padRightDownCorner(img, stride, padValue):
  function transfer (line 61) | def transfer(model, model_weights):
  function draw_bodypose (line 68) | def draw_bodypose(canvas: np.ndarray, keypoints: List[Keypoint]) -> np.n...
  function draw_handpose (line 125) | def draw_handpose(canvas: np.ndarray, keypoints: Union[List[Keypoint], N...
  function draw_facepose (line 171) | def draw_facepose(canvas: np.ndarray, keypoints: Union[List[Keypoint], N...
  function handDetect (line 201) | def handDetect(body: BodyResult, oriImg) -> List[Tuple[int, int, int, bo...
  function faceDetect (line 299) | def faceDetect(body: BodyResult, oriImg) -> Union[Tuple[int, int, int], ...
  function npmax (line 381) | def npmax(array):

FILE: modules/control/proc/pidi.py
  class PidiNetDetector (line 14) | class PidiNetDetector:
    method __init__ (line 15) | def __init__(self, model):
    method from_pretrained (line 19) | def from_pretrained(cls, pretrained_model_or_path, filename=None, cach...
    method to (line 30) | def to(self, device):
    method __call__ (line 34) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/pidi_model.py
  function img2tensor (line 15) | def img2tensor(imgs, bgr2rgb=True, float32=True):
  function createConvFunc (line 298) | def createConvFunc(op_type):
  class Conv2d (line 349) | class Conv2d(nn.Module):
    method __init__ (line 350) | def __init__(self, pdc, in_channels, out_channels, kernel_size, stride...
    method reset_parameters (line 371) | def reset_parameters(self):
    method forward (line 378) | def forward(self, input):
  class CSAM (line 382) | class CSAM(nn.Module):
    method __init__ (line 386) | def __init__(self, channels):
    method forward (line 396) | def forward(self, x):
  class CDCM (line 404) | class CDCM(nn.Module):
    method __init__ (line 408) | def __init__(self, in_channels, out_channels):
    method forward (line 419) | def forward(self, x):
  class MapReduce (line 429) | class MapReduce(nn.Module):
    method __init__ (line 433) | def __init__(self, channels):
    method forward (line 438) | def forward(self, x):
  class PDCBlock (line 442) | class PDCBlock(nn.Module):
    method __init__ (line 443) | def __init__(self, pdc, inplane, ouplane, stride=1):
    method forward (line 455) | def forward(self, x):
  class PDCBlock_converted (line 466) | class PDCBlock_converted(nn.Module):
    method __init__ (line 471) | def __init__(self, pdc, inplane, ouplane, stride=1):
    method forward (line 485) | def forward(self, x):
  class PiDiNet (line 496) | class PiDiNet(nn.Module):
    method __init__ (line 497) | def __init__(self, inplane, pdcs, dil=None, sa=False, convert=False):
    method get_weights (line 576) | def get_weights(self):
    method forward (line 590) | def forward(self, x):
  function config_model (line 649) | def config_model(model):
  function pidinet (line 664) | def pidinet():

FILE: modules/control/proc/segment_anything/__init__.py
  class SamDetector (line 21) | class SamDetector:
    method __init__ (line 22) | def __init__(self, mask_generator: SamAutomaticMaskGenerator = None):
    method from_pretrained (line 26) | def from_pretrained(cls, model_path, filename, model_type, cache_dir=N...
    method show_anns (line 38) | def show_anns(self, anns):
    method __call__ (line 54) | def __call__(self, input_image: Union[np.ndarray, Image.Image]=None, d...

FILE: modules/control/proc/segment_anything/automatic_mask_generator.py
  class SamAutomaticMaskGenerator (line 33) | class SamAutomaticMaskGenerator:
    method __init__ (line 34) | def __init__(
    method generate (line 128) | def generate(self, image: np.ndarray) -> List[Dict[str, Any]]:
    method _generate_masks (line 188) | def _generate_masks(self, image: np.ndarray) -> MaskData:
    method _process_crop (line 216) | def _process_crop(
    method _process_batch (line 257) | def _process_batch(
    method postprocess_small_regions (line 315) | def postprocess_small_regions(

FILE: modules/control/proc/segment_anything/build_sam.py
  function build_sam_vit_h (line 14) | def build_sam_vit_h(checkpoint=None):
  function build_sam_vit_l (line 27) | def build_sam_vit_l(checkpoint=None):
  function build_sam_vit_b (line 37) | def build_sam_vit_b(checkpoint=None):
  function build_sam_vit_t (line 47) | def build_sam_vit_t(checkpoint=None):
  function _build_sam (line 105) | def _build_sam(

FILE: modules/control/proc/segment_anything/modeling/common.py
  class MLPBlock (line 13) | class MLPBlock(nn.Module):
    method __init__ (line 14) | def __init__(
    method forward (line 25) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class LayerNorm2d (line 31) | class LayerNorm2d(nn.Module):
    method __init__ (line 32) | def __init__(self, num_channels: int, eps: float = 1e-6) -> None:
    method forward (line 38) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: modules/control/proc/segment_anything/modeling/image_encoder.py
  class ImageEncoderViT (line 17) | class ImageEncoderViT(nn.Module):
    method __init__ (line 18) | def __init__(
    method forward (line 106) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Block (line 119) | class Block(nn.Module):
    method __init__ (line 122) | def __init__(
    method forward (line 166) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Attention (line 185) | class Attention(nn.Module):
    method __init__ (line 188) | def __init__(
    method forward (line 224) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  function window_partition (line 243) | def window_partition(x: torch.Tensor, window_size: int) -> Tuple[torch.T...
  function window_unpartition (line 267) | def window_unpartition(
  function get_rel_pos (line 292) | def get_rel_pos(q_size: int, k_size: int, rel_pos: torch.Tensor) -> torc...
  function add_decomposed_rel_pos (line 325) | def add_decomposed_rel_pos(
  class PatchEmbed (line 364) | class PatchEmbed(nn.Module):
    method __init__ (line 369) | def __init__(
    method forward (line 391) | def forward(self, x: torch.Tensor) -> torch.Tensor:

FILE: modules/control/proc/segment_anything/modeling/mask_decoder.py
  class MaskDecoder (line 16) | class MaskDecoder(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 71) | def forward(
    method predict_masks (line 112) | def predict_masks(
  class MLP (line 154) | class MLP(nn.Module):
    method __init__ (line 155) | def __init__(
    method forward (line 171) | def forward(self, x):

FILE: modules/control/proc/segment_anything/modeling/prompt_encoder.py
  class PromptEncoder (line 16) | class PromptEncoder(nn.Module):
    method __init__ (line 17) | def __init__(
    method get_dense_pe (line 62) | def get_dense_pe(self) -> torch.Tensor:
    method _embed_points (line 73) | def _embed_points(
    method _embed_boxes (line 93) | def _embed_boxes(self, boxes: torch.Tensor) -> torch.Tensor:
    method _embed_masks (line 102) | def _embed_masks(self, masks: torch.Tensor) -> torch.Tensor:
    method _get_batch_size (line 107) | def _get_batch_size(
    method _get_device (line 125) | def _get_device(self) -> torch.device:
    method forward (line 128) | def forward(
  class PositionEmbeddingRandom (line 171) | class PositionEmbeddingRandom(nn.Module):
    method __init__ (line 176) | def __init__(self, num_pos_feats: int = 64, scale: Optional[float] = N...
    method _pe_encoding (line 185) | def _pe_encoding(self, coords: torch.Tensor) -> torch.Tensor:
    method forward (line 194) | def forward(self, size: Tuple[int, int]) -> torch.Tensor:
    method forward_with_coords (line 207) | def forward_with_coords(

FILE: modules/control/proc/segment_anything/modeling/sam.py
  class Sam (line 19) | class Sam(nn.Module):
    method __init__ (line 23) | def __init__(
    method device (line 55) | def device(self) -> Any:
    method forward (line 58) | def forward(
    method postprocess_masks (line 137) | def postprocess_masks(
    method preprocess (line 168) | def preprocess(self, x: torch.Tensor) -> torch.Tensor:

FILE: modules/control/proc/segment_anything/modeling/tiny_vit_sam.py
  class Conv2d_BN (line 21) | class Conv2d_BN(torch.nn.Sequential):
    method __init__ (line 22) | def __init__(self, a, b, ks=1, stride=1, pad=0, dilation=1,
    method fuse (line 32) | def fuse(self):
  class DropPath (line 45) | class DropPath(TimmDropPath):
    method __init__ (line 46) | def __init__(self, drop_prob=None):
    method __repr__ (line 50) | def __repr__(self):
  class PatchEmbed (line 56) | class PatchEmbed(nn.Module):
    method __init__ (line 57) | def __init__(self, in_chans, embed_dim, resolution, activation):
    method forward (line 72) | def forward(self, x):
  class MBConv (line 76) | class MBConv(nn.Module):
    method __init__ (line 77) | def __init__(self, in_chans, out_chans, expand_ratio,
    method forward (line 98) | def forward(self, x):
  class PatchMerging (line 117) | class PatchMerging(nn.Module):
    method __init__ (line 118) | def __init__(self, input_resolution, dim, out_dim, activation):
    method forward (line 132) | def forward(self, x):
  class ConvLayer (line 149) | class ConvLayer(nn.Module):
    method __init__ (line 150) | def __init__(self, dim, input_resolution, depth,
    method forward (line 177) | def forward(self, x):
  class Mlp (line 188) | class Mlp(nn.Module):
    method __init__ (line 189) | def __init__(self, in_features, hidden_features=None,
    method forward (line 200) | def forward(self, x):
  class Attention (line 211) | class Attention(torch.nn.Module):
    method __init__ (line 212) | def __init__(self, dim, key_dim, num_heads=8,
    method train (line 249) | def train(self, mode=True):
    method forward (line 256) | def forward(self, x):  # x (B,N,C)
  class TinyViTBlock (line 283) | class TinyViTBlock(nn.Module):
    method __init__ (line 299) | def __init__(self, dim, input_resolution, num_heads, window_size=7,
    method forward (line 331) | def forward(self, x):
    method extra_repr (line 374) | def extra_repr(self) -> str:
  class BasicLayer (line 378) | class BasicLayer(nn.Module):
    method __init__ (line 397) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
    method forward (line 431) | def forward(self, x):
    method extra_repr (line 441) | def extra_repr(self) -> str:
  class LayerNorm2d (line 444) | class LayerNorm2d(nn.Module):
    method __init__ (line 445) | def __init__(self, num_channels: int, eps: float = 1e-6) -> None:
    method forward (line 451) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class TinyViT (line 457) | class TinyViT(nn.Module):
    method __init__ (line 458) | def __init__(self, img_size=224, in_chans=3, num_classes=1000,
    method set_layer_lr_decay (line 556) | def set_layer_lr_decay(self, layer_lr_decay):
    method _init_weights (line 590) | def _init_weights(self, m):
    method no_weight_decay_keywords (line 600) | def no_weight_decay_keywords(self):
    method forward_features (line 603) | def forward_features(self, x):
    method forward (line 619) | def forward(self, x):
  function register_tiny_vit_model (line 637) | def register_tiny_vit_model(fn):
  function tiny_vit_5m_224 (line 663) | def tiny_vit_5m_224(pretrained=False, num_classes=1000, drop_path_rate=0...
  function tiny_vit_11m_224 (line 675) | def tiny_vit_11m_224(pretrained=False, num_classes=1000, drop_path_rate=...
  function tiny_vit_21m_224 (line 687) | def tiny_vit_21m_224(pretrained=False, num_classes=1000, drop_path_rate=...
  function tiny_vit_21m_384 (line 699) | def tiny_vit_21m_384(pretrained=False, num_classes=1000, drop_path_rate=...
  function tiny_vit_21m_512 (line 712) | def tiny_vit_21m_512(pretrained=False, num_classes=1000, drop_path_rate=...

FILE: modules/control/proc/segment_anything/modeling/transformer.py
  class TwoWayTransformer (line 16) | class TwoWayTransformer(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 62) | def forward(
  class TwoWayAttentionBlock (line 109) | class TwoWayAttentionBlock(nn.Module):
    method __init__ (line 110) | def __init__(
    method forward (line 151) | def forward(
  class Attention (line 185) | class Attention(nn.Module):
    method __init__ (line 191) | def __init__(
    method _separate_heads (line 208) | def _separate_heads(self, x: Tensor, num_heads: int) -> Tensor:
    method _recombine_heads (line 213) | def _recombine_heads(self, x: Tensor) -> Tensor:
    method forward (line 218) | def forward(self, q: Tensor, k: Tensor, v: Tensor) -> Tensor:

FILE: modules/control/proc/segment_anything/predictor.py
  class SamPredictor (line 14) | class SamPredictor:
    method __init__ (line 15) | def __init__(
    method set_image (line 31) | def set_image(
    method set_torch_image (line 59) | def set_torch_image(
    method predict (line 88) | def predict(
    method predict_torch (line 164) | def predict_torch(
    method get_image_embedding (line 240) | def get_image_embedding(self) -> torch.Tensor:
    method device (line 254) | def device(self) -> torch.device:
    method reset_image (line 257) | def reset_image(self) -> None:

FILE: modules/control/proc/segment_anything/utils/amg.py
  class MaskData (line 16) | class MaskData:
    method __init__ (line 22) | def __init__(self, **kwargs) -> None:
    method __setitem__ (line 29) | def __setitem__(self, key: str, item: Any) -> None:
    method __delitem__ (line 35) | def __delitem__(self, key: str) -> None:
    method __getitem__ (line 38) | def __getitem__(self, key: str) -> Any:
    method items (line 41) | def items(self) -> ItemsView[str, Any]:
    method filter (line 44) | def filter(self, keep: torch.Tensor) -> None:
    method cat (line 59) | def cat(self, new_stats: "MaskData") -> None:
    method to_numpy (line 72) | def to_numpy(self) -> None:
  function is_box_near_crop_edge (line 78) | def is_box_near_crop_edge(
  function box_xyxy_to_xywh (line 91) | def box_xyxy_to_xywh(box_xyxy: torch.Tensor) -> torch.Tensor:
  function batch_iterator (line 98) | def batch_iterator(batch_size: int, *args) -> Generator[List[Any], None,...
  function mask_to_rle_pytorch (line 107) | def mask_to_rle_pytorch(tensor: torch.Tensor) -> List[Dict[str, Any]]:
  function rle_to_mask (line 138) | def rle_to_mask(rle: Dict[str, Any]) -> np.ndarray:
  function area_from_rle (line 152) | def area_from_rle(rle: Dict[str, Any]) -> int:
  function calculate_stability_score (line 156) | def calculate_stability_score(
  function build_point_grid (line 179) | def build_point_grid(n_per_side: int) -> np.ndarray:
  function build_all_layer_point_grids (line 189) | def build_all_layer_point_grids(
  function generate_crop_boxes (line 200) | def generate_crop_boxes(
  function uncrop_boxes_xyxy (line 237) | def uncrop_boxes_xyxy(boxes: torch.Tensor, crop_box: List[int]) -> torch...
  function uncrop_points (line 246) | def uncrop_points(points: torch.Tensor, crop_box: List[int]) -> torch.Te...
  function uncrop_masks (line 255) | def uncrop_masks(
  function remove_small_regions (line 267) | def remove_small_regions(
  function coco_encode_rle (line 294) | def coco_encode_rle(uncompressed_rle: Dict[str, Any]) -> Dict[str, Any]:
  function batched_mask_to_box (line 303) | def batched_mask_to_box(masks: torch.Tensor) -> torch.Tensor:

FILE: modules/control/proc/segment_anything/utils/onnx.py
  class SamOnnxModel (line 17) | class SamOnnxModel(nn.Module):
    method __init__ (line 25) | def __init__(
    method resize_longest_image_size (line 42) | def resize_longest_image_size(
    method _embed_points (line 51) | def _embed_points(self, point_coords: torch.Tensor, point_labels: torc...
    method _embed_masks (line 69) | def _embed_masks(self, input_mask: torch.Tensor, has_mask_input: torch...
    method mask_postprocessing (line 76) | def mask_postprocessing(self, masks: torch.Tensor, orig_im_size: torch...
    method select_masks (line 92) | def select_masks(
    method forward (line 107) | def forward(

FILE: modules/control/proc/segment_anything/utils/transforms.py
  class ResizeLongestSide (line 16) | class ResizeLongestSide:
    method __init__ (line 23) | def __init__(self, target_length: int) -> None:
    method apply_image (line 26) | def apply_image(self, image: np.ndarray) -> np.ndarray:
    method apply_coords (line 33) | def apply_coords(self, coords: np.ndarray, original_size: Tuple[int, ....
    method apply_boxes (line 47) | def apply_boxes(self, boxes: np.ndarray, original_size: Tuple[int, ......
    method apply_image_torch (line 55) | def apply_image_torch(self, image: torch.Tensor) -> torch.Tensor:
    method apply_coords_torch (line 67) | def apply_coords_torch(
    method apply_boxes_torch (line 83) | def apply_boxes_torch(
    method get_preprocess_shape (line 94) | def get_preprocess_shape(oldh: int, oldw: int, long_side_length: int) ...

FILE: modules/control/proc/shuffle.py
  class ContentShuffleDetector (line 10) | class ContentShuffleDetector:
    method __call__ (line 11) | def __call__(self, input_image, h=None, w=None, f=None, detect_resolut...
  class ColorShuffleDetector (line 49) | class ColorShuffleDetector:
    method __call__ (line 50) | def __call__(self, img):
  class GrayDetector (line 66) | class GrayDetector:
    method __call__ (line 67) | def __call__(self, img):
  class DownSampleDetector (line 81) | class DownSampleDetector:
    method __call__ (line 82) | def __call__(self, img, level=3, k=16.0):
  class Image2MaskShuffleDetector (line 93) | class Image2MaskShuffleDetector:
    method __init__ (line 94) | def __init__(self, resolution=(640, 512)):
    method __call__ (line 97) | def __call__(self, img):

FILE: modules/control/proc/zoe/__init__.py
  class ZoeDetector (line 18) | class ZoeDetector:
    method __init__ (line 19) | def __init__(self, model):
    method from_pretrained (line 23) | def from_pretrained(cls, pretrained_model_or_path, model_type="zoedept...
    method to (line 51) | def to(self, device):
    method __call__ (line 55) | def __call__(self, input_image, detect_resolution=512, image_resolutio...

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas.py
  function denormalize (line 32) | def denormalize(x):
  function get_activation (line 45) | def get_activation(name, bank):
  class Resize (line 51) | class Resize(object):
    method __init__ (line 55) | def __init__(
    method constrain_to_multiple_of (line 101) | def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
    method get_size (line 114) | def get_size(self, width, height):
    method __call__ (line 172) | def __call__(self, x):
  class PrepForMidas (line 176) | class PrepForMidas(object):
    method __init__ (line 177) | def __init__(self, resize_mode="minimal", keep_aspect_ratio=True, img_...
    method __call__ (line 186) | def __call__(self, x):
  class MidasCore (line 190) | class MidasCore(nn.Module):
    method __init__ (line 191) | def __init__(self, midas, trainable=False, fetch_features=True, layer_...
    method set_trainable (line 224) | def set_trainable(self, trainable):
    method set_fetch_features (line 232) | def set_fetch_features(self, fetch_features):
    method freeze (line 241) | def freeze(self):
    method unfreeze (line 247) | def unfreeze(self):
    method freeze_bn (line 253) | def freeze_bn(self):
    method forward (line 259) | def forward(self, x, denorm=False, return_rel_depth=False):
    method get_rel_pos_params (line 278) | def get_rel_pos_params(self):
    method get_enc_params_except_rel_pos (line 283) | def get_enc_params_except_rel_pos(self):
    method freeze_encoder (line 288) | def freeze_encoder(self, freeze_rel_pos=False):
    method attach_hooks (line 297) | def attach_hooks(self, midas):
    method remove_hooks (line 321) | def remove_hooks(self):
    method __del__ (line 326) | def __del__(self):
    method set_output_channels (line 329) | def set_output_channels(self, model_type):
    method build (line 333) | def build(midas_model_type="DPT_BEiT_L_384", train_midas=False, use_pr...
    method build_from_config (line 351) | def build_from_config(config):
    method parse_img_size (line 355) | def parse_img_size(config):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/hubconf.py
  function DPT_BEiT_L_512 (line 9) | def DPT_BEiT_L_512(pretrained=True, **kwargs):
  function DPT_BEiT_L_384 (line 32) | def DPT_BEiT_L_384(pretrained=True, **kwargs):
  function DPT_BEiT_B_384 (line 55) | def DPT_BEiT_B_384(pretrained=True, **kwargs):
  function DPT_SwinV2_L_384 (line 78) | def DPT_SwinV2_L_384(pretrained=True, **kwargs):
  function DPT_SwinV2_B_384 (line 101) | def DPT_SwinV2_B_384(pretrained=True, **kwargs):
  function DPT_SwinV2_T_256 (line 124) | def DPT_SwinV2_T_256(pretrained=True, **kwargs):
  function DPT_Swin_L_384 (line 147) | def DPT_Swin_L_384(pretrained=True, **kwargs):
  function DPT_Next_ViT_L_384 (line 170) | def DPT_Next_ViT_L_384(pretrained=True, **kwargs):
  function DPT_LeViT_224 (line 193) | def DPT_LeViT_224(pretrained=True, **kwargs):
  function DPT_Large (line 218) | def DPT_Large(pretrained=True, **kwargs):
  function DPT_Hybrid (line 241) | def DPT_Hybrid(pretrained=True, **kwargs):
  function MiDaS (line 264) | def MiDaS(pretrained=True, **kwargs):
  function MiDaS_small (line 283) | def MiDaS_small(pretrained=True, **kwargs):
  function transforms (line 303) | def transforms():

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/beit.py
  function forward_beit (line 14) | def forward_beit(pretrained, x):
  function patch_embed_forward (line 18) | def patch_embed_forward(self, x):
  function _get_rel_pos_bias (line 29) | def _get_rel_pos_bias(self, window_size):
  function attention_forward (line 65) | def attention_forward(self, x, resolution, shared_rel_pos_bias: Optional...
  function block_forward (line 94) | def block_forward(self, x, resolution, shared_rel_pos_bias: Optional[tor...
  function beit_forward_features (line 108) | def beit_forward_features(self, x):
  function _make_beit_backbone (line 130) | def _make_beit_backbone(
  function _make_pretrained_beitl16_512 (line 163) | def _make_pretrained_beitl16_512(pretrained, use_readout="ignore", hooks...
  function _make_pretrained_beitl16_384 (line 180) | def _make_pretrained_beitl16_384(pretrained, use_readout="ignore", hooks...
  function _make_pretrained_beitb16_384 (line 193) | def _make_pretrained_beitb16_384(pretrained, use_readout="ignore", hooks...

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/levit.py
  function forward_levit (line 9) | def forward_levit(pretrained, x):
  function _make_levit_backbone (line 23) | def _make_levit_backbone(
  class ConvTransposeNorm (line 59) | class ConvTransposeNorm(nn.Sequential):
    method __init__ (line 66) | def __init__(
    method fuse (line 76) | def fuse(self):
  function stem_b4_transpose (line 89) | def stem_b4_transpose(in_chs, out_chs, activation):
  function _make_pretrained_levit_384 (line 102) | def _make_pretrained_levit_384(pretrained, hooks=None):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/next_vit.py
  function forward_next_vit (line 7) | def forward_next_vit(pretrained, x):
  function _make_next_vit_backbone (line 11) | def _make_next_vit_backbone(
  function _make_pretrained_next_vit_large_6m (line 30) | def _make_pretrained_next_vit_large_6m(hooks=None):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/swin.py
  function _make_pretrained_swinl12_384 (line 6) | def _make_pretrained_swinl12_384(pretrained, hooks=None):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/swin2.py
  function _make_pretrained_swin2l24_384 (line 6) | def _make_pretrained_swin2l24_384(pretrained, hooks=None):
  function _make_pretrained_swin2b24_384 (line 16) | def _make_pretrained_swin2b24_384(pretrained, hooks=None):
  function _make_pretrained_swin2t16_256 (line 26) | def _make_pretrained_swin2t16_256(pretrained, hooks=None):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/swin_common.py
  function forward_swin (line 9) | def forward_swin(pretrained, x):
  function _make_swin_backbone (line 13) | def _make_swin_backbone(

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/utils.py
  class Slice (line 6) | class Slice(nn.Module):
    method __init__ (line 7) | def __init__(self, start_index=1):
    method forward (line 11) | def forward(self, x):
  class AddReadout (line 15) | class AddReadout(nn.Module):
    method __init__ (line 16) | def __init__(self, start_index=1):
    method forward (line 20) | def forward(self, x):
  class ProjectReadout (line 28) | class ProjectReadout(nn.Module):
    method __init__ (line 29) | def __init__(self, in_features, start_index=1):
    method forward (line 35) | def forward(self, x):
  class Transpose (line 42) | class Transpose(nn.Module):
    method __init__ (line 43) | def __init__(self, dim0, dim1):
    method forward (line 48) | def forward(self, x):
  function get_activation (line 56) | def get_activation(name):
  function forward_default (line 63) | def forward_default(pretrained, x, function_name="forward_features"):
  function forward_adapted_unflatten (line 83) | def forward_adapted_unflatten(pretrained, x, function_name="forward_feat...
  function get_readout_oper (line 127) | def get_readout_oper(vit_features, features, use_readout, start_index=1):
  function make_backbone_default (line 142) | def make_backbone_default(

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/backbones/vit.py
  function forward_vit (line 12) | def forward_vit(pretrained, x):
  function _resize_pos_embed (line 16) | def _resize_pos_embed(self, posemb, gs_h, gs_w):
  function forward_flex (line 33) | def forward_flex(self, x):
  function _make_vit_b16_backbone (line 75) | def _make_vit_b16_backbone(
  function _make_pretrained_vitl16_384 (line 104) | def _make_pretrained_vitl16_384(pretrained, use_readout="ignore", hooks=...
  function _make_pretrained_vitb16_384 (line 117) | def _make_pretrained_vitb16_384(pretrained, use_readout="ignore", hooks=...
  function _make_vit_b_rn50_backbone (line 126) | def _make_vit_b_rn50_backbone(
  function _make_pretrained_vitb_rn50_384 (line 222) | def _make_pretrained_vitb_rn50_384(

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/base_model.py
  class BaseModel (line 4) | class BaseModel(torch.nn.Module):
    method load (line 5) | def load(self, path):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/blocks.py
  function _make_encoder (line 32) | def _make_encoder(backbone, features, use_pretrained, groups=1, expand=F...
  function _make_scratch (line 135) | def _make_scratch(in_shape, out_shape, groups=1, expand=False):
  function _make_pretrained_efficientnet_lite3 (line 168) | def _make_pretrained_efficientnet_lite3(use_pretrained, exportable=False):
  function _make_efficientnet_backbone (line 178) | def _make_efficientnet_backbone(effnet):
  function _make_resnet_backbone (line 191) | def _make_resnet_backbone(resnet):
  function _make_pretrained_resnext101_wsl (line 204) | def _make_pretrained_resnext101_wsl(use_pretrained):
  class Interpolate (line 210) | class Interpolate(nn.Module):
    method __init__ (line 214) | def __init__(self, scale_factor, mode, align_corners=False):
    method forward (line 228) | def forward(self, x):
  class ResidualConvUnit (line 245) | class ResidualConvUnit(nn.Module):
    method __init__ (line 249) | def __init__(self, features):
    method forward (line 267) | def forward(self, x):
  class FeatureFusionBlock (line 284) | class FeatureFusionBlock(nn.Module):
    method __init__ (line 288) | def __init__(self, features):
    method forward (line 299) | def forward(self, *xs):
  class ResidualConvUnit_custom (line 321) | class ResidualConvUnit_custom(nn.Module):
    method __init__ (line 325) | def __init__(self, features, activation, bn):
    method forward (line 353) | def forward(self, x):
  class FeatureFusionBlock_custom (line 381) | class FeatureFusionBlock_custom(nn.Module):
    method __init__ (line 385) | def __init__(self, features, activation, deconv=False, bn=False, expan...
    method forward (line 412) | def forward(self, *xs, size=None):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/dpt_depth.py
  function _make_fusion_block (line 18) | def _make_fusion_block(features, use_bn, size = None):
  class DPT (line 30) | class DPT(BaseModel):
    method __init__ (line 31) | def __init__(
    method forward (line 110) | def forward(self, x):
  class DPTDepthModel (line 142) | class DPTDepthModel(DPT):
    method __init__ (line 143) | def __init__(self, path=None, non_negative=True, **kwargs):
    method forward (line 165) | def forward(self, x):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/midas_net.py
  class MidasNet (line 12) | class MidasNet(BaseModel):
    method __init__ (line 16) | def __init__(self, path=None, features=256, non_negative=True):
    method forward (line 49) | def forward(self, x):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/midas_net_custom.py
  class MidasNet_small (line 12) | class MidasNet_small(BaseModel):
    method __init__ (line 16) | def __init__(self, path=None, features=64, backbone="efficientnet_lite...
    method forward (line 75) | def forward(self, x):
  function fuse_model (line 111) | def fuse_model(m):

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/model_loader.py
  function load_model (line 29) | def load_model(device, model_path, model_type="dpt_large_384", optimize=...

FILE: modules/control/proc/zoe/zoedepth/models/base_models/midas_repo/midas/transforms.py
  function apply_min_size (line 6) | def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AR...
  class Resize (line 48) | class Resize(object):
    method __init__ (line 52) | def __init__(
    method constrain_to_multiple_of (line 94) | def constrain_to_multiple_of(self, x, min_val=0, max_val=None):
    method get_size (line 105) | def get_size(self, width, height):
    method __call__ (line 162) | def __call__(self, sample):
  class NormalizeImage (line 197) | class NormalizeImage(object):
    method __init__ (line 201) | def __init__(self, mean, std):
    method __call__ (line 205) | def __call__(self, sample):
  class PrepareForNet (line 211) | class PrepareForNet(object):
    method __init__ (line 215) | def __init__(self):
    method __call__ (line 218) | def __call__(self, sample):

FILE: modules/control/proc/zoe/zoedepth/models/builder.py
  function build_model (line 28) | def build_model(config) -> DepthModel:

FILE: modules/control/proc/zoe/zoedepth/models/depth_model.py
  class DepthModel (line 35) | class DepthModel(nn.Module):
    method __init__ (line 36) | def __init__(self, device='cpu'):
    method to (line 40) | def to(self, device) -> nn.Module:
    method forward (line 44) | def forward(self, x, *args, **kwargs):
    method _infer (line 47) | def _infer(self, x: torch.Tensor):
    method _infer_with_pad_aug (line 57) | def _infer_with_pad_aug(self, x: torch.Tensor, pad_input: bool=True, f...
    method infer_with_flip_aug (line 99) | def infer_with_flip_aug(self, x, pad_input: bool=True, **kwargs) -> to...
    method infer (line 115) | def infer(self, x, pad_input: bool=True, with_flip_aug: bool=True, **k...
    method infer_pil (line 130) | def infer_pil(self, pil_img, pad_input: bool=True, with_flip_aug: bool...

FILE: modules/control/proc/zoe/zoedepth/models/layers/attractor.py
  function exp_attractor (line 30) | def exp_attractor(dx, alpha: float = 300, gamma: int = 2):
  function inv_attractor (line 45) | def inv_attractor(dx, alpha: float = 300, gamma: int = 2):
  class AttractorLayer (line 60) | class AttractorLayer(nn.Module):
    method __init__ (line 61) | def __init__(self, in_features, n_bins, n_attractors=16, mlp_dim=128, ...
    method forward (line 85) | def forward(self, x, b_prev, prev_b_embedding=None, interpolate=True, ...
  class AttractorLayerUnnormed (line 139) | class AttractorLayerUnnormed(nn.Module):
    method __init__ (line 140) | def __init__(self, in_features, n_bins, n_attractors=16, mlp_dim=128, ...
    method forward (line 164) | def forward(self, x, b_prev, prev_b_embedding=None, interpolate=True, ...

FILE: modules/control/proc/zoe/zoedepth/models/layers/dist_layers.py
  function log_binom (line 29) | def log_binom(n, k, eps=1e-7):
  class LogBinomial (line 36) | class LogBinomial(nn.Module):
    method __init__ (line 37) | def __init__(self, n_classes=256, act=torch.softmax):
    method forward (line 51) | def forward(self, x, t=1., eps=1e-4):
  class ConditionalLogBinomial (line 72) | class ConditionalLogBinomial(nn.Module):
    method __init__ (line 73) | def __init__(self, in_features, condition_dim, n_classes=256, bottlene...
    method forward (line 100) | def forward(self, x, cond):

FILE: modules/control/proc/zoe/zoedepth/models/layers/localbins_layers.py
  class SeedBinRegressor (line 29) | class SeedBinRegressor(nn.Module):
    method __init__ (line 30) | def __init__(self, in_features, n_bins=16, mlp_dim=256, min_depth=1e-3...
    method forward (line 52) | def forward(self, x):
  class SeedBinRegressorUnnormed (line 71) | class SeedBinRegressorUnnormed(nn.Module):
    method __init__ (line 72) | def __init__(self, in_features, n_bins=16, mlp_dim=256, min_depth=1e-3...
    method forward (line 91) | def forward(self, x):
  class Projector (line 99) | class Projector(nn.Module):
    method __init__ (line 100) | def __init__(self, in_features, out_features, mlp_dim=128):
    method forward (line 116) | def forward(self, x):
  class LinearSplitter (line 121) | class LinearSplitter(nn.Module):
    method __init__ (line 122) | def __init__(self, in_features, prev_nbins, split_factor=2, mlp_dim=12...
    method forward (line 137) | def forward(self, x, b_prev, prev_b_embedding=None, interpolate=True, ...

FILE: modules/control/proc/zoe/zoedepth/models/layers/patch_transformer.py
  class PatchTransformerEncoder (line 29) | class PatchTransformerEncoder(nn.Module):
    method __init__ (line 30) | def __init__(self, in_channels, patch_size=10, embedding_dim=128, num_...
    method positional_encoding_1d (line 50) | def positional_encoding_1d(self, sequence_length, batch_size, embeddin...
    method forward (line 71) | def forward(self, x):

FILE: modules/control/proc/zoe/zoedepth/models/model_io.py
  function load_state_dict (line 27) | def load_state_dict(model, state_dict):
  function load_wts (line 54) | def load_wts(model, checkpoint_path):
  function load_state_dict_from_url (line 59) | def load_state_dict_from_url(model, url, **kwargs):
  function load_state_from_resource (line 64) | def load_state_from_resource(model, resource: str):

FILE: modules/control/proc/zoe/zoedepth/models/zoedepth/zoedepth_v1.py
  class ZoeDepth (line 38) | class ZoeDepth(DepthModel):
    method __init__ (line 39) | def __init__(self, core,  n_bins=64, bin_centers_type="softplus", bin_...
    method forward (line 126) | def forward(self, x, return_final_centers=False, denorm=False, return_...
    method get_lr_params (line 206) | def get_lr_params(self, lr):
    method build (line 241) | def build(midas_model_type="DPT_BEiT_L_384", pretrained_resource=None,...
    method build_from_config (line 251) | def build_from_config(config):

FILE: modules/control/proc/zoe/zoedepth/models/zoedepth_nk/zoedepth_nk_v1.py
  class ZoeDepthNK (line 39) | class ZoeDepthNK(DepthModel):
    method __init__ (line 40) | def __init__(self, core,  bin_conf, bin_centers_type="softplus", bin_e...
    method forward (line 160) | def forward(self, x, return_final_centers=False, denorm=False, return_...
    method get_lr_params (line 245) | def get_lr_params(self, lr):
    method get_conf_parameters (line 285) | def get_conf_parameters(self, conf_name):
    method freeze_conf (line 297) | def freeze_conf(self, conf_name):
    method unfreeze_conf (line 304) | def unfreeze_conf(self, conf_name):
    method freeze_all_confs (line 311) | def freeze_all_confs(self):
    method build (line 322) | def build(midas_model_type="DPT_BEiT_L_384", pretrained_resource=None,...
    method build_from_config (line 332) | def build_from_config(config):

FILE: modules/control/proc/zoe/zoedepth/utils/arg_utils.py
  function infer_type (line 3) | def infer_type(x):  # hacky way to infer type from string args
  function parse_unknown (line 22) | def parse_unknown(unknown_args):

FILE: modules/control/proc/zoe/zoedepth/utils/config.py
  function flatten (line 257) | def flatten(config, except_keys=('bin_conf')):
  function split_combined_args (line 271) | def split_combined_args(kwargs):
  function parse_list (line 295) | def parse_list(config, key, dtype=int):
  function get_model_config (line 306) | def get_model_config(model_name, model_version=None):
  function update_model_config (line 334) | def update_model_config(config, mode, model_name, model_version=None, st...
  function check_choices (line 344) | def check_choices(name, value, choices):
  function get_config (line 354) | def get_config(model_name, mode='train', dataset=None, **overwrite_kwargs):
  function change_dataset (line 435) | def change_dataset(config, new_dataset):

FILE: modules/control/proc/zoe/zoedepth/utils/easydict/__init__.py
  class EasyDict (line 7) | class EasyDict(dict):
    method __init__ (line 120) | def __init__(self, d=None, **kwargs):
    method __setattr__ (line 134) | def __setattr__(self, name, value):
    method update (line 145) | def update(self, e=None, **f):
    method pop (line 151) | def pop(self, k, d=None):

FILE: modules/control/processor.py
  function preprocess_image (line 41) | def preprocess_image(

FILE: modules/control/processors.py
  function delay_load_config (line 49) | def delay_load_config():
  function list_models (line 107) | def list_models(refresh=False):
  function update_settings (line 116) | def update_settings(*settings):
  class Processor (line 164) | class Processor():
    method __init__ (line 165) | def __init__(self, processor_id: str = None, resize = True):
    method __str__ (line 175) | def __str__(self):
    method reset (line 178) | def reset(self, processor_id: str = None):
    method config (line 194) | def config(self, processor_id = None):
    method load (line 207) | def load(self, processor_id: str = None, force: bool = True) -> str:
    method __call__ (line 271) | def __call__(self, image_input: Image, mode: str = 'RGB', width: int =...
    method preview (line 333) | def preview(self):

FILE: modules/control/run.py
  function restore_pipeline (line 33) | def restore_pipeline():
  function terminate (line 47) | def terminate(msg):
  function is_unified_model (line 53) | def is_unified_model():
  function has_inputs (line 57) | def has_inputs(inputs):
  function set_pipe (line 66) | def set_pipe(p, has_models, unit_type, selected_models, active_model, ac...
  function check_active (line 143) | def check_active(p, unit_type, units):
  function check_enabled (line 219) | def check_enabled(p, unit_type, units, active_model, active_strength, ac...
  function control_set (line 248) | def control_set(kwargs):
  function init_units (line 257) | def init_units(units: List[unit.Unit]):
  function control_run (line 273) | def control_run(state: str = '', # pylint: disable=keyword-arg-before-va...

FILE: modules/control/test.py
  function test_processors (line 9) | def test_processors(image):
  function test_controlnets (line 58) | def test_controlnets(prompt, negative, image):
  function test_adapters (line 109) | def test_adapters(prompt, negative, image):
  function test_xs (line 161) | def test_xs(prompt, negative, image):
  function test_lite (line 212) | def test_lite(prompt, negative, image):

FILE: modules/control/tile.py
  function get_tile (line 6) | def get_tile(image: Image.Image, x: int, y: int, sx: int, sy: int) -> Im...
  function set_tile (line 15) | def set_tile(image: Image.Image, x: int, y: int, tiled: Image.Image):
  function run_tiling (line 20) | def run_tiling(p: processing.StableDiffusionProcessing, input_image: Ima...

FILE: modules/control/unit.py
  class Unit (line 19) | class Unit(): # mashup of gradio controls and mapping to actual implemen...
    method update_choices (line 20) | def update_choices(self, model_id=None):
    method __str__ (line 33) | def __str__(self):
    method __init__ (line 36) | def __init__(self,
    method reset (line 256) | def reset(self):

FILE: modules/control/units/controlnet.py
  function find_models (line 150) | def find_models():
  function api_list_models (line 168) | def api_list_models(model_type: str = None):
  function list_models (line 190) | def list_models(refresh=False):
  class ControlNet (line 219) | class ControlNet():
    method __init__ (line 220) | def __init__(self, model_id: str = None, device = None, dtype = None, ...
    method __str__ (line 237) | def __str__(self):
    method reset (line 240) | def reset(self):
    method get_class (line 247) | def get_class(self, model_id:str=''):
    method load_safetensors (line 289) | def load_safetensors(self, model_id, model_path, cls, config): # pylin...
    method load (line 316) | def load(self, model_id: str = None, force: bool = False) -> str:
  class ControlNetPipeline (line 422) | class ControlNetPipeline():
    method __init__ (line 423) | def __init__(self,
    method restore (line 571) | def restore(self):

FILE: modules/control/units/detect.py
  function is_compatible (line 1) | def is_compatible(model, pattern='None'):
  function is_sd15 (line 9) | def is_sd15(model):
  function is_sdxl (line 13) | def is_sdxl(model):
  function is_f1 (line 17) | def is_f1(model):
  function is_sd3 (line 21) | def is_sd3(model):
  function is_qwen (line 25) | def is_qwen(model):
  function is_hunyuandit (line 29) | def is_hunyuandit(model):
  function is_zimage (line 32) | def is_zimage(model):

FILE: modules/control/units/lite.py
  function find_models (line 34) | def find_models():
  function list_models (line 46) | def list_models(refresh=False):
  class ControlLLLite (line 65) | class ControlLLLite():
    method __init__ (line 66) | def __init__(self, model_id: str = None, device = None, dtype = None, ...
    method __str__ (line 77) | def __str__(self):
    method reset (line 80) | def reset(self):
    method load (line 86) | def load(self, model_id: str = None, force: bool = True) -> str:
  class ControlLLitePipeline (line 135) | class ControlLLitePipeline():
    method __init__ (line 136) | def __init__(self, pipeline: Union[StableDiffusionXLPipeline, StableDi...
    method apply (line 141) | def apply(self, controlnet: Union[ControlNetLLLite, list[ControlNetLLL...
    method restore (line 152) | def restore(self):

FILE: modules/control/units/lite_model.py
  class LLLiteModule (line 12) | class LLLiteModule(torch.nn.Module):
    method __init__ (line 13) | def __init__(
    method set_cond_image (line 69) | def set_cond_image(self, cond_image):
    method forward (line 73) | def forward(self, x):
  function clear_all_lllite (line 99) | def clear_all_lllite():
  class ControlNetLLLite (line 108) | class ControlNetLLLite(torch.nn.Module): # pylint: disable=abstract-method
    method __init__ (line 109) | def __init__(self, path: str):
    method apply (line 150) | def apply(self, pipe, cond, weight): # pylint: disable=arguments-differ
    method get_hacked_forward (line 189) | def get_hacked_forward(self, original_forward, model, blk):

FILE: modules/control/units/reference.py
  function list_models (line 13) | def list_models():
  class ReferencePipeline (line 17) | class ReferencePipeline():
    method __init__ (line 18) | def __init__(self, pipeline: Union[StableDiffusionXLPipeline, StableDi...
    method restore (line 64) | def restore(self):

FILE: modules/control/units/t2iadapter.py
  function list_models (line 50) | def list_models(refresh=False):
  class AdapterModel (line 69) | class AdapterModel(T2IAdapter):
  class Adapter (line 73) | class Adapter():
    method __init__ (line 74) | def __init__(self, model_id: str = None, device = None, dtype = None, ...
    method __str__ (line 85) | def __str__(self):
    method reset (line 88) | def reset(self):
    method load (line 94) | def load(self, model_id: str = None, force: bool = True) -> str:
  class AdapterPipeline (line 144) | class AdapterPipeline():
    method __init__ (line 145) | def __init__(self, adapter: Union[T2IAdapter, list[T2IAdapter]], pipel...
    method restore (line 205) | def restore(self):

FILE: modules/control/units/xs.py
  function find_models (line 30) | def find_models():
  function list_models (line 42) | def list_models(refresh=False):
  class ControlNetXS (line 61) | class ControlNetXS():
    method __init__ (line 62) | def __init__(self, model_id: str = None, device = None, dtype = None, ...
    method __str__ (line 73) | def __str__(self):
    method reset (line 76) | def reset(self):
    method load (line 82) | def load(self, model_id: str = None, time_embedding_mix: float = 0.0, ...
  class ControlNetXSPipeline (line 128) | class ControlNetXSPipeline():
    method __init__ (line 129) | def __init__(self, controlnet: Union[ControlNetXSModel, list[ControlNe...
    method restore (line 175) | def restore(self):

FILE: modules/control/units/xs_model.py
  class ControlNetXSOutput (line 50) | class ControlNetXSOutput(BaseOutput):
  class ControlNetConditioningEmbedding (line 64) | class ControlNetConditioningEmbedding(nn.Module):
    method __init__ (line 74) | def __init__(
    method forward (line 96) | def forward(self, conditioning):
  class ControlNetXSModel (line 109) | class ControlNetXSModel(ModelMixin, ConfigMixin):
    method init_original (line 141) | def init_original(cls, base_model: UNet2DConditionModel, is_sdxl=True):
    method _gather_subblock_sizes (line 182) | def _gather_subblock_sizes(cls, unet: UNet2DConditionModel, base_or_co...
    method __init__ (line 229) | def __init__(
    method from_unet (line 366) | def from_unet(
    method attn_processors (line 483) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 491) | def set_attn_processor(
    method set_default_attn_processor (line 508) | def set_default_attn_processor(self):
    method set_attention_slice (line 514) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 530) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 537) | def forward(
    method _make_zero_conv (line 746) | def _make_zero_conv(self, in_channels, out_channels=None):
    method _check_if_vae_compatible (line 754) | def _check_if_vae_compatible(self, vae: AutoencoderKL):
  class SubBlock (line 761) | class SubBlock(nn.ModuleList):
    method __init__ (line 766) | def __init__(self, ms, *args, **kwargs):
    method forward (line 771) | def forward(
  function adjust_time_dims (line 797) | def adjust_time_dims(unet: UNet2DConditionModel, in_dim: int, out_dim: i...
  function increase_block_input_in_encoder_resnet (line 801) | def increase_block_input_in_encoder_resnet(unet: UNet2DConditionModel, b...
  function increase_block_input_in_encoder_downsampler (line 855) | def increase_block_input_in_encoder_downsampler(unet: UNet2DConditionMod...
  function increase_block_input_in_mid_resnet (line 885) | def increase_block_input_in_mid_resnet(unet: UNet2DConditionModel, by):
  function adjust_group_norms (line 935) | def adjust_group_norms(unet: UNet2DConditionModel, max_num_group: int = ...
  function is_iterable (line 961) | def is_iterable(o):
  function to_sub_blocks (line 971) | def to_sub_blocks(blocks):
  function zero_module (line 1007) | def zero_module(module):

FILE: modules/control/units/xs_pipe.py
  class StableDiffusionXLControlNetXSPipeline (line 55) | class StableDiffusionXLControlNetXSPipeline(
    method __init__ (line 102) | def __init__(
    method enable_vae_slicing (line 158) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 166) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 174) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 183) | def disable_vae_tiling(self):
    method encode_prompt (line 191) | def encode_prompt(
    method prepare_extra_step_kwargs (line 426) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 443) | def check_inputs(
    method check_image (line 550) | def check_image(self, image, prompt, prompt_embeds):
    method prepare_image (line 587) | def prepare_image(
    method prepare_latents (line 617) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 635) | def _get_add_time_ids(
    method upcast_vae (line 654) | def upcast_vae(self):
    method enable_freeu (line 673) | def enable_freeu(self, s1: float, s2: float, b1: float, b2: float):
    method disable_freeu (line 696) | def disable_freeu(self):
    method __call__ (line 701) | def __call__(
  class StableDiffusionControlNetXSPipeline (line 1089) | class StableDiffusionControlNetXSPipeline(
    method __init__ (line 1130) | def __init__(
    method enable_vae_slicing (line 1186) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 1194) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 1202) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 1211) | def disable_vae_tiling(self):
    method _encode_prompt (line 1219) | def _encode_prompt(
    method encode_prompt (line 1249) | def encode_prompt(
    method run_safety_checker (line 1431) | def run_safety_checker(self, image, device, dtype):
    method decode_latents (line 1446) | def decode_latents(self, latents):
    method prepare_extra_step_kwargs (line 1455) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 1472) | def check_inputs(
    method check_image (line 1552) | def check_image(self, image, prompt, prompt_embeds):
    method prepare_image (line 1589) | def prepare_image(
    method prepare_latents (line 1619) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method enable_freeu (line 1637) | def enable_freeu(self, s1: float, s2: float, b1: float, b2: float):
    method disable_freeu (line 1660) | def disable_freeu(self):
    method __call__ (line 1665) | def __call__(

FILE: modules/control/util.py
  function dict2str (line 12) | def dict2str(d: dict):
  function HWC3 (line 17) | def HWC3(x):
  function make_noise_disk (line 37) | def make_noise_disk(H, W, C, F):
  function nms (line 48) | def nms(x, t, s):
  function min_max_norm (line 61) | def min_max_norm(x):
  function safe_step (line 67) | def safe_step(x, step=2):
  function img2mask (line 73) | def img2mask(img, H, W, low=10, high=90):
  function resize_image (line 86) | def resize_image(input_image, resolution):
  function torch_gc (line 99) | def torch_gc():
  function ade_palette (line 105) | def ade_palette():
  function blend (line 147) | def blend(images):
  function decode_fourcc (line 163) | def decode_fourcc(cc):

FILE: modules/detailer.py
  class Detailer (line 5) | class Detailer: # abstract class used for postprocessing
    method name (line 6) | def name(self):
    method restore (line 10) | def restore(self, np_image):
  function detail (line 14) | def detail(np_image, p=None): # postprocesses the image

FILE: modules/devices.py
  function has_mps (line 37) | def has_mps() -> bool:
  function has_xpu (line 45) | def has_xpu() -> bool:
  function has_rocm (line 49) | def has_rocm() -> bool:
  function has_zluda (line 53) | def has_zluda() -> bool:
  function has_triton (line 64) | def has_triton(early:bool=False) -> bool:
  function get_hip_agent (line 70) | def get_hip_agent() -> rocm.Agent:
  function get_backend (line 74) | def get_backend(shared_cmd_opts):
  function get_gpu_info (line 96) | def get_gpu_info():
  function get_cuda_device_string (line 167) | def get_cuda_device_string():
  function get_optimal_device_name (line 183) | def get_optimal_device_name():
  function get_optimal_device (line 193) | def get_optimal_device():
  function torch_gc (line 197) | def torch_gc(force:bool=False, fast:bool=False, reason:str=None):
  function set_cuda_sync_mode (line 264) | def set_cuda_sync_mode(mode):
  function set_cuda_memory_limit (line 283) | def set_cuda_memory_limit():
  function set_cuda_tunable (line 296) | def set_cuda_tunable():
  function test_fp16 (line 320) | def test_fp16():
  function test_bf16 (line 351) | def test_bf16():
  function test_triton (line 384) | def test_triton(early: bool = False):
  function set_cudnn_params (line 416) | def set_cudnn_params():
  function override_ipex_math (line 444) | def override_ipex_math():
  function set_sdpa_params (line 454) | def set_sdpa_params():
  function set_dtype (line 512) | def set_dtype():
  function set_cuda_params (line 563) | def set_cuda_params():
  function randn (line 584) | def randn(seed, shape=None):
  function randn_without_seed (line 598) | def randn_without_seed(shape):
  function autocast (line 604) | def autocast(disable=False):
  function without_autocast (line 615) | def without_autocast(disable=False):
  class NansException (line 626) | class NansException(Exception):
  function test_for_nans (line 630) | def test_for_nans(x, where):
  function normalize_device (line 649) | def normalize_device(dev):
  function same_device (line 657) | def same_device(d1, d2):

FILE: modules/devices_mac.py
  function check_for_mps (line 10) | def check_for_mps() -> bool:
  function cumsum_fix (line 22) | def cumsum_fix(input, cumsum_func, *args, **kwargs): # pylint: disable=r...

FILE: modules/dml/Generator.py
  class Generator (line 5) | class Generator(torch.Generator):
    method __init__ (line 6) | def __init__(self, device: Optional[torch.device] = None):

FILE: modules/dml/__init__.py
  function _set_memory_provider (line 17) | def _set_memory_provider():
  function directml_init (line 41) | def directml_init():
  function directml_do_hijack (line 70) | def directml_do_hijack():
  class OverrideItem (line 87) | class OverrideItem(NamedTuple):
  function directml_override_opts (line 98) | def directml_override_opts():

FILE: modules/dml/amp/autocast_mode.py
  function forward (line 13) | def forward(op, args: tuple, kwargs: dict):
  function cast (line 22) | def cast(tensor: torch.Tensor):
  function cond (line 31) | def cond(op: str):
  class autocast (line 50) | class autocast:
    method __init__ (line 55) | def __init__(self, dtype: Optional[torch.dtype] = torch.float16):
    method __enter__ (line 58) | def __enter__(self):
    method __exit__ (line 64) | def __exit__(self, exc_type: Any, exc_val: Any, exc_tb: Any):

FILE: modules/dml/backend.py
  function amd_mem_get_info (line 12) | def amd_mem_get_info(device: Optional[rDevice]=None) -> tuple[int, int]:
  function pdh_mem_get_info (line 17) | def pdh_mem_get_info(device: Optional[rDevice]=None) -> tuple[int, int]:
  function mem_get_info (line 22) | def mem_get_info(device: Optional[rDevice]=None) -> tuple[int, int]: # p...
  class DirectML (line 26) | class DirectML:
    method is_available (line 38) | def is_available() -> bool:
    method is_directml_device (line 41) | def is_directml_device(device: torch.device) -> bool:
    method has_float64_support (line 44) | def has_float64_support(device: Optional[rDevice]=None) -> bool:
    method device_count (line 47) | def device_count() -> int:
    method current_device (line 50) | def current_device() -> torch.device:
    method default_device (line 53) | def default_device() -> torch.device:
    method get_device_string (line 56) | def get_device_string(device: Optional[rDevice]=None) -> str:
    method get_device_name (line 59) | def get_device_name(device: Optional[rDevice]=None) -> str:
    method get_device_properties (line 62) | def get_device_properties(device: Optional[rDevice]=None) -> DevicePro...
    method memory_stats (line 65) | def memory_stats(device: Optional[rDevice]=None):
    method memory_allocated (line 73) | def memory_allocated(device: Optional[rDevice]=None) -> int:
    method max_memory_allocated (line 76) | def max_memory_allocated(device: Optional[rDevice]=None):
    method reset_peak_memory_stats (line 79) | def reset_peak_memory_stats(device: Optional[rDevice]=None):

FILE: modules/dml/device.py
  class Device (line 6) | class Device:
    method __enter__ (line 9) | def __enter__(self, device: Optional[rDevice]=None):
    method __init__ (line 13) | def __init__(self, device: Optional[rDevice]=None) -> torch.device: # ...
    method __exit__ (line 16) | def __exit__(self, t, v, tb):

FILE: modules/dml/device_properties.py
  class DeviceProperties (line 4) | class DeviceProperties:
    method __init__ (line 12) | def __init__(self, device: torch.device):
    method __str__ (line 16) | def __str__(self):
    method __repr__ (line 19) | def __repr__(self):

FILE: modules/dml/hijack/realesrgan_model.py
  function tile_process (line 8) | def tile_process(self):

FILE: modules/dml/hijack/tomesd.py
  function make_tome_block (line 6) | def make_tome_block(block_class: Type[torch.nn.Module]) -> Type[torch.nn...

FILE: modules/dml/hijack/torch.py
  function cuda (line 10) | def cuda(self: torch.Tensor):
  function pow_ (line 17) | def pow_(self: torch.Tensor, *args, **kwargs):
  function load (line 25) | def load(f, map_location = "cpu", *args, **kwargs):

FILE: modules/dml/hijack/transformers.py
  function _make_causal_mask (line 6) | def _make_causal_mask(
  function CLIPTextEmbeddings_forward (line 23) | def CLIPTextEmbeddings_forward(

FILE: modules/dml/hijack/utils.py
  function catch_nan (line 6) | def catch_nan(func: Callable[[], torch.Tensor]):

FILE: modules/dml/memory.py
  class MemoryProvider (line 6) | class MemoryProvider:
    method __init__ (line 10) | def __init__(self):
    method get_memory (line 14) | def get_memory(self, device_id: int) -> dict[str, int]:
    method __del__ (line 30) | def __del__(self):

FILE: modules/dml/memory_amd/__init__.py
  class AMDMemoryProvider (line 4) | class AMDMemoryProvider:
    method mem_get_info (line 8) | def mem_get_info(index):

FILE: modules/dml/memory_amd/driver/atiadlxx.py
  class ATIADLxx (line 7) | class ATIADLxx:
    method __init__ (line 10) | def __init__(self):
    method get_memory_info2 (line 25) | def get_memory_info2(self, adapterIndex: int) -> ADLMemoryInfo2:
    method get_dedicated_vram_usage (line 33) | def get_dedicated_vram_usage(self, index: int) -> int:
    method get_vram_usage (line 41) | def get_vram_usage(self, index: int) -> int:

FILE: modules/dml/memory_amd/driver/atiadlxx_apis.py
  function ADL_Main_Memory_Alloc (line 17) | def ADL_Main_Memory_Alloc(iSize):
  function ADL_Main_Memory_Free (line 22) | def ADL_Main_Memory_Free(lpBuffer):

FILE: modules/dml/memory_amd/driver/atiadlxx_structures.py
  class _ADLPMActivity (line 4) | class _ADLPMActivity(C.Structure):
  class _ADLMemoryInfo2 (line 32) | class _ADLMemoryInfo2(C.Structure):
  class _AdapterInfo (line 52) | class _AdapterInfo(C.Structure):

FILE: modules/dml/pdh/__init__.py
  class __InternalAbstraction (line 11) | class __InternalAbstraction(NamedTuple):
  function expand_wildcard_path (line 22) | def expand_wildcard_path(path: str) -> list[str]:
  class HCounter (line 44) | class HCounter(PDH_HCOUNTER):
    method get_formatted_value (line 45) | def get_formatted_value(self, typ: T) -> T:
    method get_formatted_dict (line 54) | def get_formatted_dict(self, typ: T) -> dict[str, T]:
  class HQuery (line 72) | class HQuery(PDH_HQUERY):
    method __init__ (line 73) | def __init__(self):
    method add_counter (line 78) | def add_counter(self, path: str) -> HCounter:
    method collect_data (line 84) | def collect_data(self):
    method close (line 88) | def close(self):

FILE: modules/dml/pdh/errors.py
  class PDHError (line 1) | class PDHError(Exception):
    method __init__ (line 2) | def __init__(self, message: str):

FILE: modules/dml/pdh/structures.py
  class PDH_FMT_COUNTERVALUE_U (line 9) | class PDH_FMT_COUNTERVALUE_U(Union):
  class PDH_FMT_COUNTERVALUE (line 25) | class PDH_FMT_COUNTERVALUE(Structure):
  class PDH_FMT_COUNTERVALUE_ITEM_W (line 37) | class PDH_FMT_COUNTERVALUE_ITEM_W(Structure):

FILE: modules/dml/utils.py
  function get_device (line 6) | def get_device(device: Optional[rDevice]=None) -> torch.device:

FILE: modules/errorlimiter.py
  class ErrorLimiterTrigger (line 9) | class ErrorLimiterTrigger(BaseException):  # Use BaseException to avoid ...
    method __init__ (line 10) | def __init__(self, name: str, *args):
  class ErrorLimiterAbort (line 15) | class ErrorLimiterAbort(RuntimeError):
    method __init__ (line 16) | def __init__(self, msg: str):
  class ErrorLimiter (line 20) | class ErrorLimiter:
    method start (line 24) | def start(cls, name: str, limit: int = 5):
    method notify (line 28) | def notify(cls, name: str | Iterable[str]):  # Can be manually trigger...
    method end (line 38) | def end(cls, name: str):
  function limit_errors (line 43) | def limit_errors(name: str, limit: int = 5):

FILE: modules/errors.py
  function install (line 13) | def install(suppress=[]):
  function display (line 19) | def display(e: Exception, task: str, suppress=[]):
  function display_once (line 34) | def display_once(e: Exception, task):
  function run (line 41) | def run(code, task: str):
  function exception (line 48) | def exception(suppress=[]):
  function profile (line 53) | def profile(profiler, msg: str, n: int = 16):
  function profile_torch (line 82) | def profile_torch(profiler, msg: str):

FILE: modules/extensions.py
  function parse_isotime (line 14) | def parse_isotime(time_string: str) -> datetime:
  function format_dt (line 28) | def format_dt(d: datetime, seconds = False) -> str:
  function ts2utc (line 36) | def ts2utc(timestamp: int) -> datetime:
  function active (line 42) | def active():
  function temp_disable_extensions (line 51) | def temp_disable_extensions():
  class Extension (line 121) | class Extension:
    method __init__ (line 122) | def __init__(self, name, path, enabled=True, is_builtin=False):
    method read_info (line 140) | def read_info(self, force=False):
    method list_files (line 178) | def list_files(self, subdir, extension):
    method check_updates (line 197) | def check_updates(self):
    method git_fetch (line 221) | def git_fetch(self, commit='origin'):
  function list_extensions (line 231) | def list_extensions():

FILE: modules/extra_networks.py
  function initialize (line 10) | def initialize():
  function register_extra_network (line 14) | def register_extra_network(extra_network):
  function register_default_extra_networks (line 18) | def register_default_extra_networks():
  class ExtraNetworkParams (line 27) | class ExtraNetworkParams:
    method __init__ (line 28) | def __init__(self, items=None):
  class ExtraNetwork (line 40) | class ExtraNetwork:
    method __init__ (line 41) | def __init__(self, name):
    method activate (line 44) | def activate(self, p, params_list):
    method deactivate (line 61) | def deactivate(self, p, force=False):
  function is_stepwise (line 68) | def is_stepwise(en_obj):
  function activate (line 76) | def activate(p, extra_network_data=None, step=0, include=[], exclude=[]):
  function deactivate (line 125) | def deactivate(p, extra_network_data=None, force=shared.opts.lora_force_...
  function parse_prompt (line 154) | def parse_prompt(prompt: str | None) -> tuple[str, defaultdict[str, list...
  function parse_prompts (line 171) | def parse_prompts(prompts: list[str]):

FILE: modules/extras.py
  function run_pnginfo (line 14) | def run_pnginfo(image):
  function to_half (line 26) | def to_half(tensor, enable):
  function run_modelmerger (line 32) | def run_modelmerger(id_task, **kwargs):  # pylint: disable=unused-argument
  function run_model_modules (line 184) | def run_model_modules(model_type:str, model_name:str, custom_name:str,

FILE: modules/face/__init__.py
  class Script (line 10) | class Script(scripts_manager.Script):
    method title (line 14) | def title(self):
    method show (line 17) | def show(self, is_img2img):
    method load_images (line 20) | def load_images(self, files):
    method mode_change (line 40) | def mode_change(self, mode):
    method ui (line 50) | def ui(self, _is_img2img):
    method run (line 108) | def run(self, p: processing.StableDiffusionProcessing, mode, input_ima...
    method after (line 175) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: modules/face/faceid.py
  function hijack_load_ip_adapter (line 28) | def hijack_load_ip_adapter(self):
  function face_id (line 34) | def face_id(

FILE: modules/face/faceswap.py
  function face_swap (line 15) | def face_swap(p: processing.StableDiffusionProcessing, app, input_images...

FILE: modules/face/insightface.py
  function get_app (line 10) | def get_app(mp_name, threshold=0.5, resolution=640):

FILE: modules/face/instantid.py
  function instant_id (line 14) | def instant_id(p: processing.StableDiffusionProcessing, app, source_imag...

FILE: modules/face/instantid_model.py
  function FeedForward (line 50) | def FeedForward(dim, mult=4):
  function reshape_tensor (line 60) | def reshape_tensor(x, heads):
  class PerceiverAttention (line 71) | class PerceiverAttention(nn.Module):
    method __init__ (line 72) | def __init__(self, *, dim, dim_head=64, heads=8):
    method forward (line 86) | def forward(self, x, latents):
  class Resampler (line 118) | class Resampler(nn.Module):
    method __init__ (line 119) | def __init__(
    method forward (line 150) | def forward(self, x):
  class AttnProcessor (line 162) | class AttnProcessor(nn.Module):
    method __init__ (line 167) | def __init__(
    method __call__ (line 174) | def __call__(
  class IPAttnProcessor (line 235) | class IPAttnProcessor(nn.Module):
    method __init__ (line 249) | def __init__(self, hidden_size, cross_attention_dim=None, scale=1.0, n...
    method __call__ (line 260) | def __call__(
    method _memory_efficient_attention_xformers (line 346) | def _memory_efficient_attention_xformers(self, query, key, value, atte...
  function draw_kps (line 409) | def draw_kps(image_pil, kps, color_list=None):
  class StableDiffusionXLInstantIDPipeline (line 442) | class StableDiffusionXLInstantIDPipeline(StableDiffusionXLControlNetPipe...
    method cuda (line 443) | def cuda(self, dtype=torch.float16, use_xformers=False):
    method load_ip_adapter_instantid (line 463) | def load_ip_adapter_instantid(self, model_ckpt, image_emb_dim=512, num...
    method set_image_proj_model (line 467) | def set_image_proj_model(self, model_ckpt, image_emb_dim=512, num_toke...
    method set_ip_adapter (line 489) | def set_ip_adapter(self, model_ckpt, num_tokens, scale):
    method set_ip_adapter_scale (line 519) | def set_ip_adapter_scale(self, scale):
    method _encode_prompt_image_emb (line 525) | def _encode_prompt_image_emb(self, prompt_image_emb, device, dtype, do...
    method __call__ (line 545) | def __call__(

FILE: modules/face/photomaker.py
  function restore_pipeline (line 11) | def restore_pipeline():
  function photo_maker (line 18) | def photo_maker(p: processing.StableDiffusionProcessing, app, model: str...

FILE: modules/face/photomaker_model_v1.py
  class MLP (line 17) | class MLP(nn.Module):
    method __init__ (line 18) | def __init__(self, in_dim, out_dim, hidden_dim, use_residual=True):
    method forward (line 28) | def forward(self, x):
  class FuseModule (line 39) | class FuseModule(nn.Module):
    method __init__ (line 40) | def __init__(self, embed_dim):
    method fuse_fn (line 46) | def fuse_fn(self, prompt_embeds, id_embeds):
    method forward (line 54) | def forward(
  class PhotoMakerIDEncoder (line 87) | class PhotoMakerIDEncoder(CLIPVisionModelWithProjection):
    method __init__ (line 88) | def __init__(self):
    method forward (line 93) | def forward(self, id_pixel_values, prompt_embeds, class_tokens_mask): ...

FILE: modules/face/photomaker_model_v2.py
  class FacePerceiverResampler (line 12) | class FacePerceiverResampler(torch.nn.Module):
    method __init__ (line 13) | def __init__(
    method forward (line 39) | def forward(self, latents, x):
  function FeedForward (line 48) | def FeedForward(dim, mult=4):
  function reshape_tensor (line 58) | def reshape_tensor(x, heads):
  class PerceiverAttention (line 69) | class PerceiverAttention(nn.Module):
    method __init__ (line 70) | def __init__(self, *, dim, dim_head=64, heads=8):
    method forward (line 84) | def forward(self, x, latents):
  class Resampler (line 116) | class Resampler(nn.Module):
    method __init__ (line 117) | def __init__(
    method forward (line 162) | def forward(self, x):
  function masked_mean (line 185) | def masked_mean(t, *, dim, mask=None):
  class MLP (line 206) | class MLP(nn.Module):
    method __init__ (line 207) | def __init__(self, in_dim, out_dim, hidden_dim, use_residual=True):
    method forward (line 217) | def forward(self, x):
  class QFormerPerceiver (line 228) | class QFormerPerceiver(nn.Module):
    method __init__ (line 229) | def __init__(self, id_embeddings_dim, cross_attention_dim, num_tokens,...
    method forward (line 251) | def forward(self, x, last_hidden_state):
  class FuseModule (line 261) | class FuseModule(nn.Module):
    method __init__ (line 262) | def __init__(self, embed_dim):
    method fuse_fn (line 268) | def fuse_fn(self, prompt_embeds, id_embeds):
    method forward (line 275) | def forward(
  class PhotoMakerIDEncoder_CLIPInsightfaceExtendtoken (line 310) | class PhotoMakerIDEncoder_CLIPInsightfaceExtendtoken(CLIPVisionModelWith...
    method __init__ (line 311) | def __init__(self, id_embeddings_dim=512):
    method forward (line 326) | def forward(self, id_pixel_values, prompt_embeds, class_tokens_mask, i...

FILE: modules/face/photomaker_pipeline.py
  function rescale_noise_cfg (line 35) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 50) | def retrieve_timesteps(
  class PhotoMakerStableDiffusionXLPipeline (line 109) | class PhotoMakerStableDiffusionXLPipeline(StableDiffusionXLPipeline):
    method load_photomaker_adapter (line 111) | def load_photomaker_adapter(
    method encode_prompt_with_trigger_word (line 214) | def encode_prompt_with_trigger_word(
    method __call__ (line 445) | def __call__(

FILE: modules/face/reswapper.py
  function get_model (line 22) | def get_model(model_name: str):
  function reswapper (line 43) | def reswapper(

FILE: modules/face/reswapper_model.py
  class ReSwapperModel (line 7) | class ReSwapperModel(nn.Module):
    method __init__ (line 8) | def __init__(self):
    method forward (line 53) | def forward(self, target, source):
  class StyleBlock (line 88) | class StyleBlock(nn.Module):
    method __init__ (line 89) | def __init__(self, in_channels, out_channels, blockIndex):
    method normalizeConvRMS (line 99) | def normalizeConvRMS(self, conv):
    method forward (line 106) | def forward(self, residual, style):

FILE: modules/face/reswapper_utils.py
  function get_emap (line 10) | def get_emap():
  function postprocess_face (line 15) | def postprocess_face(face_tensor):
  function getBlob (line 21) | def getBlob(aimg, input_size = (128, 128)):
  function getLatent (line 26) | def getLatent(source_face):
  function blend_swapped_image (line 34) | def blend_swapped_image(swapped_face, target_image, M):
  function drawKeypoints (line 60) | def drawKeypoints(image, keypoints, colorBGR, keypointsRadius=2):
  function estimate_norm (line 74) | def estimate_norm(lmk, image_size=112,mode='arcface'): # pylint: disable...
  function norm_crop (line 100) | def norm_crop(img, landmark, image_size=112, mode='arcface'):
  function norm_crop2 (line 106) | def norm_crop2(img, landmark, image_size=112, mode='arcface'):
  function square_crop (line 112) | def square_crop(im, S):
  function transform (line 127) | def transform(data, center, output_size, scale, rotation):
  function trans_points2d (line 143) | def trans_points2d(pts, M):
  function trans_points3d (line 153) | def trans_points3d(pts, M):
  function trans_points (line 167) | def trans_points(pts, M):

FILE: modules/face_restoration.py
  class FaceRestoration (line 4) | class FaceRestoration:
    method name (line 5) | def name(self):
    method restore (line 8) | def restore(self, np_image):
  function restore_faces (line 12) | def restore_faces(np_image, p=None):

FILE: modules/facelib/detection/__init__.py
  function init_detection_model (line 16) | def init_detection_model(model_name, half=False, device='cuda'):
  function init_retinaface_model (line 27) | def init_retinaface_model(model_name, half=False, device='cuda'):
  function init_yolov5face_model (line 51) | def init_yolov5face_model(model_name, device='cuda'):

FILE: modules/facelib/detection/align_trans.py
  class FaceWarpException (line 13) | class FaceWarpException(Exception):
    method __str__ (line 15) | def __str__(self):
  function get_reference_facial_points (line 19) | def get_reference_facial_points(output_size=None, inner_padding_factor=0...
  function get_affine_transform_matrix (line 112) | def get_affine_transform_matrix(src_pts, dst_pts):
  function warp_and_crop_face (line 145) | def warp_and_crop_face(src_img, facial_pts, reference_pts=None, crop_siz...

FILE: modules/facelib/detection/matlab_cp2tform.py
  class MatlabCp2tormException (line 7) | class MatlabCp2tormException(Exception):
    method __str__ (line 9) | def __str__(self):
  function tformfwd (line 13) | def tformfwd(trans, uv):
  function tforminv (line 37) | def tforminv(trans, uv):
  function findNonreflectiveSimilarity (line 60) | def findNonreflectiveSimilarity(uv, xy, options=None):
  function findSimilarity (line 94) | def findSimilarity(uv, xy, options=None):
  function get_similarity_transform (line 130) | def get_similarity_transform(src_pts, dst_pts, reflective=True):
  function cvt_tform_mat_for_cv2 (line 170) | def cvt_tform_mat_for_cv2(trans):
  function get_similarity_transform_for_cv2 (line 198) | def get_similarity_transform_for_cv2(src_pts, dst_pts, reflective=True):

FILE: modules/facelib/detection/retinaface/retinaface.py
  function generate_config (line 17) | def generate_config(network_name):
  class RetinaFace (line 73) | class RetinaFace(nn.Module):
    method __init__ (line 75) | def __init__(self, network_name='resnet50', half=False, phase='test'):
    method forward (line 120) | def forward(self, inputs):
    method __detect_faces (line 145) | def __detect_faces(self, inputs):
    method transform (line 165) | def transform(self, image, use_origin_size):
    method detect_faces (line 192) | def detect_faces(
    method __align_multi (line 239) | def __align_multi(self, image, boxes, landmarks, limit=None):
    method align_multi (line 257) | def align_multi(self, img, conf_threshold=0.8, limit=None):
    method batched_transform (line 265) | def batched_transform(self, frames, use_origin_size):
    method batched_detect_faces (line 308) | def batched_detect_faces(self, frames, conf_threshold=0.8, nms_thresho...

FILE: modules/facelib/detection/retinaface/retinaface_net.py
  function conv_bn (line 6) | def conv_bn(inp, oup, stride=1, leaky=0):
  function conv_bn_no_relu (line 12) | def conv_bn_no_relu(inp, oup, stride):
  function conv_bn1X1 (line 19) | def conv_bn1X1(inp, oup, stride, leaky=0):
  function conv_dw (line 25) | def conv_dw(inp, oup, stride, leaky=0.1):
  class SSH (line 36) | class SSH(nn.Module):
    method __init__ (line 38) | def __init__(self, in_channel, out_channel):
    method forward (line 52) | def forward(self, input):
  class FPN (line 66) | class FPN(nn.Module):
    method __init__ (line 68) | def __init__(self, in_channels_list, out_channels):
    method forward (line 80) | def forward(self, input):
  class MobileNetV1 (line 100) | class MobileNetV1(nn.Module):
    method __init__ (line 102) | def __init__(self):
    method forward (line 127) | def forward(self, x):
  class ClassHead (line 138) | class ClassHead(nn.Module):
    method __init__ (line 140) | def __init__(self, inchannels=512, num_anchors=3):
    method forward (line 145) | def forward(self, x):
  class BboxHead (line 152) | class BboxHead(nn.Module):
    method __init__ (line 154) | def __init__(self, inchannels=512, num_anchors=3):
    method forward (line 158) | def forward(self, x):
  class LandmarkHead (line 165) | class LandmarkHead(nn.Module):
    method __init__ (line 167) | def __init__(self, inchannels=512, num_anchors=3):
    method forward (line 171) | def forward(self, x):
  function make_class_head (line 178) | def make_class_head(fpn_num=3, inchannels=64, anchor_num=2):
  function make_bbox_head (line 185) | def make_bbox_head(fpn_num=3, inchannels=64, anchor_num=2):
  function make_landmark_head (line 192) | def make_landmark_head(fpn_num=3, inchannels=64, anchor_num=2):

FILE: modules/facelib/detection/retinaface/retinaface_utils.py
  class PriorBox (line 8) | class PriorBox(object):
    method __init__ (line 10) | def __init__(self, cfg, image_size=None, phase='train'):
    method forward (line 19) | def forward(self):
  function py_cpu_nms (line 39) | def py_cpu_nms(dets, thresh):
  function point_form (line 50) | def point_form(boxes):
  function center_size (line 65) | def center_size(boxes):
  function intersect (line 79) | def intersect(box_a, box_b):
  function jaccard (line 98) | def jaccard(box_a, box_b):
  function matrix_iou (line 117) | def matrix_iou(a, b):
  function matrix_iof (line 130) | def matrix_iof(a, b):
  function match (line 142) | def match(threshold, truths, priors, variances, labels, landms, loc_t, c...
  function encode (line 199) | def encode(matched, priors, variances):
  function encode_landm (line 223) | def encode_landm(matched, priors, variances):
  function decode (line 253) | def decode(loc, priors, variances):
  function decode_landm (line 273) | def decode_landm(pre, priors, variances):
  function batched_decode (line 296) | def batched_decode(b_loc, priors, variances):
  function batched_decode_landm (line 319) | def batched_decode_landm(pre, priors, variances):
  function log_sum_exp (line 342) | def log_sum_exp(x):
  function nms (line 356) | def nms(boxes, scores, overlap=0.5, top_k=200):

FILE: modules/facelib/detection/yolov5face/face_detector.py
  function isListempty (line 23) | def isListempty(inList):
  class YoloDetector (line 28) | class YoloDetector:
    method __init__ (line 29) | def __init__(
    method _preprocess (line 49) | def _preprocess(self, imgs):
    method _postprocess (line 70) | def _postprocess(self, imgs, origimgs, pred, conf_thres, iou_thres):
    method detect_faces (line 105) | def detect_faces(self, imgs, conf_thres=0.7, iou_thres=0.5):
    method __call__ (line 141) | def __call__(self, *args):

FILE: modules/facelib/detection/yolov5face/models/common.py
  function autopad (line 18) | def autopad(k, p=None):  # kernel, padding
  function channel_shuffle (line 25) | def channel_shuffle(x, groups):
  function DWConv (line 37) | def DWConv(c1, c2, k=1, s=1, act=True):
  class Conv (line 42) | class Conv(nn.Module):
    method __init__ (line 44) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 50) | def forward(self, x):
    method fuseforward (line 53) | def fuseforward(self, x):
  class StemBlock (line 57) | class StemBlock(nn.Module):
    method __init__ (line 58) | def __init__(self, c1, c2, k=3, s=2, p=None, g=1, act=True):
    method forward (line 66) | def forward(self, x):
  class Bottleneck (line 74) | class Bottleneck(nn.Module):
    method __init__ (line 76) | def __init__(self, c1, c2, shortcut=True, g=1, e=0.5):  # ch_in, ch_ou...
    method forward (line 83) | def forward(self, x):
  class BottleneckCSP (line 87) | class BottleneckCSP(nn.Module):
    method __init__ (line 89) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 100) | def forward(self, x):
  class C3 (line 106) | class C3(nn.Module):
    method __init__ (line 108) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 116) | def forward(self, x):
  class ShuffleV2Block (line 120) | class ShuffleV2Block(nn.Module):
    method __init__ (line 121) | def __init__(self, inp, oup, stride):
    method depthwise_conv (line 160) | def depthwise_conv(i, o, kernel_size, stride=1, padding=0, bias=False):
    method forward (line 163) | def forward(self, x):
  class SPP (line 173) | class SPP(nn.Module):
    method __init__ (line 175) | def __init__(self, c1, c2, k=(5, 9, 13)):
    method forward (line 182) | def forward(self, x):
  class Focus (line 187) | class Focus(nn.Module):
    method __init__ (line 189) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 193) | def forward(self, x):  # x(b,c,w,h) -> y(b,4c,w/2,h/2)
  class Concat (line 197) | class Concat(nn.Module):
    method __init__ (line 199) | def __init__(self, dimension=1):
    method forward (line 203) | def forward(self, x):
  class NMS (line 207) | class NMS(nn.Module):
    method forward (line 213) | def forward(self, x):
  class AutoShape (line 217) | class AutoShape(nn.Module):
    method __init__ (line 224) | def __init__(self, model):
    method autoshape (line 228) | def autoshape(self):
    method forward (line 232) | def forward(self, imgs, size=640, augment=False, profile=False):
  class Detections (line 275) | class Detections:
    method __init__ (line 277) | def __init__(self, imgs, pred, names=None):
    method __len__ (line 290) | def __len__(self):
    method tolist (line 293) | def tolist(self):

FILE: modules/facelib/detection/yolov5face/models/experimental.py
  class CrossConv (line 10) | class CrossConv(nn.Module):
    method __init__ (line 12) | def __init__(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False):
    method forward (line 20) | def forward(self, x):
  class MixConv2d (line 24) | class MixConv2d(nn.Module):
    method __init__ (line 26) | def __init__(self, c1, c2, k=(1, 3), s=1, equal_ch=True):
    method forward (line 44) | def forward(self, x):

FILE: modules/facelib/detection/yolov5face/models/yolo.py
  class Detect (line 29) | class Detect(nn.Module):
    method __init__ (line 33) | def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
    method forward (line 46) | def forward(self, x):
    method _make_grid (line 89) | def _make_grid(nx=20, ny=20):
  class Model (line 95) | class Model(nn.Module):
    method __init__ (line 96) | def __init__(self, cfg="yolov5s.yaml", ch=3, nc=None):  # model, input...
    method forward (line 120) | def forward(self, x):
    method forward_once (line 123) | def forward_once(self, x):
    method _initialize_biases (line 134) | def _initialize_biases(self, cf=None):  # initialize biases into Detec...
    method _print_biases (line 143) | def _print_biases(self):
    method fuse (line 149) | def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
    method nms (line 160) | def nms(self, mode=True):  # add or remove NMS module
    method autoshape (line 174) | def autoshape(self):  # add autoShape module
  function parse_model (line 181) | def parse_model(d, ch):  # model_dict, input_channels(3)

FILE: modules/facelib/detection/yolov5face/utils/autoanchor.py
  function check_anchor_order (line 4) | def check_anchor_order(m):

FILE: modules/facelib/detection/yolov5face/utils/datasets.py
  function letterbox (line 5) | def letterbox(img, new_shape=(640, 640), color=(114, 114, 114), auto=Tru...

FILE: modules/facelib/detection/yolov5face/utils/general.py
  function check_img_size (line 9) | def check_img_size(img_size, s=32):
  function make_divisible (line 17) | def make_divisible(x, divisor):
  function xyxy2xywh (line 22) | def xyxy2xywh(x):
  function xywh2xyxy (line 32) | def xywh2xyxy(x):
  function scale_coords (line 42) | def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
  function clip_coords (line 58) | def clip_coords(boxes, img_shape):
  function box_iou (line 66) | def box_iou(box1, box2):
  function non_max_suppression_face (line 89) | def non_max_suppression_face(prediction, conf_thres=0.25, iou_thres=0.45...
  function non_max_suppression (line 168) | def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, cla...
  function scale_coords_landmarks (line 249) | def scale_coords_landmarks(img1_shape, coords, img0_shape, ratio_pad=None):

FILE: modules/facelib/detection/yolov5face/utils/torch_utils.py
  function fuse_conv_and_bn (line 5) | def fuse_conv_and_bn(conv, bn):
  function copy_attr (line 34) | def copy_attr(a, b, include=(), exclude=()):

FILE: modules/facelib/parsing/__init__.py
  function init_parsing_model (line 13) | def init_parsing_model(model_name='bisenet', half=False, device='cuda'):

FILE: modules/facelib/parsing/bisenet.py
  class ConvBNReLU (line 8) | class ConvBNReLU(nn.Module):
    method __init__ (line 10) | def __init__(self, in_chan, out_chan, ks=3, stride=1, padding=1):
    method forward (line 15) | def forward(self, x):
  class BiSeNetOutput (line 21) | class BiSeNetOutput(nn.Module):
    method __init__ (line 23) | def __init__(self, in_chan, mid_chan, num_class):
    method forward (line 28) | def forward(self, x):
  class AttentionRefinementModule (line 34) | class AttentionRefinementModule(nn.Module):
    method __init__ (line 36) | def __init__(self, in_chan, out_chan):
    method forward (line 43) | def forward(self, x):
  class ContextPath (line 53) | class ContextPath(nn.Module):
    method __init__ (line 55) | def __init__(self):
    method forward (line 64) | def forward(self, x):
  class FeatureFusionModule (line 87) | class FeatureFusionModule(nn.Module):
    method __init__ (line 89) | def __init__(self, in_chan, out_chan):
    method forward (line 97) | def forward(self, fsp, fcp):
  class BiSeNet (line 110) | class BiSeNet(nn.Module):
    method __init__ (line 112) | def __init__(self, num_class):
    method forward (line 120) | def forward(self, x, return_feat=False):

FILE: modules/facelib/parsing/parsenet.py
  class NormLayer (line 8) | class NormLayer(nn.Module):
    method __init__ (line 16) | def __init__(self, channels, normalize_shape=None, norm_type='bn'):
    method forward (line 35) | def forward(self, x, ref=None):
  class ReluLayer (line 42) | class ReluLayer(nn.Module):
    method __init__ (line 54) | def __init__(self, channels, relu_type='relu'):
    method forward (line 70) | def forward(self, x):
  class ConvLayer (line 74) | class ConvLayer(nn.Module):
    method __init__ (line 76) | def __init__(self,
    method forward (line 103) | def forward(self, x):
  class ResidualBlock (line 113) | class ResidualBlock(nn.Module):
    method __init__ (line 118) | def __init__(self, c_in, c_out, relu_type='prelu', norm_type='bn', sca...
    method forward (line 132) | def forward(self, x):
  class ParseNet (line 140) | class ParseNet(nn.Module):
    method __init__ (line 142) | def __init__(self,
    method forward (line 188) | def forward(self, x):

FILE: modules/facelib/parsing/resnet.py
  function conv3x3 (line 5) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 10) | class BasicBlock(nn.Module):
    method __init__ (line 12) | def __init__(self, in_chan, out_chan, stride=1):
    method forward (line 26) | def forward(self, x):
  function create_layer_basic (line 41) | def create_layer_basic(in_chan, out_chan, bnum, stride=1):
  class ResNet18 (line 48) | class ResNet18(nn.Module):
    method __init__ (line 50) | def __init__(self):
    method forward (line 60) | def forward(self, x):

FILE: modules/facelib/utils/face_restoration_helper.py
  function get_largest_face (line 12) | def get_largest_face(det_faces, h, w):
  function get_center_face (line 34) | def get_center_face(det_faces, h=0, w=0, center=None):
  class FaceRestoreHelper (line 48) | class FaceRestoreHelper(object):
    method __init__ (line 51) | def __init__(self,
    method set_upscale_factor (line 111) | def set_upscale_factor(self, upscale_factor):
    method read_image (line 114) | def read_image(self, img):
    method get_face_landmarks_5 (line 136) | def get_face_landmarks_5(self,
    method align_warp_face (line 256) | def align_warp_face(self, save_cropped_path=None, border_mode='constan...
    method get_inverse_affine (line 288) | def get_inverse_affine(self, save_inverse_affine_path=None):
    method add_restored_face (line 301) | def add_restored_face(self, face):
    method paste_faces_to_input_image (line 307) | def paste_faces_to_input_image(self, save_path=None, upsample_img=None...
    method clean_all (line 453) | def clean_all(self):

FILE: modules/facelib/utils/face_utils.py
  function compute_increased_bbox (line 7) | def compute_increased_bbox(bbox, increase_area, preserve_aspect=True):
  function get_valid_bboxes (line 24) | def get_valid_bboxes(bboxes, h, w):
  function align_crop_face_landmarks (line 32) | def align_crop_face_landmarks(img,
  function paste_face_back (line 190) | def paste_face_back(img, face, inverse_affine):

FILE: modules/facelib/utils/misc.py
  function download_pretrained_models (line 14) | def download_pretrained_models(file_ids, save_path_root):
  function imwrite (line 38) | def imwrite(img, file_path, params=None, auto_mkdir=True):
  function img2tensor (line 57) | def img2tensor(imgs, bgr2rgb=True, float32=True):
  function load_file_from_url (line 86) | def load_file_from_url(url, model_dir=None, progress=True, file_name=None):
  function scandir (line 106) | def scandir(dir_path, suffix=None, recursive=False, full_path=False):
  function is_gray (line 146) | def is_gray(img, threshold=10):
  function rgb2gray (line 162) | def rgb2gray(img, out_channel=3):
  function bgr2gray (line 169) | def bgr2gray(img, out_channel=3):

FILE: modules/files_cache.py
  class Directory (line 10) | class Directory: # forward declaration
    method __post_init__ (line 40) | def __post_init__(self):
    method from_dict (line 44) | def from_dict(cls, dict_object: dict) -> Directory:
    method clear (line 52) | def clear(self) -> None:
    method update (line 60) | def update(self, source_directory: Directory) -> Directory:
    method _update (line 65) | def _update(self, source:Directory) -> None:
    method exists (line 75) | def exists(self) -> bool:
    method is_directory (line 79) | def is_directory(self) -> bool:
    method live_mtime (line 83) | def live_mtime(self) -> float:
    method is_stale (line 87) | def is_stale(self) -> bool:
  function real_path (line 25) | def real_path(directory_path:str) -> Union[str, None]:
  class Directory (line 34) | class Directory(Directory): # pylint: disable=E0102
    method __post_init__ (line 40) | def __post_init__(self):
    method from_dict (line 44) | def from_dict(cls, dict_object: dict) -> Directory:
    method clear (line 52) | def clear(self) -> None:
    method update (line 60) | def update(self, source_directory: Directory) -> Directory:
    method _update (line 65) | def _update(self, source:Directory) -> None:
    method exists (line 75) | def exists(self) -> bool:
    method is_directory (line 79) | def is_directory(self) -> bool:
    method live_mtime (line 83) | def live_mtime(self) -> float:
    method is_stale (line 87) | def is_stale(self) -> bool:
  class DirectoryCache (line 91) | class DirectoryCache(UserDict, DirectoryCollection):
    method __delattr__ (line 92) | def __delattr__(self, directory_path: str) -> None:
  function clean_directory (line 100) | def clean_directory(directory: Directory, /, recursive: RecursiveType=Fa...
  function get_directory (line 128) | def get_directory(directory_or_path: str, /, fetch: bool=True) -> Union[...
  function fetch_directory (line 146) | def fetch_directory(directory_path: str) -> Union[Directory, None]:
  function _walk (line 153) | def _walk(top, recurse:RecursiveType=True) -> Directory:
  function _cached_walk (line 182) | def _cached_walk(top, recurse:RecursiveType=True) -> Directory:
  function walk (line 196) | def walk(top, recurse:RecursiveType=True, cached=True) -> Directory:
  function delete_cached_directory (line 200) | def delete_cached_directory(directory_path:str) -> bool:
  function is_directory (line 206) | def is_directory(dir_path:str) -> bool:
  function directory_mtime (line 210) | def directory_mtime(directory_path:str, /, recursive:RecursiveType=True)...
  function unique_directories (line 214) | def unique_directories(directories:DirectoryPathList, /, recursive:Recur...
  function unique_paths (line 247) | def unique_paths(directory_paths:DirectoryPathList) -> DirectoryPathIter...
  function get_directories (line 252) | def get_directories(*directory_paths: DirectoryPathList, fetch:bool=True...
  function directory_files (line 258) | def directory_files(*directories_or_paths: Union[DirectoryPathList, Dire...
  function extension_filter (line 278) | def extension_filter(ext_filter: Optional[ExtensionList]=None, ext_black...
  function not_hidden (line 288) | def not_hidden(filepath: str) -> bool:
  function filter_files (line 292) | def filter_files(file_paths: FilePathList, ext_filter: Optional[Extensio...
  function list_files (line 296) | def list_files(*directory_paths:DirectoryPathList, ext_filter: Optional[...

FILE: modules/flash_attn_triton_amd/fwd_prefill.py
  function load_fn (line 11) | def load_fn(ptrs, offset_first, offset_second, boundary_first, boundary_...
  function _attn_fwd_inner (line 28) | def _attn_fwd_inner(acc, l_i, m_i, q, k_ptrs, v_ptrs, bias_ptrs, stride_...
  function get_cdna_autotune_configs (line 149) | def get_cdna_autotune_configs():
  function get_rdna_autotune_configs (line 169) | def get_rdna_autotune_configs():
  function get_autotune_configs (line 189) | def get_autotune_configs():
  function attn_fwd (line 224) | def attn_fwd(Q, K, V, bias, Cache_seqlens, Cache_batch_idx, # pylint: di...
  function attention_prefill_forward_triton_impl (line 489) | def attention_prefill_forward_triton_impl(

FILE: modules/flash_attn_triton_amd/interface_fa.py
  function fwd (line 6) | def fwd(q: torch.Tensor,

FILE: modules/flash_attn_triton_amd/utils.py
  class MetaData (line 21) | class MetaData():
    method __repr__ (line 47) | def __repr__(self) -> str:
    method __init__ (line 66) | def __init__(self, sm_scale=1.0):
    method set_varlen_params (line 69) | def set_varlen_params(self, cu_seqlens_q, cu_seqlens_k, max_seqlen_q, ...
    method need_bias (line 81) | def need_bias(self, bias, batch, nheads, seqlen_q, seqlen_k):
    method need_alibi (line 88) | def need_alibi(self, alibi_slopes, batch, nheads):
    method need_causal (line 95) | def need_causal(self, causal):
    method need_rotary (line 98) | def need_rotary(self, sin, cos, rotary_interleaved, rotary_conjunction...
    method need_dropout (line 104) | def need_dropout(self, dropout_p, return_scores = True):
    method check_args (line 110) | def check_args(self, q, k, v, o):
  function random_seqlens_composition (line 136) | def random_seqlens_composition(SEQ_LEN, BATCH):
  function generate_varlen_tensor (line 148) | def generate_varlen_tensor(
  function generate_bshd_tensor (line 198) | def generate_bshd_tensor(BATCH, SEQ_LEN, NUM_HEADS, D_HEAD, dtype, devic...
  function generate_bhsd_tensor (line 209) | def generate_bhsd_tensor(BATCH, NUM_HEADS, SEQ_LEN, D_HEAD, dtype, devic...
  function input_helper (line 220) | def input_helper(
  function compute_alibi_block (line 319) | def compute_alibi_block(alibi_slope, seqlen_q, seqlen_k, offs_m, offs_n,...
  function get_shape_from_layout (line 353) | def get_shape_from_layout(
  function get_shapes_from_layout (line 377) | def get_shapes_from_layout(q, k, layout, cu_seqlens_q = None, cu_seqlens...
  function get_stride_from_layout (line 387) | def get_stride_from_layout(x: torch.Tensor, layout:Literal["bshd", "bhsd...
  function get_shape_and_strides_from_layout (line 398) | def get_shape_and_strides_from_layout(x: torch.Tensor, layout: Literal["...
  function get_strides_from_layout (line 401) | def get_strides_from_layout(q, k, v, o, layout):
  function get_padded_headsize (line 408) | def get_padded_headsize(size):
  function compute_alibi_tensor_ref (line 416) | def compute_alibi_tensor_ref(alibi_slopes, seqlen_q, seqlen_k):
  function create_dropout_mask (line 425) | def create_dropout_mask(dropout_p, shape, seed):
  function create_dropout_mask_varlen (line 430) | def create_dropout_mask_varlen(dropout_p, batch, nheads_q, cu_seqlens_q,...
  function write_dropout_mask (line 446) | def write_dropout_mask(x, tensor_name = "tensor"):
  function is_cdna (line 485) | def is_cdna():
  function is_rdna (line 490) | def is_rdna():

FILE: modules/framepack/create-video.py
  function auth (line 23) | def auth():
  function get (line 29) | def get(endpoint: str, dct: dict = None):
  function post (line 37) | def post(endpoint: str, dct: dict = None):
  function encode (line 45) | def encode(f):
  function generate (line 60) | def generate(args): # pylint: disable=redefined-outer-name

FILE: modules/framepack/framepack_api.py
  class ReqFramepack (line 7) | class ReqFramepack(BaseModel):
  class ResFramepack (line 46) | class ResFramepack(BaseModel):
  function framepack_post (line 52) | def framepack_post(request: ReqFramepack):
  function create_api (line 131) | def create_api(_fastapi, _gradioapp):

FILE: modules/framepack/framepack_hijack.py
  function set_progress_bar_config (line 23) | def set_progress_bar_config():
  function set_prompt_template (line 32) | def set_prompt_template(prompt, system_prompt:str=None, optimized_prompt...

FILE: modules/framepack/framepack_install.py
  function rename (line 8) | def rename(src:str, dst:str):
  function install_requirements (line 19) | def install_requirements(attention:str='SDPA'):
  function git_clone (line 35) | def git_clone(git_repo:str, git_dir:str, tmp_dir:str):
  function git_update (line 61) | def git_update(git_dir:str, git_commit:str):

FILE: modules/framepack/framepack_load.py
  function split_url (line 28) | def split_url(url):
  function set_model (line 37) | def set_model(receipe: str=None):
  function get_model (line 50) | def get_model():
  function reset_model (line 57) | def reset_model():
  function load_model (line 64) | def load_model(variant:str=None, pipeline:str=None, text_encoder:str=Non...
  function unload_model (line 211) | def unload_model():

FILE: modules/framepack/framepack_ui.py
  function change_sections (line 9) | def change_sections(duration, mp4_fps, mp4_interpolate, latent_ws, varia...
  function create_ui (line 15) | def create_ui(prompt, negative, styles, _overrides, init_image, last_ima...

FILE: modules/framepack/framepack_vae.py
  function vae_decode_simple (line 30) | def vae_decode_simple(latents):
  function vae_decode_tiny (line 43) | def vae_decode_tiny(latents):
  function vae_decode_remote (line 58) | def vae_decode_remote(latents):
  function vae_decode_full (line 71) | def vae_decode_full(latents):
  function vae_decode (line 79) | def vae_decode(latents, vae_type):
  function vae_encode (line 94) | def vae_encode(image):

FILE: modules/framepack/framepack_worker.py
  function get_latent_paddings (line 13) | def get_latent_paddings(mp4_fps, mp4_interpolate, latent_window_size, to...
  function worker (line 32) | def worker(

FILE: modules/framepack/framepack_wrappers.py
  function prepare_image (line 23) | def prepare_image(image, resolution):
  function interpolate_prompts (line 48) | def interpolate_prompts(prompts, steps):
  function prepare_prompts (line 67) | def prepare_prompts(p, init_image, prompt:str, section_prompt:str, num_s...
  function load_model (line 93) | def load_model(variant, attention):
  function unload_model (line 110) | def unload_model():
  function run_framepack (line 116) | def run_framepack(task_id, _ui_state, init_image, end_image, start_weigh...

FILE: modules/framepack/pipeline/bucket_tools.py
  function find_nearest_bucket (line 21) | def find_nearest_bucket(h, w, resolution=640):

FILE: modules/framepack/pipeline/clip_vision.py
  function hf_clip_vision_encode (line 4) | def hf_clip_vision_encode(image, feature_extractor, image_encoder):

FILE: modules/framepack/pipeline/dit_common.py
  function LayerNorm_forward (line 10) | def LayerNorm_forward(self, x):
  function FP32LayerNorm_forward (line 18) | def FP32LayerNorm_forward(self, x):
  function RMSNorm_forward (line 32) | def RMSNorm_forward(self, hidden_states):
  function AdaLayerNormContinuous_forward (line 46) | def AdaLayerNormContinuous_forward(self, x, conditioning_embedding):

FILE: modules/framepack/pipeline/hunyuan.py
  function encode_prompt_conds (line 7) | def encode_prompt_conds(prompt, text_encoder, text_encoder_2, tokenizer,...
  function vae_decode_fake (line 61) | def vae_decode_fake(latents):
  function vae_decode (line 93) | def vae_decode(latents, vae, image_mode=False):
  function vae_encode (line 107) | def vae_encode(image, vae):

FILE: modules/framepack/pipeline/hunyuan_video_packed.py
  function pad_for_3d_conv (line 55) | def pad_for_3d_conv(x, kernel_size):
  function center_down_sample_3d (line 64) | def center_down_sample_3d(x, kernel_size):
  function get_cu_seqlens (line 73) | def get_cu_seqlens(text_mask, img_len):
  function apply_rotary_emb_transposed (line 90) | def apply_rotary_emb_transposed(x, freqs_cis):
  function attn_varlen_func (line 99) | def attn_varlen_func(q, k, v, cu_seqlens_q, cu_seqlens_kv, max_seqlen_q,...
  class HunyuanAttnProcessorFlashAttnDouble (line 134) | class HunyuanAttnProcessorFlashAttnDouble:
    method __call__ (line 135) | def __call__(self, attn, hidden_states, encoder_hidden_states, attenti...
  class HunyuanAttnProcessorFlashAttnSingle (line 180) | class HunyuanAttnProcessorFlashAttnSingle:
    method __call__ (line 181) | def __call__(self, attn, hidden_states, encoder_hidden_states, attenti...
  class CombinedTimestepGuidanceTextProjEmbeddings (line 210) | class CombinedTimestepGuidanceTextProjEmbeddings(nn.Module):
    method __init__ (line 211) | def __init__(self, embedding_dim, pooled_projection_dim):
    method forward (line 219) | def forward(self, timestep, guidance, pooled_projection):
  class CombinedTimestepTextProjEmbeddings (line 234) | class CombinedTimestepTextProjEmbeddings(nn.Module):
    method __init__ (line 235) | def __init__(self, embedding_dim, pooled_projection_dim):
    method forward (line 242) | def forward(self, timestep, pooled_projection):
  class HunyuanVideoAdaNorm (line 253) | class HunyuanVideoAdaNorm(nn.Module):
    method __init__ (line 254) | def __init__(self, in_features: int, out_features: Optional[int] = Non...
    method forward (line 261) | def forward(
  class HunyuanVideoIndividualTokenRefinerBlock (line 270) | class HunyuanVideoIndividualTokenRefinerBlock(nn.Module):
    method __init__ (line 271) | def __init__(
    method forward (line 297) | def forward(
  class HunyuanVideoIndividualTokenRefiner (line 320) | class HunyuanVideoIndividualTokenRefiner(nn.Module):
    method __init__ (line 321) | def __init__(
    method forward (line 345) | def forward(
  class HunyuanVideoTokenRefiner (line 367) | class HunyuanVideoTokenRefiner(nn.Module):
    method __init__ (line 368) | def __init__(
    method forward (line 395) | def forward(
  class HunyuanVideoRotaryPosEmbed (line 416) | class HunyuanVideoRotaryPosEmbed(nn.Module):
    method __init__ (line 417) | def __init__(self, rope_dim, theta):
    method get_frequency (line 423) | def get_frequency(self, dim, pos):
    method forward_inner (line 430) | def forward_inner(self, frame_indices, height, width, device):
    method forward (line 447) | def forward(self, frame_indices, height, width, device):
  class AdaLayerNormZero (line 454) | class AdaLayerNormZero(nn.Module):
    method __init__ (line 455) | def __init__(self, embedding_dim: int, norm_type="layer_norm", bias=Tr...
    method forward (line 464) | def forward(
  class AdaLayerNormZeroSingle (line 476) | class AdaLayerNormZeroSingle(nn.Module):
    method __init__ (line 477) | def __init__(self, embedding_dim: int, norm_type="layer_norm", bias=Tr...
    method forward (line 487) | def forward(
  class AdaLayerNormContinuous (line 499) | class AdaLayerNormContinuous(nn.Module):
    method __init__ (line 500) | def __init__(
    method forward (line 517) | def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
  class HunyuanVideoSingleTransformerBlock (line 525) | class HunyuanVideoSingleTransformerBlock(nn.Module):
    method __init__ (line 526) | def __init__(
    method forward (line 556) | def forward(
  class HunyuanVideoTransformerBlock (line 599) | class HunyuanVideoTransformerBlock(nn.Module):
    method __init__ (line 600) | def __init__(
    method forward (line 634) | def forward(
  class ClipVisionProjection (line 674) | class ClipVisionProjection(nn.Module):
    method __init__ (line 675) | def __init__(self, in_channels, out_channels):
    method forward (line 680) | def forward(self, x):
  class HunyuanVideoPatchEmbed (line 685) | class HunyuanVideoPatchEmbed(nn.Module):
    method __init__ (line 686) | def __init__(self, patch_size, in_chans, embed_dim):
  class HunyuanVideoPatchEmbedForCleanLatents (line 691) | class HunyuanVideoPatchEmbedForCleanLatents(nn.Module):
    method __init__ (line 692) | def __init__(self, inner_dim):
    method initialize_weight_from_another_conv3d (line 699) | def initialize_weight_from_another_conv3d(self, another_layer):
  class HunyuanVideoTransformer3DModelPacked (line 718) | class HunyuanVideoTransformer3DModelPacked(ModelMixin, ConfigMixin, Peft...
    method __init__ (line 720) | def __init__(
    method install_image_projection (line 796) | def install_image_projection(self, in_channels):
    method install_clean_x_embedder (line 801) | def install_clean_x_embedder(self):
    method enable_gradient_checkpointing (line 805) | def enable_gradient_checkpointing(self):
    method disable_gradient_checkpointing (line 808) | def disable_gradient_checkpointing(self):
    method initialize_teacache (line 811) | def initialize_teacache(self, enable_teacache=True, num_steps=25, rel_...
    method gradient_checkpointing_method (line 821) | def gradient_checkpointing_method(self, block, *args):
    method process_input_hidden_states (line 828) | def process_input_hidden_states(
    method forward (line 887) | def forward(

FILE: modules/framepack/pipeline/k_diffusion_hunyuan.py
  function flux_time_shift (line 8) | def flux_time_shift(t, mu=1.15, sigma=1.0):
  function calculate_flux_mu (line 12) | def calculate_flux_mu(context_length, x1=256, y1=0.5, x2=4096, y2=1.15, ...
  function get_flux_sigmas_from_mu (line 20) | def get_flux_sigmas_from_mu(n, mu):
  function sample_hunyuan (line 27) | def sample_hunyuan(

FILE: modules/framepack/pipeline/thread_utils.py
  class Listener (line 6) | class Listener:
    method _process_tasks (line 12) | def _process_tasks(cls):
    method add_task (line 30) | def add_task(cls, func, *args, **kwargs):
  function async_run (line 39) | def async_run(func, *args, **kwargs):
  class FIFOQueue (line 43) | class FIFOQueue:
    method __init__ (line 44) | def __init__(self):
    method push (line 48) | def push(self, item):
    method pop (line 52) | def pop(self):
    method top (line 58) | def top(self):
    method next (line 64) | def next(self):
  class AsyncStream (line 73) | class AsyncStream:
    method __init__ (line 74) | def __init__(self):

FILE: modules/framepack/pipeline/uni_pc_fm.py
  function expand_dims (line 12) | def expand_dims(v, dims):
  function test_solver (line 19) | def test_solver():
  function linalg_solve (line 31) | def linalg_solve(A, B, device):
  class FlowMatchUniPC (line 46) | class FlowMatchUniPC:
    method __init__ (line 47) | def __init__(self, model, extra_args, variant='bh1'):
    method model_fn (line 52) | def model_fn(self, x, t):
    method update_fn (line 55) | def update_fn(self, x, model_prev_list, t_prev_list, t, order):
    method sample (line 141) | def sample(self, x, sigmas, callback=None, disable_pbar=False):
  function sample_unipc (line 169) | def sample_unipc(model, noise, sigmas, extra_args=None, callback=None, d...

FILE: modules/framepack/pipeline/utils.py
  function min_resize (line 14) | def min_resize(x, m):
  function d_resize (line 31) | def d_resize(x, y):
  function resize_and_center_crop (line 43) | def resize_and_center_crop(image, target_width, target_height):
  function resize_and_center_crop_pytorch (line 61) | def resize_and_center_crop_pytorch(image, target_width, target_height):
  function resize_without_crop (line 80) | def resize_without_crop(image, target_width, target_height):
  function just_crop (line 89) | def just_crop(image, w, h):
  function write_to_json (line 103) | def write_to_json(data, file_path):
  function read_from_json (line 111) | def read_from_json(file_path):
  function get_active_parameters (line 117) | def get_active_parameters(m):
  function cast_training_params (line 121) | def cast_training_params(m, dtype=torch.float32):
  function separate_lora_AB (line 130) | def separate_lora_AB(parameters, B_patterns=None):
  function set_attr_recursive (line 146) | def set_attr_recursive(obj, attr, value):
  function batch_mixture (line 155) | def batch_mixture(a, b=None, probability_a=0.5, mask_a=None):
  function zero_module (line 171) | def zero_module(module):
  function supress_lower_channels (line 178) | def supress_lower_channels(m, k, alpha=0.01):
  function freeze_module (line 188) | def freeze_module(m):
  function get_latest_safetensors (line 196) | def get_latest_safetensors(folder_path):
  function generate_random_prompt_from_tags (line 207) | def generate_random_prompt_from_tags(tags_str, min_length=3, max_length=...
  function interpolate_numbers (line 214) | def interpolate_numbers(a, b, n, round_to_int=False, gamma=1.0):
  function uniform_random_by_intervals (line 221) | def uniform_random_by_intervals(inclusive, exclusive, n, round_to_int=Fa...
  function soft_append_bcthw (line 230) | def soft_append_bcthw(history, current, overlap=0):
  function save_bcthw_as_mp4 (line 244) | def save_bcthw_as_mp4(x, output_filename, fps=10, crf=0):
  function save_bcthw_as_png (line 261) | def save_bcthw_as_png(x, output_filename):
  function save_bchw_as_png (line 270) | def save_bchw_as_png(x, output_filename):
  function add_tensors_with_padding (line 279) | def add_tensors_with_padding(tensor1, tensor2):
  function visualize_txt_as_img (line 298) | def visualize_txt_as_img(width, height, text, font_path='font/DejaVuSans...
  function blue_mark (line 334) | def blue_mark(x):
  function green_mark (line 342) | def green_mark(x):
  function frame_mark (line 349) | def frame_mark(x):
  function pytorch2numpy (line 359) | def pytorch2numpy(imgs):
  function numpy2pytorch (line 370) | def numpy2pytorch(imgs):
  function duplicate_prefix_to_suffix (line 377) | def duplicate_prefix_to_suffix(x, count, zero_out=False):
  function weighted_mse (line 384) | def weighted_mse(a, b, weight):
  function clamped_linear_interpolation (line 388) | def clamped_linear_interpolation(x, x_min, y_min, x_max, y_max, sigma=1.0):
  function expand_to_dims (line 395) | def expand_to_dims(x, target_dims):
  function repeat_to_batch_size (line 399) | def repeat_to_batch_size(tensor: torch.Tensor, batch_size: int):
  function dim5 (line 416) | def dim5(x):
  function dim4 (line 420) | def dim4(x):
  function dim3 (line 424) | def dim3(x):
  function crop_or_pad_yield_mask (line 428) | def crop_or_pad_yield_mask(x, length):
  function extend_dim (line 443) | def extend_dim(x, dim, minimal_length, zero_pad=False):
  function lazy_positional_encoding (line 461) | def lazy_positional_encoding(t, repeats=None):
  function state_dict_offset_merge (line 478) | def state_dict_offset_merge(A, B, C=None):
  function state_dict_weighted_merge (line 495) | def state_dict_weighted_merge(state_dicts, weights):
  function group_files_by_folder (line 522) | def group_files_by_folder(all_files):
  function generate_timestamp (line 535) | def generate_timestamp():
  function write_PIL_image_with_png_info (line 543) | def write_PIL_image_with_png_info(image, metadata, path):
  function torch_safe_save (line 554) | def torch_safe_save(content, path):
  function move_optimizer_to_device (line 560) | def move_optimizer_to_device(optimizer, device):

FILE: modules/framepack/pipeline/wrapper.py
  function append_dims (line 4) | def append_dims(x, target_dims):
  function rescale_noise_cfg (line 8) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=1.0):
  function fm_wrapper (line 19) | def fm_wrapper(transformer, t_scale=1000.0):

FILE: modules/generation_parameters_copypaste.py
  class ParamBinding (line 25) | class ParamBinding:
    method __init__ (line 26) | def __init__(self, paste_button, tabname: str, source_text_component=N...
  function reset (line 37) | def reset():
  function image_from_url_text (line 42) | def image_from_url_text(filedata):
  function add_paste_fields (line 86) | def add_paste_fields(tabname: str, init_img: gr.Image | gr.HTML | None, ...
  function get_all_fields (line 134) | def get_all_fields():
  function create_buttons (line 144) | def create_buttons(tabs_list: list[str]) -> dict[str, gr.Button]:
  function should_skip (line 164) | def should_skip(param: str):
  function register_paste_params_button (line 187) | def register_paste_params_button(binding: ParamBinding):
  function connect_paste_params_buttons (line 191) | def connect_paste_params_buttons():
  function send_image (line 237) | def send_image(x):
  function create_override_settings_dict (line 242) | def create_override_settings_dict(text_pairs):
  function connect_paste (line 256) | def connect_paste(button, local_paste_fields, input_comp, override_setti...

FILE: modules/ggml/__init__.py
  function install_gguf (line 8) | def install_gguf():
  function load_gguf_state_dict (line 29) | def load_gguf_state_dict(path: str, compute_dtype: torch.dtype) -> dict:
  function load_gguf (line 48) | def load_gguf(path, cls, compute_dtype: torch.dtype):

FILE: modules/ggml/gguf_tensor.py
  function dequantize_and_run (line 9) | def dequantize_and_run(func, args, kwargs):
  function apply_to_quantized_tensor (line 21) | def apply_to_quantized_tensor(func, args, kwargs):
  class GGMLTensor (line 55) | class GGMLTensor(torch.Tensor):
    method __new__ (line 63) | def __new__(
    method __init__ (line 81) | def __init__(
    method __repr__ (line 94) | def __repr__(self, *, tensor_contents=None):
    method size (line 98) | def size(self, dim: None = None) -> torch.Size: ...
    method size (line 101) | def size(self, dim: int) -> int: ...
    method size (line 103) | def size(self, dim: int | None = None):
    method shape (line 110) | def shape(self) -> torch.Size:  # pyright: ignore[reportIncompatibleVa...
    method quantized_shape (line 115) | def quantized_shape(self) -> torch.Size:
    method requires_grad_ (line 119) | def requires_grad_(self, mode: bool = True) -> torch.Tensor:
    method get_dequantized_tensor (line 125) | def get_dequantized_tensor(self):
    method __torch_dispatch__ (line 143) | def __torch_dispatch__(cls, func, types, args, kwargs):

FILE: modules/ggml/gguf_utils.py
  function get_scale_min (line 16) | def get_scale_min(scales: torch.Tensor):
  function dequantize_blocks_Q8_0 (line 30) | def dequantize_blocks_Q8_0(
  function dequantize_blocks_Q5_1 (line 39) | def dequantize_blocks_Q5_1(
  function dequantize_blocks_Q5_0 (line 60) | def dequantize_blocks_Q5_0(
  function dequantize_blocks_Q4_1 (line 81) | def dequantize_blocks_Q4_1(
  function dequantize_blocks_Q4_0 (line 98) | def dequantize_blocks_Q4_0(
  function dequantize_blocks_BF16 (line 113) | def dequantize_blocks_BF16(
  function dequantize_blocks_Q6_K (line 119) | def dequantize_blocks_Q6_K(
  function dequantize_blocks_Q5_K (line 149) | def dequantize_blocks_Q5_K(
  function dequantize_blocks_Q4_K (line 177) | def dequantize_blocks_Q4_K(
  function dequantize_blocks_Q3_K (line 199) | def dequantize_blocks_Q3_K(
  function dequantize_blocks_Q2_K (line 234) | def dequantize_blocks_Q2_K(
  function is_torch_compatible (line 273) | def is_torch_compatible(tensor: Optional[torch.Tensor]):
  function is_quantized (line 277) | def is_quantized(tensor: torch.Tensor):
  function dequantize (line 281) | def dequantize(
  function to_uint32 (line 298) | def to_uint32(x: torch.Tensor) -> torch.Tensor:
  function split_block_dims (line 303) | def split_block_dims(blocks: torch.Tensor, *args):

FILE: modules/gr_hijack.py
  function process_kanvas (line 15) | def process_kanvas(self, x): # only used when kanvas overrides gr.Image ...
  function gr_image_preprocess (line 46) | def gr_image_preprocess(self, x):
  function add_classes_to_gradio_component (line 73) | def add_classes_to_gradio_component(comp):
  function IOComponent_init (line 82) | def IOComponent_init(self, *args, **kwargs):
  function Block_get_config (line 95) | def Block_get_config(self):
  function BlockContext_init (line 104) | def BlockContext_init(self, *args, **kwargs):
  function Blocks_get_config_file (line 116) | def Blocks_get_config_file(self, *args, **kwargs):
  function patch_gradio (line 124) | def patch_gradio():
  function init (line 153) | def init():

FILE: modules/gr_tempdir.py
  function register_tmp_file (line 13) | def register_tmp_file(gradio, filename):
  function check_tmp_file (line 18) | def check_tmp_file(gradio, filename):
  function pil_to_temp_file (line 51) | def pil_to_temp_file(self, img: Image, dir: str, format="png") -> str: #...
  function on_tmpdir_changed (line 98) | def on_tmpdir_changed():
  function cleanup_tmpdr (line 104) | def cleanup_tmpdr():

FILE: modules/hashes.py
  function init_cache (line 14) | def init_cache():
  function dump_cache (line 20) | def dump_cache():
  function cache (line 24) | def cache(subsection):
  function calculate_sha256 (line 33) | def calculate_sha256(filename, quiet=False):
  function sha256_from_cache (line 57) | def sha256_from_cache(filename, title, use_addnet_hash=False):
  function sha256 (line 69) | def sha256(filename, title, use_addnet_hash=False):
  function addnet_hash_safetensors (line 103) | def addnet_hash_safetensors(b):

FILE: modules/hidiffusion/__init__.py
  function apply (line 8) | def apply(p, model_type):
  function unapply (line 42) | def unapply():

FILE: modules/hidiffusion/hidiffusion.py
  function sd15_hidiffusion_key (line 9) | def sd15_hidiffusion_key():
  function sdxl_hidiffusion_key (line 23) | def sdxl_hidiffusion_key():
  function sdxl_turbo_hidiffusion_key (line 43) | def sdxl_turbo_hidiffusion_key():
  function make_diffusers_transformer_block (line 82) | def make_diffusers_transformer_block(block_class: Type[torch.nn.Module])...
  function make_diffusers_cross_attn_down_block (line 256) | def make_diffusers_cross_attn_down_block(block_class: Type[torch.nn.Modu...
  function make_diffusers_cross_attn_up_block (line 388) | def make_diffusers_cross_attn_up_block(block_class: Type[torch.nn.Module...
  function make_diffusers_downsampler_block (line 487) | def make_diffusers_downsampler_block(block_class: Type[torch.nn.Module])...
  function make_diffusers_upsampler_block (line 554) | def make_diffusers_upsampler_block(block_class: Type[torch.nn.Module]) -...
  function hook_diffusion_model (line 608) | def hook_diffusion_model(model: torch.nn.Module):
  function apply_hidiffusion (line 617) | def apply_hidiffusion(
  function remove_hidiffusion (line 700) | def remove_hidiffusion(model: torch.nn.Module):

FILE: modules/hidiffusion/hidiffusion_controlnet.py
  function make_diffusers_unet_2d_condition (line 13) | def make_diffusers_unet_2d_condition(block_class):
  function make_diffusers_sdxl_contrtolnet_ppl (line 264) | def make_diffusers_sdxl_contrtolnet_ppl(block_class):

FILE: modules/hidiffusion/utils.py
  function isinstance_str (line 4) | def isinstance_str(x: object, cls_name: str):
  function init_generator (line 19) | def init_generator(device: torch.device, fallback: torch.Generator=None):

FILE: modules/history.py
  class Item (line 12) | class Item():
    method __init__ (line 13) | def __init__(self, latent, preview=None, info=None, ops=[]):
  class History (line 23) | class History():
    method __init__ (line 24) | def __init__(self):
    method count (line 29) | def count(self):
    method size (line 33) | def size(self):
    method list (line 40) | def list(self):
    method selected (line 45) | def selected(self):
    method find (line 55) | def find(self, name):
    method add (line 61) | def add(self, latent, preview=None, info=None, ops=[]):
    method clear (line 71) | def clear(self):
    method load (line 75) | def load(self):
    method save (line 78) | def save(self):

FILE: modules/images.py
  function sanitize_filename_part (line 44) | def sanitize_filename_part(text, replace_spaces=True):
  function atomically_save_image (line 59) | def atomically_save_image():
  function save_image (line 154) | def save_image(image,
  function safe_decode_string (line 239) | def safe_decode_string(s: bytes):
  function parse_comfy_metadata (line 256) | def parse_comfy_metadata(data: dict):
  function parse_invoke_metadata (line 294) | def parse_invoke_metadata(data: dict):
  function parse_novelai_metadata (line 316) | def parse_novelai_metadata(data: dict):
  function read_info_from_image (line 328) | def read_info_from_image(image: Image.Image, watermark: bool = False) ->...
  function image_data (line 394) | def image_data(data):
  function flatten (line 421) | def flatten(img, bgcolor):
  function draw_overlay (line 430) | def draw_overlay(im, text: str = '', y_offset: int = 0):
  function set_watermark (line 438) | def set_watermark(image, wm_text: str | None = None, wm_image: Image.Ima...
  function get_watermark (line 500) | def get_watermark(image):

FILE: modules/images_grid.py
  function check_grid_size (line 11) | def check_grid_size(imgs):
  function get_grid_size (line 28) | def get_grid_size(imgs, batch_size=1, rows=None, cols=None):
  function image_grid (line 60) | def image_grid(imgs, batch_size:int=1, rows:int=None, cols:int=None):
  function split_grid (line 75) | def split_grid(image, tile_w=512, tile_h=512, overlap=64):
  function combine_grid (line 100) | def combine_grid(grid):
  class GridAnnotation (line 125) | class GridAnnotation:
    method __init__ (line 126) | def __init__(self, text='', is_active=True):
  function get_font (line 132) | def get_font(fontsize):
  function draw_grid_annotations (line 139) | def draw_grid_annotations(im, width, height, x_texts, y_texts, margin=0,...
  function draw_prompt_matrix (line 212) | def draw_prompt_matrix(im, width, height, all_prompts, margin=0):

FILE: modules/images_namegen.py
  class FilenameGenerator (line 26) | class FilenameGenerator:
    method __init__ (line 68) | def __init__(self, p, seed, prompt, image=None, grid=False, width=None...
    method hasprompt (line 98) | def hasprompt(self, *args):
    method image_hash (line 114) | def image_hash(self):
    method prompt_full (line 125) | def prompt_full(self):
    method prompt_words (line 128) | def prompt_words(self):
    method prompt_no_style (line 138) | def prompt_no_style(self):
    method datetime (line 149) | def datetime(self, *args):
    method prompt_sanitize (line 164) | def prompt_sanitize(self, prompt):
    method sanitize (line 170) | def sanitize(self, filename):
    method safe_int (line 207) | def safe_int(self, s):
    method sequence (line 213) | def sequence(self, fn):
    method apply (line 236) | def apply(self, x):
  function get_next_sequence_number (line 284) | def get_next_sequence_number(path, basename): # pylint: disable=unused-a...

FILE: modules/images_resize.py
  function resize_image (line 10) | def resize_image(resize_mode: int, im: Union[Image.Image, torch.Tensor],...

FILE: modules/img2img.py
  function validate_inputs (line 17) | def validate_inputs(inputs):
  function process_batch (line 27) | def process_batch(p, input_files, input_dir, output_dir, inpaint_mask_di...
  function img2img (line 150) | def img2img(id_task: str, state: str, mode: int,

FILE: modules/infotext.py
  function quote (line 16) | def quote(text):
  function unquote (line 22) | def unquote(text):
  function parse (line 31) | def parse(infotext):

FILE: modules/intel/ipex/__init__.py
  function ipex_init (line 19) | def ipex_init(): # pylint: disable=too-many-statements

FILE: modules/intel/ipex/attention.py
  function find_split_size (line 16) | def find_split_size(original_size: int, slice_block_size: int, slice_rat...
  function find_sdpa_slice_sizes (line 29) | def find_sdpa_slice_sizes(query_shape: Tuple[int], key_shape: Tuple[int]...
  function dynamic_scaled_dot_product_attention (line 62) | def dynamic_scaled_dot_product_attention(query: torch.FloatTensor, key: ...

FILE: modules/intel/ipex/device_prop.py
  function mb_to_byte (line 3) | def mb_to_byte(mb: int) -> int:

FILE: modules/intel/ipex/diffusers.py
  function fourier_filter (line 13) | def fourier_filter(x_in, threshold, scale):
  class FluxPosEmbed (line 19) | class FluxPosEmbed(torch.nn.Module):
    method __init__ (line 20) | def __init__(self, theta: int, axes_dim):
    method forward (line 25) | def forward(self, ids: torch.Tensor) -> torch.Tensor:
  function hidream_rope (line 45) | def hidream_rope(pos: torch.Tensor, dim: int, theta: int) -> torch.Tensor:
  function get_1d_sincos_pos_embed_from_grid (line 63) | def get_1d_sincos_pos_embed_from_grid(embed_dim, pos, output_type="np"):
  function apply_rotary_emb (line 83) | def apply_rotary_emb(x, freqs_cis, use_real: bool = True, use_real_unbin...
  function ipex_diffusers (line 112) | def ipex_diffusers(device_supports_fp64=False):

FILE: modules/intel/ipex/hijacks.py
  function is_cuda (line 22) | def is_cuda(self):
  function check_device_type (line 26) | def check_device_type(device, device_type: str) -> bool:
  function check_cuda (line 33) | def check_cuda(device) -> bool:
  function return_xpu (line 37) | def return_xpu(device): # keep the device instance type, aka return stri...
  function autocast_init (line 44) | def autocast_init(self, device_type=None, dtype=None, enabled=True, cach...
  function GradScaler_init (line 53) | def GradScaler_init(self, device: str = None, init_scale: float = 2.0**1...
  function torch_is_autocast_enabled (line 62) | def torch_is_autocast_enabled(device_type=None):
  function torch_get_autocast_dtype (line 71) | def torch_get_autocast_dtype(device_type=None):
  function interpolate (line 82) | def interpolate(tensor, size=None, scale_factor=None, mode="nearest", al...
  function functional_pad (line 96) | def functional_pad(input, pad, mode="constant", value=None):
  function fft_fftn (line 106) | def fft_fftn(input, s=None, dim=None, norm=None, *, out=None):
  function fft_ifftn (line 114) | def fft_ifftn(input, s=None, dim=None, norm=None, *, out=None):
  function from_numpy (line 122) | def from_numpy(ndarray):
  function as_tensor (line 131) | def as_tensor(data, dtype=None, device=None):
  function torch_tensor (line 142) | def torch_tensor(data, *args, dtype=None, device=None, **kwargs):
  function Tensor_to (line 156) | def Tensor_to(self, device=None, *args, **kwargs):
  function Tensor_cuda (line 170) | def Tensor_cuda(self, device=None, *args, **kwargs):
  function Tensor_pin_memory (line 179) | def Tensor_pin_memory(self, device=None, *args, **kwargs):
  function UntypedStorage_init (line 188) | def UntypedStorage_init(*args, device=None, **kwargs):
  function UntypedStorage_to (line 198) | def UntypedStorage_to(self, *args, device=None, **kwargs):
  function UntypedStorage_cuda (line 206) | def UntypedStorage_cuda(self, device=None, non_blocking=False, **kwargs):
  function torch_empty (line 215) | def torch_empty(*args, device=None, **kwargs):
  function torch_randn (line 224) | def torch_randn(*args, device=None, dtype=None, **kwargs):
  function torch_ones (line 233) | def torch_ones(*args, device=None, **kwargs):
  function torch_zeros (line 242) | def torch_zeros(*args, device=None, **kwargs):
  function torch_full (line 251) | def torch_full(*args, device=None, **kwargs):
  function torch_arange (line 260) | def torch_arange(*args, device=None, dtype=None, **kwargs):
  function torch_linspace (line 274) | def torch_linspace(*args, device=None, dtype=None, **kwargs):
  function torch_eye (line 288) | def torch_eye(*args, device=None, **kwargs):
  function torch_load (line 297) | def torch_load(f, map_location=None, *args, **kwargs):
  function torch_cuda_synchronize (line 305) | def torch_cuda_synchronize(device=None):
  function torch_cuda_device (line 313) | def torch_cuda_device(device):
  function torch_cuda_set_device (line 321) | def torch_cuda_set_device(device):
  function get_device_properties (line 329) | def get_device_properties(device=None):
  class DeviceProperties (line 341) | class DeviceProperties():
    method __init__ (line 342) | def __init__(self, device_prop, new_keys):
  class torch_Generator (line 352) | class torch_Generator(original_torch_Generator):
    method __new__ (line 353) | def __new__(self, device=None):
  function ipex_hijacks (line 362) | def ipex_hijacks():

FILE: modules/intel/openvino/__init__.py
  function warn_once (line 77) | def warn_once(msg):
  class OpenVINOGraphModule (line 83) | class OpenVINOGraphModule(torch.nn.Module):
    method __init__ (line 84) | def __init__(self, gm, partition_id, use_python_fusion_cache, model_ha...
    method __call__ (line 93) | def __call__(self, *args):
  function get_device_list (line 104) | def get_device_list():
  function get_device (line 109) | def get_device():
  function get_openvino_device (line 142) | def get_openvino_device():
  function cached_model_name (line 150) | def cached_model_name(model_hash_str, device, args, cache_root, reversed...
  function execute (line 183) | def execute(
  function execute_cached (line 199) | def execute_cached(compiled_model, *args):
  function openvino_compile (line 210) | def openvino_compile(gm: GraphModule, *example_inputs, model_hash_str: s...
  function openvino_compile_cached_model (line 294) | def openvino_compile_cached_model(cached_model_path, *example_inputs):
  function openvino_execute (line 341) | def openvino_execute(gm: GraphModule, *args, executor_parameters=None, p...
  function openvino_execute_partitioned (line 386) | def openvino_execute_partitioned(gm: GraphModule, *args, executor_parame...
  function partition_graph (line 426) | def partition_graph(gm: GraphModule, use_python_fusion_cache: bool, mode...
  function generate_subgraph_str (line 445) | def generate_subgraph_str(tensor):
  function get_subgraph_type (line 451) | def get_subgraph_type(tensor):
  function openvino_fx (line 458) | def openvino_fx(subgraph, example_inputs, options=None):

FILE: modules/interrogate/deepbooru.py
  class DeepDanbooru (line 13) | class DeepDanbooru:
    method __init__ (line 14) | def __init__(self):
    method load (line 17) | def load(self):
    method start (line 36) | def start(self):
    method stop (line 40) | def stop(self):
    method tag (line 45) | def tag(self, pil_image, **kwargs):
    method tag_multi (line 52) | def tag_multi(
  function _save_tags_to_file (line 129) | def _save_tags_to_file(img_path, tags_str: str, save_append: bool) -> bool:
  function get_models (line 154) | def get_models() -> list:
  function load_model (line 159) | def load_model(model_name: str = None) -> bool: # pylint: disable=unused...
  function unload_model (line 169) | def unload_model():
  function tag (line 177) | def tag(image, **kwargs) -> str:
  function batch (line 204) | def batch(

FILE: modules/interrogate/deepbooru_model.py
  class DeepDanbooruModel (line 10) | class DeepDanbooruModel(nn.Module):
    method __init__ (line 11) | def __init__(self):
    method forward (line 195) | def forward(self, *inputs):
    method load_state_dict (line 672) | def load_state_dict(self, state_dict, **kwargs): # pylint: disable=arg...

FILE: modules/interrogate/deepseek.py
  class fake_attrdict (line 24) | class fake_attrdict():
    class AttrDict (line 25) | class AttrDict(dict):  # dot notation access to dictionary attributes
  function load (line 31) | def load(repo: str):
  function unload (line 61) | def unload():
  function predict (line 75) | def predict(question, image, repo):

FILE: modules/interrogate/interrogate.py
  function interrogate (line 6) | def interrogate(image):

FILE: modules/interrogate/joycaption.py
  class JoyOptions (line 43) | class JoyOptions():
    method __str__ (line 51) | def __str__(self):
  function load (line 60) | def load(repo: str = None):
  function unload (line 80) | def unload():
  function predict (line 94) | def predict(question: str, image, vqa_model: str = None) -> str:

FILE: modules/interrogate/joytag.py
  class VisionModel (line 112) | class VisionModel(nn.Module):
    method __init__ (line 116) | def __init__(self, image_size: int, n_tags: int):
    method load_model (line 122) | def load_model(path: str) -> 'VisionModel':
    method from_config (line 134) | def from_config(config: dict) -> 'VisionModel':
    method get_optimized_parameters (line 139) | def get_optimized_parameters(self, lr: float):
    method save (line 142) | def save(self):
    method load (line 145) | def load(self, state_dict):
  function basic_calculate_loss (line 149) | def basic_calculate_loss(preds: dict[str, torch.Tensor], batch: dict, po...
  class CLIPMlp (line 225) | class CLIPMlp(nn.Module):
    method __init__ (line 226) | def __init__(self, hidden_size: int, intermediate_size: int, activatio...
    method forward (line 232) | def forward(self, hidden_states: torch.Tensor):
  class FastCLIPAttention2 (line 239) | class FastCLIPAttention2(nn.Module):
    method __init__ (line 241) | def __init__(self, hidden_size: int, out_dim: int, num_attention_heads...
    method forward (line 257) | def forward(self, query_states: torch.Tensor, kv_states: torch.Tensor)...
  class SkipInit (line 285) | class SkipInit(nn.Module):
    method __init__ (line 286) | def __init__(self, hidden_size: int, channel_wise: bool, init_scale: f...
    method forward (line 296) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class FastCLIPEncoderLayer (line 300) | class FastCLIPEncoderLayer(nn.Module):
    method __init__ (line 301) | def __init__(
    method forward (line 333) | def forward(self, hidden_states: torch.Tensor):
  function sinusoidal_position_embedding (line 360) | def sinusoidal_position_embedding(width: int, height: int, depth: int, d...
  class CLIPEmbeddingLayer (line 374) | class CLIPEmbeddingLayer(nn.Module):
    method __init__ (line 375) | def __init__(self, hidden_size: int, num_channels: int, image_size: in...
    method forward (line 411) | def forward(self, pixel_values: torch.FloatTensor) -> torch.Tensor:
  class MHAPoolingHead (line 450) | class MHAPoolingHead(nn.Module):
    method __init__ (line 451) | def __init__(self, hidden_size: int, num_attention_heads: int, activat...
    method forward (line 473) | def forward(self, hidden_states: torch.Tensor):
  class GAPHead (line 486) | class GAPHead(nn.Module):
    method __init__ (line 487) | def __init__(self, hidden_size: int, out_dim: int):
    method forward (line 492) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class CLIPLikeModel (line 499) | class CLIPLikeModel(VisionModel):
    method __init__ (line 500) | def __init__(
    method forward (line 546) | def forward(self, batch):
    method calculate_loss (line 555) | def calculate_loss(self, preds, batch, pos_weight):
    method get_optimized_parameters (line 558) | def get_optimized_parameters(self, lr: float):
    method get_optimized_parameters_no_wd_bias (line 564) | def get_optimized_parameters_no_wd_bias(self):
    method save (line 581) | def save(self):
    method load (line 584) | def load(self, state_dict):
  class MaskedAutoEncoderViT (line 588) | class MaskedAutoEncoderViT(nn.Module):
    method __init__ (line 589) | def __init__(
    method forward (line 667) | def forward(self, batch):
    method calculate_loss (line 742) | def calculate_loss(self, preds, batch, pos_weight):
    method get_optimized_parameters (line 745) | def get_optimized_parameters(self, _lr: float):
    method save (line 748) | def save(self):
    method load (line 751) | def load(self, state_dict):
  class StochDepth (line 755) | class StochDepth(nn.Module):
    method __init__ (line 756) | def __init__(self, drop_rate: float, scale_by_keep: bool = False):
    method forward (line 761) | def forward(self, x):
  class SkipInitChannelwise (line 773) | class SkipInitChannelwise(nn.Module):
    method __init__ (line 774) | def __init__(self, channels, init_val=1e-6):
    method forward (line 780) | def forward(self, x):
  class PosEmbedding (line 784) | class PosEmbedding(nn.Module):
    method __init__ (line 785) | def __init__(self, d_model: int, max_len: int, use_sine: bool, patch_s...
    method forward (line 796) | def forward(self, x, width: int, height: int):
  class MLPBlock (line 804) | class MLPBlock(nn.Module):
    method __init__ (line 805) | def __init__(self, d_model: int, d_ff: int, stochdepth_rate: float):
    method forward (line 815) | def forward(self, x):
  class ViTBlock (line 824) | class ViTBlock(nn.Module):
    method __init__ (line 825) | def __init__(self, num_heads: int, d_model: int, d_ff: int, layerscale...
    method forward (line 842) | def forward(self, x):
  function CaiT_LayerScale_init (line 868) | def CaiT_LayerScale_init(network_depth):
  class CNNLayerNorm (line 877) | class CNNLayerNorm(nn.Module):
    method __init__ (line 878) | def __init__(self, d_model: int):
    method forward (line 882) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class CNNStem (line 889) | class CNNStem(nn.Module):
    method __init__ (line 890) | def __init__(self, config: str):
    method forward (line 920) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class ViT (line 924) | class ViT(VisionModel):
    method __init__ (line 925) | def __init__(self,
    method forward (line 966) | def forward(self, batch, return_embeddings=False, return_loss: bool = ...
    method calculate_loss (line 1005) | def calculate_loss(self, preds, batch, pos_weight):
    method get_optimized_parameters (line 1008) | def get_optimized_parameters(self, lr: float):
    method save (line 1011) | def save(self):
    method load (line 1014) | def load(self, state_dict):
  function prepare_image (line 1022) | def prepare_image(image: Image.Image, target_size: int) -> torch.Tensor:
  function load (line 1037) | def load():
  function unload (line 1051) | def unload():
  function predict (line 1064) | def predict(image: Image.Image):

FILE: modules/interrogate/moondream3.py
  function debug (line 16) | def debug(*args, **kwargs):
  function get_settings (line 27) | def get_settings():
  function load_model (line 42) | def load_model(repo: str):
  function encode_image (line 75) | def encode_image(image: Image.Image, cache_key: str = None):
  function query (line 102) | def query(image: Image.Image, question: str, repo: str, stream: bool = F...
  function caption (line 163) | def caption(image: Image.Image, repo: str, length: str = 'normal', strea...
  function point (line 208) | def point(image: Image.Image, object_name: str, repo: str):
  function detect (line 241) | def detect(image: Image.Image, object_name: str, repo: str, max_objects:...
  function predict (line 274) | def predict(question: str, image: Image.Image, repo: str, model_name: st...
  function clear_cache (line 389) | def clear_cache():
  function unload (line 397) | def unload():

FILE: modules/interrogate/openclip.py
  function _apply_blip2_fix (line 15) | def _apply_blip2_fix(model, processor):
  class BatchWriter (line 52) | class BatchWriter:
    method __init__ (line 53) | def __init__(self, folder, mode='w'):
    method add (line 59) | def add(self, file, prompt):
    method close (line 66) | def close(self):
  function update_interrogate_params (line 71) | def update_interrogate_params():
  function get_clip_models (line 80) | def get_clip_models():
  function refresh_clip_models (line 84) | def refresh_clip_models():
  function load_interrogator (line 93) | def load_interrogator(clip_model, blip_model):
  function unload_clip_model (line 142) | def unload_clip_model():
  function interrogate (line 153) | def interrogate(image, mode, caption=None):
  function interrogate_image (line 179) | def interrogate_image(image, clip_model, blip_model, mode):
  function interrogate_batch (line 201) | def interrogate_batch(batch_files, batch_folder, batch_str, clip_model, ...
  function analyze_image (line 250) | def analyze_image(image, clip_model, blip_model):

FILE: modules/interrogate/tagger.py
  function get_models (line 9) | def get_models() -> list:
  function refresh_models (line 15) | def refresh_models() -> list:
  function is_deepbooru (line 20) | def is_deepbooru(model_name: str) -> bool:
  function load_model (line 25) | def load_model(model_name: str) -> bool:
  function unload_model (line 35) | def unload_model():
  function tag (line 42) | def tag(image, model_name: str = None, **kwargs) -> str:
  function batch (line 64) | def batch(model_name: str, **kwargs) -> str:

FILE: modules/interrogate/vqa.py
  function debug (line 18) | def debug(*args, **kwargs):
  function get_prompts_for_model (line 156) | def get_prompts_for_model(model_name: str) -> list:
  function get_internal_prompt (line 178) | def get_internal_prompt(friendly_name: str, user_prompt: str = None) -> ...
  function get_prompt_placeholder (line 191) | def get_prompt_placeholder(friendly_name: str) -> str:
  function is_florence_task (line 196) | def is_florence_task(question: str) -> bool:
  function is_thinking_model (line 210) | def is_thinking_model(model_name: str) -> bool:
  function truncate_b64_in_conversation (line 227) | def truncate_b64_in_conversation(conversation, front_chars=50, tail_char...
  function keep_think_block_open (line 251) | def keep_think_block_open(text_prompt: str) -> str:
  function b64 (line 272) | def b64(image):
  function clean (line 282) | def clean(response, question, prefill=None):
  function get_kwargs (line 339) | def get_kwargs():
  class VQA (line 355) | class VQA:
    method __init__ (line 358) | def __init__(self):
    method unload (line 365) | def unload(self):
    method load (line 379) | def load(self, model_name: str = None):
    method _load_fastvlm (line 447) | def _load_fastvlm(self, repo: str):
    method _fastvlm (line 464) | def _fastvlm(self, question: str, image: Image.Image, repo: str, model...
    method _load_qwen (line 493) | def _load_qwen(self, repo: str):
    method _qwen (line 519) | def _qwen(self, question: str, image: Image.Image, repo: str, system_p...
    method _load_gemma (line 631) | def _load_gemma(self, repo: str):
    method _gemma (line 653) | def _gemma(self, question: str, image: Image.Image, repo: str, system_...
    method _load_paligemma (line 757) | def _load_paligemma(self, repo: str):
    method _paligemma (line 771) | def _paligemma(self, question: str, image: Image.Image, repo: str, mod...
    method _load_ovis (line 786) | def _load_ovis(self, repo: str):
    method _ovis (line 801) | def _ovis(self, question: str, image: Image.Image, repo: str, model_na...
    method _load_smol (line 834) | def _load_smol(self, repo: str):
    method _smol (line 852) | def _smol(self, question: str, image: Image.Image, repo: str, system_p...
    method _load_git (line 940) | def _load_git(self, repo: str):
    method _git (line 954) | def _git(self, question: str, image: Image.Image, repo: str, model_nam...
    method _load_blip (line 970) | def _load_blip(self, repo: str):
    method _blip (line 984) | def _blip(self, question: str, image: Image.Image, repo: str, model_na...
    method _load_vilt (line 994) | def _load_vilt(self, repo: str):
    method _vilt (line 1008) | def _vilt(self, question: str, image: Image.Image, repo: str, model_na...
    method _load_pix (line 1020) | def _load_pix(self, repo: str):
    method _pix (line 1034) | def _pix(self, question: str, image: Image.Image, repo: str, model_nam...
    method _load_moondream (line 1046) | def _load_moondream(self, repo: str):
    method _moondream (line 1063) | def _moondream(self, question: str, image: Image.Image, repo: str, mod...
    method _load_florence (line 1125) | def _load_florence(self, repo: str, revision: str = None):
    method _florence (line 1163) | def _florence(self, question: str, image: Image.Image, repo: str, revi...
    method _load_sa2 (line 1183) | def _load_sa2(self, repo: str):
    method _sa2 (line 1202) | def _sa2(self, question: str, image: Image.Image, repo: str, model_nam...
    method interrogate (line 1220) | def interrogate(self, question: str = '', system_prompt: str = None, p...
    method batch (line 1364) | def batch(self, model_name, system_prompt, batch_files, batch_folder, ...
  function get_instance (line 1432) | def get_instance() -> VQA:
  function interrogate (line 1441) | def interrogate(*args, **kwargs):
  function unload_model (line 1445) | def unload_model():
  function load_model (line 1449) | def load_model(model_name: str = None):
  function get_last_annotated_image (line 1453) | def get_last_annotated_image():
  function batch (line 1457) | def batch(*args, **kwargs):

FILE: modules/interrogate/vqa_detection.py
  function parse_points (line 8) | def parse_points(result) -> list:
  function parse_detections (line 41) | def parse_detections(result, label: str, max_objects: int = None) -> list:
  function format_points_text (line 77) | def format_points_text(points: list) -> str:
  function format_detections_text (line 98) | def format_detections_text(detections: list, include_confidence: bool = ...
  function calculate_eye_position (line 125) | def calculate_eye_position(face_bbox: dict) -> tuple:
  function draw_bounding_boxes (line 139) | def draw_bounding_boxes(image: Image.Image, detections: list, points: li...

FILE: modules/interrogate/waifudiffusion.py
  class WaifuDiffusionTagger (line 41) | class WaifuDiffusionTagger:
    method __init__ (line 44) | def __init__(self):
    method load (line 52) | def load(self, model_name: str = None):
    method _load_tags (line 117) | def _load_tags(self):
    method unload (line 141) | def unload(self):
    method preprocess_image (line 155) | def preprocess_image(self, image: Image.Image) -> np.ndarray:
    method predict (line 195) | def predict(
    method tag (line 331) | def tag(self, image: Image.Image, **kwargs) -> str:
  function _save_tags_to_file (line 340) | def _save_tags_to_file(img_path, tags_str: str, save_append: bool) -> bool:
  function get_models (line 365) | def get_models() -> list:
  function refresh_models (line 370) | def refresh_models() -> list:
  function load_model (line 377) | def load_model(model_name: str = None) -> bool:
  function unload_model (line 382) | def unload_model():
  function tag (line 387) | def tag(image: Image.Image, model_name: str = None, **kwargs) -> str:
  function batch (line 419) | def batch(

FILE: modules/ipadapter.py
  function get_adapters (line 60) | def get_adapters():
  function get_images (line 75) | def get_images(input_images):
  function get_scales (line 109) | def get_scales(adapter_scales, adapter_images):
  function get_crops (line 116) | def get_crops(adapter_crops, adapter_images):
  function crop_images (line 123) | def crop_images(images, crops):
  function unapply (line 144) | def unapply(pipe, unload: bool = False): # pylint: disable=arguments-differ
  function load_image_encoder (line 167) | def load_image_encoder(pipe: DiffusionPipeline, adapter_names: list[str]):
  function load_feature_extractor (line 223) | def load_feature_extractor(pipe):
  function parse_params (line 247) | def parse_params(p: processing.StableDiffusionProcessing, adapters: list...
  function apply (line 291) | def apply(pipe, p: processing.StableDiffusionProcessing, adapter_names=[...

FILE: modules/json_helpers.py
  function readfile (line 15) | def readfile(filename: str, silent: bool = False, lock: bool = False, *,...
  function readfile (line 17) | def readfile(filename: str, silent: bool = False, lock: bool = False, *,...
  function readfile (line 19) | def readfile(filename: str, silent: bool = False, lock: bool = False) ->...
  function readfile (line 20) | def readfile(filename: str, silent: bool = False, lock: bool = False, *,...
  function writefile (line 77) | def writefile(data, filename, mode='w', silent=False, atomic=False):

FILE: modules/lama.py
  function prepare_img_and_mask (line 15) | def prepare_img_and_mask(image, mask, device, pad_out_to_modulo=8, scale...
  function download_model (line 67) | def download_model():
  class SimpleLama (line 81) | class SimpleLama:
    method __init__ (line 82) | def __init__(self):
    method __call__ (line 89) | def __call__(self, image: Image.Image, mask: Image.Image):

FILE: modules/linfusion/__init__.py
  function detect (line 9) | def detect(pipeline):
  function apply (line 17) | def apply(pipeline, pretrained: bool = True):
  function unapply (line 39) | def unapply(pipeline):

FILE: modules/linfusion/attention.py
  function get_none_linear_projection (line 6) | def get_none_linear_projection(query_dim, mid_dim=None):
  class GeneralizedLinearAttention (line 21) | class GeneralizedLinearAttention(Attention):
    method __init__ (line 22) | def __init__(self, *args, projection_mid_dim=None, **kwargs):
    method from_attention_instance (line 35) | def from_attention_instance(self, attention_instance, projection_mid_d...
    method add_non_linear_model (line 42) | def add_non_linear_model(self, mid_dim=None, **kwargs):
    method forward (line 47) | def forward( # pylint: disable=unused-argument

FILE: modules/linfusion/linfusion.py
  function replace_submodule (line 16) | def replace_submodule(model, module_name, new_submodule):
  class LinFusion (line 22) | class LinFusion(ModelMixin, ConfigMixin):
    method __init__ (line 23) | def __init__(self, modules_list, *args, **kwargs) -> None:
    method get_default_config (line 43) | def get_default_config(
    method construct_for (line 73) | def construct_for(
    method mount_to (line 109) | def mount_to(self, pipeline=None, unet=None) -> None:

FILE: modules/loader.py
  function obj2sctype (line 23) | def obj2sctype(obj):
  function dummy_npwarn_decorator_factory (line 29) | def dummy_npwarn_decorator_factory():
  class _tqdm_cls (line 172) | class _tqdm_cls():
    method __call__ (line 173) | def __call__(self, *args, **kwargs):
  class _tqdm_old (line 177) | class _tqdm_old(tqdm_lib.tqdm):
    method __init__ (line 178) | def __init__(self, *args, **kwargs):
  function get_packages (line 190) | def get_packages():
  function deprecate_warn (line 223) | def deprecate_warn(*args, **kwargs):
  class VersionString (line 232) | class VersionString(str): # support both string and tuple for version check
    method __ge__ (line 233) | def __ge__(self, version):

FILE: modules/localization.py
  function list_localizations (line 8) | def list_localizations(dirname): # pylint: disable=unused-argument
  function localization_js (line 26) | def localization_js(current_localization_name):

FILE: modules/lora/extra_networks_lora.py
  function get_stepwise (line 14) | def get_stepwise(param, step, steps): # from https://github.com/cheald/s...
  function prompt (line 39) | def prompt(p):
  function infotext (line 72) | def infotext(p):
  function to_float (line 86) | def to_float(value):
  function parse (line 93) | def parse(p, params_list, step=0):
  function unload_diffusers (line 152) | def unload_diffusers():
  class ExtraNetworkLora (line 165) | class ExtraNetworkLora(extra_networks.ExtraNetwork):
    method __init__ (line 167) | def __init__(self):
    method signature (line 173) | def signature(self, names: List[str], te_multipliers: List, unet_multi...
    method changed (line 176) | def changed(self, requested: List[str], include: List[str] = None, exc...
    method activate (line 201) | def activate(self, p, params_list, step=0, include=[], exclude=[]):
    method deactivate (line 250) | def deactivate(self, p, force=False):

FILE: modules/lora/lora_apply.py
  function network_backup_weights (line 15) | def network_backup_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear,...
  function network_calc_weights (line 79) | def network_calc_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, t...
  function network_add_weights (line 150) | def network_add_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, to...
  function network_apply_direct (line 242) | def network_apply_direct(self: Union[torch.nn.Conv2d, torch.nn.Linear, t...
  function network_apply_weights (line 269) | def network_apply_weights(self: Union[torch.nn.Conv2d, torch.nn.Linear, ...

FILE: modules/lora/lora_convert.py
  function make_unet_conversion_map (line 26) | def make_unet_conversion_map() -> Dict[str, str]:
  class KeyConvert (line 108) | class KeyConvert:
    method __init__ (line 109) | def __init__(self):
    method __call__ (line 119) | def __call__(self, key):
  function _convert_to_ai_toolkit (line 145) | def _convert_to_ai_toolkit(sds_sd, ait_sd, sds_key, ait_key):
  function _convert_to_ai_toolkit_cat (line 165) | def _convert_to_ai_toolkit_cat(sds_sd, ait_sd, sds_key, ait_keys, dims=N...
  function _convert_text_encoder_lora_key (line 227) | def _convert_text_encoder_lora_key(key, lora_name):
  function _convert_kohya_flux_lora_to_diffusers (line 253) | def _convert_kohya_flux_lora_to_diffusers(state_dict):
  function _convert_kohya_sd3_lora_to_diffusers (line 359) | def _convert_kohya_sd3_lora_to_diffusers(state_dict):
  function assign_network_names_to_compvis_modules (line 478) | def assign_network_names_to_compvis_modules(sd_model):

FILE: modules/lora/lora_diffusers.py
  function load_per_module (line 14) | def load_per_module(sd_model: diffusers.DiffusionPipeline, filename: str...
  function load_diffusers (line 53) | def load_diffusers(name: str, network_on_disk: network.NetworkOnDisk, lo...

FILE: modules/lora/lora_extract.py
  class SVDHandler (line 14) | class SVDHandler:
    method __init__ (line 15) | def __init__(self, maxrank=0, rank_ratio=1):
    method decompose (line 28) | def decompose(self, weight, backupweight):
    method findrank (line 45) | def findrank(self):
    method makeweights (line 58) | def makeweights(self):
  function loaded_lora (line 72) | def loaded_lora():
  function loaded_lora_str (line 85) | def loaded_lora_str():
  function make_meta (line 89) | def make_meta(fn, maxrank, rank_ratio):
  function make_lora (line 118) | def make_lora(fn, maxrank, auto_rank, rank_ratio, modules, overwrite):
  function create_ui (line 247) | def create_ui():

FILE: modules/lora/lora_load.py
  function lora_dump (line 21) | def lora_dump(lora, dct):
  function load_safetensors (line 42) | def load_safetensors(name, network_on_disk: network.NetworkOnDisk) -> Un...
  function maybe_recompile_model (line 139) | def maybe_recompile_model(names, te_multipliers):
  function list_available_networks (line 174) | def list_available_networks():
  function network_download (line 209) | def network_download(name):
  function gather_networks (line 222) | def gather_networks(names):
  function network_load (line 233) | def network_load(names, te_multipliers=None, unet_multipliers=None, dyn_...

FILE: modules/lora/lora_nunchaku.py
  function load_nunchaku (line 9) | def load_nunchaku(names, strengths):

FILE: modules/lora/lora_overrides.py
  function get_method (line 42) | def get_method(shorthash=''):
  function disable_fuse (line 57) | def disable_fuse():

FILE: modules/lora/lora_timers.py
  class Timer (line 1) | class Timer():
    method total (line 13) | def total(self):
    method summary (line 17) | def summary(self):
    method clear (line 24) | def clear(self, complete: bool = False):
    method add (line 34) | def add(self, name, t):
    method __str__ (line 37) | def __str__(self):

FILE: modules/lora/lyco_helpers.py
  function make_weight_cp (line 4) | def make_weight_cp(t, wa, wb):
  function rebuild_conventional (line 9) | def rebuild_conventional(up, down, shape, dyn_dim=None):
  function rebuild_cp_decomposition (line 18) | def rebuild_cp_decomposition(up, down, mid):
  function factorization (line 25) | def factorization(dimension: int, factor:int=-1) -> tuple[int, int]:

FILE: modules/lora/network.py
  class SdVersion (line 12) | class SdVersion(enum.Enum):
  class NetworkOnDisk (line 24) | class NetworkOnDisk:
    method __init__ (line 25) | def __init__(self, name, filename):
    method __str__ (line 48) | def __str__(self):
    method detect_version (line 51) | def detect_version(self):
    method set_hash (line 99) | def set_hash(self, v):
    method read_hash (line 103) | def read_hash(self):
    method get_info (line 107) | def get_info(self):
    method get_desc (line 117) | def get_desc(self):
    method get_alias (line 127) | def get_alias(self):
  class Network (line 131) | class Network:  # LoraModule
    method __init__ (line 132) | def __init__(self, name, network_on_disk: NetworkOnDisk):
  class ModuleType (line 146) | class ModuleType:
    method create_module (line 147) | def create_module(self, net: Network, weights: NetworkWeights) -> Unio...
  class NetworkModule (line 151) | class NetworkModule:
    method __init__ (line 152) | def __init__(self, net: Network, weights: NetworkWeights):
    method multiplier (line 169) | def multiplier(self):
    method calc_scale (line 182) | def calc_scale(self):
    method apply_weight_decompose (line 189) | def apply_weight_decompose(self, updown, orig_weight):
    method finalize_updown (line 210) | def finalize_updown(self, updown, orig_weight, output_shape, ex_bias=N...
    method calc_updown (line 225) | def calc_updown(self, target):
    method forward (line 228) | def forward(self, x, y):

FILE: modules/lora/network_full.py
  class ModuleTypeFull (line 4) | class ModuleTypeFull(network.ModuleType):
    method create_module (line 5) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleFull (line 11) | class NetworkModuleFull(network.NetworkModule): # pylint: disable=abstra...
    method __init__ (line 12) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 18) | def calc_updown(self, target):

FILE: modules/lora/network_glora.py
  class ModuleTypeGLora (line 4) | class ModuleTypeGLora(network.ModuleType):
    method create_module (line 5) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleGLora (line 11) | class NetworkModuleGLora(network.NetworkModule): # pylint: disable=abstr...
    method __init__ (line 12) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 23) | def calc_updown(self, target): # pylint: disable=arguments-differ

FILE: modules/lora/network_hada.py
  class ModuleTypeHada (line 5) | class ModuleTypeHada(network.ModuleType):
    method create_module (line 6) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleHada (line 12) | class NetworkModuleHada(network.NetworkModule): # pylint: disable=abstra...
    method __init__ (line 13) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 25) | def calc_updown(self, target):

FILE: modules/lora/network_ia3.py
  class ModuleTypeIa3 (line 3) | class ModuleTypeIa3(network.ModuleType):
    method create_module (line 4) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleIa3 (line 10) | class NetworkModuleIa3(network.NetworkModule): # pylint: disable=abstrac...
    method __init__ (line 11) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 16) | def calc_updown(self, target):

FILE: modules/lora/network_lokr.py
  class ModuleTypeLokr (line 6) | class ModuleTypeLokr(network.ModuleType):
    method create_module (line 7) | def create_module(self, net: network.Network, weights: network.Network...
  function make_kron (line 15) | def make_kron(orig_shape, w1, w2):
  class NetworkModuleLokr (line 22) | class NetworkModuleLokr(network.NetworkModule): # pylint: disable=abstra...
    method __init__ (line 23) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 35) | def calc_updown(self, target):

FILE: modules/lora/network_lora.py
  class ModuleTypeLora (line 8) | class ModuleTypeLora(network.ModuleType):
    method create_module (line 9) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleLora (line 15) | class NetworkModuleLora(network.NetworkModule):
    method __init__ (line 17) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method create_module (line 24) | def create_module(self, weights, key, none_ok=False):
    method calc_updown (line 55) | def calc_updown(self, target): # pylint: disable=W0237
    method forward (line 72) | def forward(self, x, y):

FILE: modules/lora/network_norm.py
  class ModuleTypeNorm (line 4) | class ModuleTypeNorm(network.ModuleType):
    method create_module (line 5) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleNorm (line 11) | class NetworkModuleNorm(network.NetworkModule): # pylint: disable=abstra...
    method __init__ (line 12) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 17) | def calc_updown(self, target):

FILE: modules/lora/network_oft.py
  class ModuleTypeOFT (line 7) | class ModuleTypeOFT(network.ModuleType):
    method create_module (line 8) | def create_module(self, net: network.Network, weights: network.Network...
  class NetworkModuleOFT (line 16) | class NetworkModuleOFT(network.NetworkModule): # pylint: disable=abstrac...
    method __init__ (line 17) | def __init__(self,  net: network.Network, weights: network.NetworkWeig...
    method calc_updown (line 55) | def calc_updown(self, target):

FILE: modules/lora/networks.py
  function network_activate (line 14) | def network_activate(include=[], exclude=[]):
  function network_deactivate (line 80) | def network_deactivate(include=[], exclude=[]):

FILE: modules/ltx/ltx_process.py
  function run_ltx (line 20) | def run_ltx(task_id,

FILE: modules/ltx/ltx_ui.py
  function create_ui (line 11) | def create_ui(prompt, negative, styles, overrides, init_image, init_stre...

FILE: modules/ltx/ltx_util.py
  function get_bucket (line 10) | def get_bucket(size: int):
  function get_frames (line 16) | def get_frames(frames: int):
  function load_model (line 20) | def load_model(engine: str, model: str):
  function load_upsample (line 41) | def load_upsample(upsample_pipe, upsample_repo_id):
  function get_conditions (line 57) | def get_conditions(width, height, condition_strength, condition_images, ...
  function get_prompts (line 98) | def get_prompts(prompt, negative, styles):
  function get_generator (line 106) | def get_generator(seed):
  function vae_decode (line 114) | def vae_decode(latents, decode_timestep, seed):

FILE: modules/masking.py
  function get_crop_region (line 19) | def get_crop_region(mask, pad=0):
  function expand_crop_region (line 61) | def expand_crop_region(crop_region, processing_width, processing_height,...
  function fill (line 106) | def fill(image, mask):
  function init_model (line 176) | def init_model(selected_model: str):
  function run_segment (line 211) | def run_segment(input_image: gr.Image, input_mask: np.ndarray):
  function run_rembg (line 260) | def run_rembg(input_image: Image, input_mask: np.ndarray):
  function get_mask (line 308) | def get_mask(input_image: gr.Image, input_mask: gr.Image):
  function outpaint (line 355) | def outpaint(input_image: Image.Image, outpaint_type: str = 'Edge'):
  function run_mask (line 381) | def run_mask(input_image: Image.Image, input_mask: Image.Image = None, r...
  function run_lama (line 484) | def run_lama(input_image: gr.Image, input_mask: gr.Image = None):
  function run_mask_live (line 505) | def run_mask_live(input_image: gr.Image):
  function create_segment_ui (line 516) | def create_segment_ui():
  function bind_controls (line 564) | def bind_controls(image_controls: List[gr.Image], preview_image: gr.Imag...
  function process_kanvas (line 573) | def process_kanvas(kanvas_data):
  function process_kanvas_lama (line 583) | def process_kanvas_lama(kanvas_data):
  function bind_kanvas (line 593) | def bind_kanvas(input_image: Image.Image, output_image: gr.Image):

FILE: modules/memmon.py
  class MemUsageMonitor (line 5) | class MemUsageMonitor():
    method __init__ (line 11) | def __init__(self, name, device):
    method cuda_mem_get_info (line 24) | def cuda_mem_get_info(self): # legacy for extensions only
    method reset (line 29) | def reset(self):
    method read (line 41) | def read(self):
    method summary (line 57) | def summary(self):

FILE: modules/memstats.py
  function gb (line 18) | def gb(val: float):
  function get_docker_limit (line 22) | def get_docker_limit():
  function get_runpod_limit (line 36) | def get_runpod_limit():
  function ram_stats (line 46) | def ram_stats():
  function gpu_stats (line 87) | def gpu_stats():
  function memory_stats (line 111) | def memory_stats():
  function reset_stats (line 122) | def reset_stats():
  class Object (line 129) | class Object:
    method __init__ (line 132) | def __init__(self, name, obj):
    method __str__ (line 144) | def __str__(self):
  function get_objects (line 148) | def get_objects(gcl={}, threshold:int=0):

FILE: modules/merging/convert_sdxl.py
  function convert_unet_state_dict (line 88) | def convert_unet_state_dict(unet_state_dict):
  function reshape_weight_for_sd (line 156) | def reshape_weight_for_sd(w):
  function convert_vae_state_dict (line 164) | def convert_vae_state_dict(vae_state_dict):
  function convert_openclip_text_enc_state_dict (line 203) | def convert_openclip_text_enc_state_dict(text_enc_dict):
  function convert_openai_text_enc_state_dict (line 250) | def convert_openai_text_enc_state_dict(text_enc_dict):
  function calculate_model_hash (line 254) | def calculate_model_hash(state_dict):
  function convert (line 263) | def convert(model_path:str, checkpoint_path:str, metadata:dict={}):

FILE: modules/merging/merge.py
  function fix_clip (line 41) | def fix_clip(model: Dict) -> Dict:
  function prune_sd_model (line 52) | def prune_sd_model(model: Dict, keyset: Set) -> Dict:
  function restore_sd_model (line 64) | def restore_sd_model(original_model: Dict, merged_model: Dict) -> Dict:
  function log_vram (line 71) | def log_vram(txt=""):
  function load_thetas (line 75) | def load_thetas(
  function merge_models (line 97) | def merge_models(
  function un_prune_model (line 138) | def un_prune_model(
  function simple_merge (line 181) | def simple_merge(
  function rebasin_merge (line 228) | def rebasin_merge(
  function simple_merge_key (line 299) | def simple_merge_key(progress, task, key, thetas, *args, **kwargs):
  function merge_key (line 306) | def merge_key(  # pylint: disable=inconsistent-return-statements
  function clip_weights (line 352) | def clip_weights(thetas, merged):
  function clip_weights_key (line 359) | def clip_weights_key(thetas, merged_weights, key):
  function merge_key_context (line 368) | def merge_key_context(*args, **kwargs):
  function get_merge_method_args (line 377) | def get_merge_method_args(
  function save_model (line 395) | def save_model(model, output_file, file_format) -> None:

FILE: modules/merging/merge_PermSpec.py
  function sdunet_permutation_spec (line 2) | def sdunet_permutation_spec() -> PermutationSpec:

FILE: modules/merging/merge_PermSpec_SDXL.py
  function sdxl_permutation_spec (line 3) | def sdxl_permutation_spec() -> PermutationSpec:

FILE: modules/merging/merge_methods.py
  function weighted_sum (line 26) | def weighted_sum(a: Tensor, b: Tensor, alpha: float, **kwargs) -> Tensor...
  function weighted_subtraction (line 35) | def weighted_subtraction(a: Tensor, b: Tensor, alpha: float, beta: float...
  function tensor_sum (line 48) | def tensor_sum(a: Tensor, b: Tensor, alpha: float, beta: float, **kwargs...
  function add_difference (line 68) | def add_difference(a: Tensor, b: Tensor, c: Tensor, alpha: float, **kwar...
  function sum_twice (line 75) | def sum_twice(a: Tensor, b: Tensor, c: Tensor, alpha: float, beta: float...
  function triple_sum (line 84) | def triple_sum(a: Tensor, b: Tensor, c: Tensor, alpha: float, beta: floa...
  function euclidean_add_difference (line 93) | def euclidean_add_difference(a: Tensor, b: Tensor, c: Tensor, alpha: flo...
  function multiply_difference (line 114) | def multiply_difference(a: Tensor, b: Tensor, c: Tensor, alpha: float, b...
  function top_k_tensor_sum (line 124) | def top_k_tensor_sum(a: Tensor, b: Tensor, alpha: float, beta: float, **...
  function kth_abs_value (line 147) | def kth_abs_value(a: Tensor, k: int) -> Tensor:
  function ratio_to_region (line 154) | def ratio_to_region(width: float, offset: float, n: int) -> Tuple[int, i...
  function similarity_add_difference (line 176) | def similarity_add_difference(a: Tensor, b: Tensor, c: Tensor, alpha: fl...
  function distribution_crossover (line 189) | def distribution_crossover(a: Tensor, b: Tensor, c: Tensor, alpha: float...
  function ties_add_difference (line 221) | def ties_add_difference(a: Tensor, b: Tensor, c: Tensor, alpha: float, b...
  function filter_top_k (line 243) | def filter_top_k(a: Tensor, k: float):

FILE: modules/merging/merge_rebasin.py
  class PermutationSpec (line 20) | class PermutationSpec(NamedTuple):
  function permutation_spec_from_axes_to_perm (line 25) | def permutation_spec_from_axes_to_perm(axes_to_perm: dict) -> Permutatio...
  function get_permuted_param (line 34) | def get_permuted_param(ps: PermutationSpec, perm, k: str, params, except...
  function apply_permutation (line 49) | def apply_permutation(ps: PermutationSpec, perm, params):
  function update_model_a (line 54) | def update_model_a(ps: PermutationSpec, perm, model_a, new_alpha):
  function inner_matching (line 66) | def inner_matching(
  function weight_matching (line 126) | def weight_matching(

FILE: modules/merging/merge_utils.py
  function interpolate (line 23) | def interpolate(values, interp_lambda):
  class WeightClass (line 30) | class WeightClass:
    method __init__ (line 31) | def __init__(self,
    method __call__ (line 64) | def __call__(self, key, it=0):
    method step_weights_and_bases (line 98) | def step_weights_and_bases(self, ratio):
    method set_it (line 110) | def set_it(self, it):

FILE: modules/merging/modules_sdxl.py
  class Recipe (line 14) | class Recipe:
    method __repr__ (line 37) | def __repr__(self):
  class Test (line 41) | class Test:
  function msg (line 57) | def msg(text, err:bool=False):
  function load_base (line 67) | def load_base(override:str=None):
  function load_unet (line 81) | def load_unet(pipe: diffusers.StableDiffusionXLPipeline, override:str=No...
  function load_scheduler (line 101) | def load_scheduler(pipe: diffusers.StableDiffusionXLPipeline, override:s...
  function load_vae (line 116) | def load_vae(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
  function load_te1 (line 137) | def load_te1(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
  function load_te2 (line 158) | def load_te2(pipe: diffusers.StableDiffusionXLPipeline, override:str=None):
  function load_lora (line 179) | def load_lora(pipe: diffusers.StableDiffusionXLPipeline, override: dict=...
  function test_model (line 205) | def test_model(pipe: diffusers.StableDiffusionXLPipeline, fn: str, **kwa...
  function get_thumbnail (line 228) | def get_thumbnail():
  function get_metadata (line 240) | def get_metadata():
  function save_model (line 268) | def save_model(pipe: diffusers.StableDiffusionXLPipeline):
  function merge (line 309) | def merge():

FILE: modules/migrate.py
  function migrate_data (line 21) | def migrate_data():

FILE: modules/mit_nunchaku.py
  function check (line 11) | def check():
  function install_nunchaku (line 31) | def install_nunchaku():

FILE: modules/model_quant.py
  function get_quant_type (line 21) | def get_quant_type(args):
  function get_quant (line 27) | def get_quant(name):
  function dont_quant (line 43) | def dont_quant():
  function create_bnb_config (line 53) | def create_bnb_config(kwargs = None, allow: bool = True, module: str = '...
  function create_ao_config (line 76) | def create_ao_config(kwargs = None, allow: bool = True, module: str = 'M...
  function create_quanto_config (line 95) | def create_quanto_config(kwargs = None, allow: bool = True, module: str ...
  function create_trt_config (line 117) | def create_trt_config(kwargs = None, allow: bool = True, module: str = '...
  function get_sdnq_devices (line 145) | def get_sdnq_devices(mode="pre"):
  function create_sdnq_config (line 165) | def create_sdnq_config(kwargs = None, allow: bool = True, module: str = ...
  function check_quant (line 249) | def check_quant(module: str = ''):
  function check_nunchaku (line 256) | def check_nunchaku(module: str = ''):
  function create_config (line 267) | def create_config(kwargs = None, allow: bool = True, module: str = 'Mode...
  function load_torchao (line 300) | def load_torchao(msg='', silent=False):
  function load_bnb (line 325) | def load_bnb(msg='', silent=False):
  function load_quanto (line 353) | def load_quanto(msg='', silent=False):
  function load_trt (line 382) | def load_trt(msg='', silent=False):
  function upcast_non_layerwise_modules (line 406) | def upcast_non_layerwise_modules(model, dtype): # pylint: disable=unused...
  function load_fp8_model_layerwise (line 423) | def load_fp8_model_layerwise(checkpoint_info, load_model_func, diffusers...
  function apply_layerwise (line 453) | def apply_layerwise(sd_model, quiet:bool=False):
  function sdnq_quantize_model (line 499) | def sdnq_quantize_model(model, op=None, sd_model=None, do_gc: bool = Tru...
  function sdnq_quantize_weights (line 606) | def sdnq_quantize_weights(sd_model):
  function optimum_quanto_model (line 633) | def optimum_quanto_model(model, op=None, sd_model=None, weights=None, ac...
  function optimum_quanto_weights (line 681) | def optimum_quanto_weights(sd_model):
  function torchao_quantization (line 740) | def torchao_quantization(sd_model):
  function get_dit_args (line 765) | def get_dit_args(load_config:dict=None, module:str=None, device_map:bool...
  function do_post_load_quant (line 794) | def do_post_load_quant(sd_model, allow=True):

FILE: modules/model_te.py
  function load_t5 (line 14) | def load_t5(name=None, cache_dir=None):
  function set_t5 (line 112) | def set_t5(pipe, module, t5=None, cache_dir=None):
  function load_vit_l (line 142) | def load_vit_l():
  function load_vit_g (line 153) | def load_vit_g():
  function set_clip (line 164) | def set_clip(pipe):
  function refresh_te_list (line 200) | def refresh_te_list():

FILE: modules/model_tools.py
  function remove_entries_after_depth (line 8) | def remove_entries_after_depth(d, depth, current_depth=0):
  function list_compact (line 16) | def list_compact(flat_list):
  function list_to_dict (line 26) | def list_to_dict(flat_list):
  function get_safetensor_keys (line 40) | def get_safetensor_keys(filename):
  function get_modules (line 50) | def get_modules(model: callable):
  function load_modules (line 58) | def load_modules(repo_id: str, params: dict):

FILE: modules/modeldata.py
  function get_model_type (line 7) | def get_model_type(pipe):
  class ModelData (line 120) | class ModelData:
    method __init__ (line 121) | def __init__(self):
    method get_sd_model (line 129) | def get_sd_model(self):
    method set_sd_model (line 147) | def set_sd_model(self, v):
    method get_sd_refiner (line 151) | def get_sd_refiner(self):
    method set_sd_refiner (line 164) | def set_sd_refiner(self, v):
  class Shared (line 170) | class Shared(sys.modules[__name__].__class__):
    method sd_loaded (line 172) | def sd_loaded(self):
    method sd_model (line 177) | def sd_model(self):
    method sd_model (line 185) | def sd_model(self, value):
    method sd_refiner (line 190) | def sd_refiner(self):
    method sd_refiner (line 195) | def sd_refiner(self, value):
    method sd_model_type (line 200) | def sd_model_type(self):
    method sd_refiner_type (line 212) | def sd_refiner_type(self):

FILE: modules/modelloader.py
  function hf_login (line 22) | def hf_login(token=None):
  function download_diffusers_model (line 58) | def download_diffusers_model(hub_id: str, cache_dir: str = None, downloa...
  function load_diffusers_models (line 116) | def load_diffusers_models(clear=True):
  function find_diffuser (line 171) | def find_diffuser(name: str, full=False):
  function get_reference_opts (line 196) | def get_reference_opts(name: str, quiet=False):
  function load_reference (line 222) | def load_reference(name: str, variant: str = None, revision: str = None,...
  function load_civitai (line 253) | def load_civitai(model: str, url: str):
  function download_url_to_file (line 275) | def download_url_to_file(url: str, dst: str):
  function load_file_from_url (line 322) | def load_file_from_url(url: str, *, model_dir: str, progress: bool = Tru...
  function load_models (line 340) | def load_models(model_path: str, model_url: str = None, command_path: st...
  function friendly_name (line 366) | def friendly_name(file: str):
  function friendly_fullname (line 374) | def friendly_fullname(file: str):
  function cleanup_models (line 381) | def cleanup_models():
  function move_files (line 410) | def move_files(src_path: str, dest_path: str, ext_filter: str = None):
  function load_upscalers (line 433) | def load_upscalers():

FILE: modules/models_hf.py
  function hf_init (line 9) | def hf_init():
  function hf_check_cache (line 45) | def hf_check_cache():
  function hf_search (line 56) | def hf_search(keyword):
  function hf_select (line 69) | def hf_select(evt: gr.SelectData, df):
  function hf_download_model (line 75) | def hf_download_model(hub_id: str, token, variant, revision, mirror, cus...
  function hf_update_token (line 84) | def hf_update_token(token):

FILE: modules/modelstats.py
  function walk (line 7) | def walk(folder: str):
  function stat (line 15) | def stat(fn: str):
  class Module (line 31) | class Module():
    method __init__ (line 41) | def __init__(self, name, module):
    method __repr__ (line 55) | def __repr__(self):
  class Model (line 64) | class Model():
    method __init__ (line 76) | def __init__(self, name):
    method __repr__ (line 89) | def __repr__(self):
  function analyze (line 93) | def analyze():

FILE: modules/modular.py
  function is_compatible (line 20) | def is_compatible(diffusion_pipeline: diffusers.DiffusionPipeline) -> bool:
  function is_guider (line 29) | def is_guider(diffusion_pipeline: diffusers.DiffusionPipeline) -> bool:
  function convert_to_modular (line 34) | def convert_to_modular(diffusion_pipeline: diffusers.DiffusionPipeline) ...
  function restore_standard (line 65) | def restore_standard(modular_pipe):

FILE: modules/modular_guiders.py
  function set_guider (line 27) | def set_guider(p: processing.StableDiffusionProcessing):

FILE: modules/olive_script.py
  class ENVStore (line 8) | class ENVStore:
    method __getattr__ (line 20) | def __getattr__(self, name: str):
    method __setattr__ (line 28) | def __setattr__(self, name: str, value) -> None:
    method __delattr__ (line 35) | def __delattr__(self, name: str) -> None:
  class OliveOptimizerConfig (line 44) | class OliveOptimizerConfig(ENVStore):
  function get_variant (line 63) | def get_variant():
  function get_loader_arguments (line 79) | def get_loader_arguments(no_variant: bool = False):
  function from_pretrained (line 92) | def from_pretrained(cls: Type[T], pretrained_model_name_or_path: os.Path...
  class RandomDataLoader (line 107) | class RandomDataLoader:
    method __init__ (line 108) | def __init__(self, create_inputs_func, batchsize, torch_dtype):
    method __getitem__ (line 113) | def __getitem__(self, idx):
  function text_encoder_inputs (line 122) | def text_encoder_inputs(batchsize, torch_dtype): # pylint: disable=unuse...
  function text_encoder_load (line 130) | def text_encoder_load(model_name):
  function text_encoder_conversion_inputs (line 135) | def text_encoder_conversion_inputs(model): # pylint: disable=unused-argu...
  function text_encoder_data_loader (line 139) | def text_encoder_data_loader(data_dir, batchsize, *_, **__): # pylint: d...
  function text_encoder_2_inputs (line 148) | def text_encoder_2_inputs(batchsize, torch_dtype): # pylint: disable=unu...
  function text_encoder_2_load (line 155) | def text_encoder_2_load(model_name):
  function text_encoder_2_conversion_inputs (line 160) | def text_encoder_2_conversion_inputs(model): # pylint: disable=unused-ar...
  function text_encoder_2_data_loader (line 164) | def text_encoder_2_data_loader(data_dir, batchsize, *_, **__): # pylint:...
  function unet_inputs (line 173) | def unet_inputs(batchsize, torch_dtype, is_conversion_inputs=False): # p...
  function unet_load (line 218) | def unet_load(model_name):
  function unet_conversion_inputs (line 223) | def unet_conversion_inputs(model): # pylint: disable=unused-argument
  function unet_data_loader (line 227) | def unet_data_loader(data_dir, batchsize, *_, **__): # pylint: disable=u...
  function vae_encoder_inputs (line 236) | def vae_encoder_inputs(batchsize, torch_dtype): # pylint: disable=unused...
  function vae_encoder_load (line 243) | def vae_encoder_load(model_name):
  function vae_encoder_conversion_inputs (line 260) | def vae_encoder_conversion_inputs(model): # pylint: disable=unused-argument
  function vae_encoder_data_loader (line 264) | def vae_encoder_data_loader(data_dir, batchsize, *_, **__): # pylint: di...
  function vae_decoder_inputs (line 273) | def vae_decoder_inputs(batchsize, torch_dtype): # pylint: disable=unused...
  function vae_decoder_load (line 280) | def vae_decoder_load(model_name):
  function vae_decoder_conversion_inputs (line 297) | def vae_decoder_conversion_inputs(model): # pylint: disable=unused-argument
  function vae_decoder_data_loader (line 301) | def vae_decoder_data_loader(data_dir, batchsize, *_, **__): # pylint: di...

FILE: modules/onnx_impl/__init__.py
  class DynamicSessionOptions (line 18) | class DynamicSessionOptions(ort.SessionOptions):
    method __init__ (line 21) | def __init__(self):
    method from_sess_options (line 26) | def from_sess_options(cls, sess_options: ort.SessionOptions):
    method enable_static_dims (line 31) | def enable_static_dims(self, config: Dict):
    method copy (line 46) | def copy(self):
  class TorchCompatibleModule (line 53) | class TorchCompatibleModule:
    method named_modules (line 57) | def named_modules(self): # dummy
    method to (line 60) | def to(self, *_, **__):
    method type (line 63) | def type(self, *_, **__):
  class TemporalModule (line 67) | class TemporalModule(TorchCompatibleModule):
    method __init__ (line 75) | def __init__(self, provider: Any, path: str, sess_options: ort.Session...
    method to (line 80) | def to(self, *args, **kwargs):
  class OnnxRuntimeModel (line 91) | class OnnxRuntimeModel(TorchCompatibleModule, diffusers.OnnxRuntimeModel):
    method to (line 94) | def to(self, *args, **kwargs):
  class VAEConfig (line 104) | class VAEConfig:
    method __init__ (line 108) | def __init__(self, config: Dict):
    method __getattr__ (line 111) | def __getattr__(self, key):
    method get (line 114) | def get(self, key, default):
  class VAE (line 118) | class VAE(TorchCompatibleModule):
    method __init__ (line 121) | def __init__(self, pipeline: Any):
    method config (line 125) | def config(self):
    method device (line 129) | def device(self):
    method encode (line 132) | def encode(self, sample: torch.Tensor, *_, **__):
    method decode (line 140) | def decode(self, latent_sample: torch.Tensor, *_, **__):
    method to (line 148) | def to(self, *args, **kwargs):
  function check_parameters_changed (line 154) | def check_parameters_changed(p, refiner_enabled: bool):
  function preprocess_pipeline (line 178) | def preprocess_pipeline(p):
  function ORTPipelinePart_to (line 195) | def ORTPipelinePart_to(self, *args, **kwargs):
  function initialize_onnx (line 200) | def initialize_onnx():
  function initialize_onnx_pipelines (line 220) | def initialize_onnx_pipelines():
  function install_olive (line 248) | def install_olive():

FILE: modules/onnx_impl/execution_providers.py
  class ExecutionProvider (line 8) | class ExecutionProvider(str, Enum):
  function get_default_execution_provider (line 43) | def get_default_execution_provider() -> ExecutionProvider:
  function get_execution_provider_options (line 57) | def get_execution_provider_options():
  function get_provider (line 93) | def get_provider() -> Tuple:
  function install_execution_provider (line 98) | def install_execution_provider(ep: ExecutionProvider):

FILE: modules/onnx_impl/pipelines/__init__.py
  class PipelineBase (line 28) | class PipelineBase(TorchCompatibleModule, diffusers.DiffusionPipeline, m...
    method __init__ (line 34) | def __init__(self): # pylint: disable=super-init-not-called
    method to (line 37) | def to(self, *args, **kwargs):
    method components (line 68) | def components(self):
    method from_pretrained (line 72) | def from_pretrained(cls, pretrained_model_name_or_path, **_): # pylint...
    method from_single_file (line 79) | def from_single_file(cls, pretrained_model_name_or_path, **_):
    method from_ckpt (line 86) | def from_ckpt(cls, pretrained_model_name_or_path, **_):
  class CallablePipelineBase (line 90) | class CallablePipelineBase(PipelineBase):
    method __init__ (line 93) | def __init__(self):
  class OnnxRawPipeline (line 98) | class OnnxRawPipeline(PipelineBase):
    method __init__ (line 111) | def __init__(self, constructor: Type[PipelineBase], path: os.PathLike)...
    method derive_properties (line 146) | def derive_properties(self, pipeline: diffusers.DiffusionPipeline):
    method convert (line 153) | def convert(self, submodels: List[str], in_dir: os.PathLike, out_dir: ...
    method run_olive (line 221) | def run_olive(self, submodels: List[str], in_dir: os.PathLike, out_dir...
    method preprocess (line 323) | def preprocess(self, p: 'StableDiffusionProcessing'):

FILE: modules/onnx_impl/pipelines/onnx_stable_diffusion_img2img_pipeline.py
  class OnnxStableDiffusionImg2ImgPipeline (line 13) | class OnnxStableDiffusionImg2ImgPipeline(diffusers.OnnxStableDiffusionIm...
    method __init__ (line 19) | def __init__(
    method __call__ (line 34) | def __call__(

FILE: modules/onnx_impl/pipelines/onnx_stable_diffusion_inpaint_pipeline.py
  class OnnxStableDiffusionInpaintPipeline (line 13) | class OnnxStableDiffusionInpaintPipeline(diffusers.OnnxStableDiffusionIn...
    method __init__ (line 17) | def __init__(
    method __call__ (line 32) | def __call__(

FILE: modules/onnx_impl/pipelines/onnx_stable_diffusion_pipeline.py
  class OnnxStableDiffusionPipeline (line 12) | class OnnxStableDiffusionPipeline(diffusers.OnnxStableDiffusionPipeline,...
    method __init__ (line 16) | def __init__(
    method __call__ (line 30) | def __call__(

FILE: modules/onnx_impl/pipelines/onnx_stable_diffusion_upscale_pipeline.py
  class OnnxStableDiffusionUpscalePipeline (line 14) | class OnnxStableDiffusionUpscalePipeline(diffusers.OnnxStableDiffusionUp...
    method __init__ (line 18) | def __init__(
    method __call__ (line 32) | def __call__(

FILE: modules/onnx_impl/pipelines/onnx_stable_diffusion_xl_img2img_pipeline.py
  class OnnxStableDiffusionXLImg2ImgPipeline (line 11) | class OnnxStableDiffusionXLImg2ImgPipeline(CallablePipelineBase, optimum...
    method __init__ (line 15) | def __init__(
    method prepare_latents (line 35) | def prepare_latents(self, image, timestep, batch_size, num_images_per_...

FILE: modules/onnx_impl/pipelines/onnx_stable_diffusion_xl_pipeline.py
  class OnnxStableDiffusionXLPipeline (line 8) | class OnnxStableDiffusionXLPipeline(CallablePipelineBase, optimum.onnxru...
    method __init__ (line 12) | def __init__(
    method prepare_latents (line 32) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...

FILE: modules/onnx_impl/pipelines/utils.py
  function extract_generator_seed (line 6) | def extract_generator_seed(generator: Union[torch.Generator, List[torch....
  function randn_tensor (line 14) | def randn_tensor(shape, dtype: np.dtype, generator: Union[torch.Generato...
  function prepare_latents (line 22) | def prepare_latents(

FILE: modules/onnx_impl/ui.py
  function get_recursively (line 8) | def get_recursively(d: Union[Dict, List], *args):
  function create_ui (line 14) | def create_ui():

FILE: modules/onnx_impl/utils.py
  function extract_device (line 9) | def extract_device(args: List, kwargs: Dict):
  function move_inference_session (line 20) | def move_inference_session(session, device: torch.device): # session: or...
  function check_diffusers_cache (line 40) | def check_diffusers_cache(path: os.PathLike):
  function check_pipeline_sdxl (line 45) | def check_pipeline_sdxl(cls: Type[diffusers.DiffusionPipeline]) -> bool:
  function check_cache_onnx (line 49) | def check_cache_onnx(path: os.PathLike) -> bool:
  function load_init_dict (line 69) | def load_init_dict(cls: Type[diffusers.DiffusionPipeline], path: os.Path...
  function load_submodel (line 88) | def load_submodel(path: os.PathLike, is_sdxl: bool, submodel_name: str, ...
  function load_submodels (line 110) | def load_submodels(path: os.PathLike, is_sdxl: bool, init_dict: Dict[str...
  function load_pipeline (line 125) | def load_pipeline(cls: Type[diffusers.DiffusionPipeline], path: os.PathL...
  function patch_kwargs (line 132) | def patch_kwargs(cls: Type[diffusers.DiffusionPipeline], kwargs: Dict) -...
  function get_base_constructor (line 143) | def get_base_constructor(cls: Type[diffusers.DiffusionPipeline], is_refi...
  function get_io_config (line 153) | def get_io_config(submodel: str, is_sdxl: bool):

FILE: modules/options.py
  function options_section (line 14) | def options_section(section_identifier: tuple[str, str], options_dict: d...
  class OptionInfo (line 23) | class OptionInfo:
    method __init__ (line 24) | def __init__(
    method needs_reload_ui (line 57) | def needs_reload_ui(self):
    method link (line 60) | def link(self, label, uri):
    method js (line 64) | def js(self, label, js_func):
    method info (line 68) | def info(self, info):
    method html (line 72) | def html(self, info):
    method needs_restart (line 76) | def needs_restart(self):
    method validate (line 80) | def validate(self, opt, value):
    method __str__ (line 115) | def __str__(self) -> str:
  class OptionsCategory (line 124) | class OptionsCategory:
  class OptionsCategories (line 128) | class OptionsCategories:
    method __init__ (line 129) | def __init__(self):
    method register_category (line 132) | def register_category(self, category_id, label):

FILE: modules/options_handler.py
  class Options (line 21) | class Options():
    method __init__ (line 27) | def __init__(self, options_templates: dict[str, OptionInfo | LegacyOpt...
    method __setattr__ (line 37) | def __setattr__(self, key, value): # pylint: disable=inconsistent-retu...
    method get (line 53) | def get(self, item):
    method __getattr__ (line 60) | def __getattr__(self, item):
    method set (line 67) | def set(self, key, value):
    method get_default (line 93) | def get_default(self, key):
    method list (line 98) | def list(self):
    method save_atomic (line 103) | def save_atomic(self, filename=None, silent=False):
    method save (line 151) | def save(self, filename=None, silent=False):
    method same_type (line 154) | def same_type(self, x, y):
    method load (line 161) | def load(self, filename=None):
    method onchange (line 186) | def onchange(self, key, func: Callable, call=True):
    method dumpjson (line 192) | def dumpjson(self):
    method add_option (line 202) | def add_option(self, key, info):
    method reorder (line 205) | def reorder(self):
    method cast_value (line 214) | def cast_value(self, key, value):

FILE: modules/pag/__init__.py
  function apply (line 11) | def apply(p: processing.StableDiffusionProcessing): # pylint: disable=ar...
  function unapply (line 50) | def unapply():

FILE: modules/pag/pipe_sd.py
  class PAGIdentitySelfAttnProcessor (line 47) | class PAGIdentitySelfAttnProcessor:
    method __init__ (line 52) | def __init__(self):
    method __call__ (line 56) | def __call__(
  class PAGCFGIdentitySelfAttnProcessor (line 160) | class PAGCFGIdentitySelfAttnProcessor:
    method __init__ (line 165) | def __init__(self):
    method __call__ (line 169) | def __call__(
  function rescale_noise_cfg (line 271) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 285) | def retrieve_timesteps(
  class StableDiffusionPAGPipeline (line 327) | class StableDiffusionPAGPipeline(
    method __init__ (line 365) | def __init__(
    method enable_vae_slicing (line 457) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 464) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 471) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 479) | def disable_vae_tiling(self):
    method _encode_prompt (line 486) | def _encode_prompt(
    method encode_prompt (line 518) | def encode_prompt(
    method encode_image (line 698) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 722) | def prepare_ip_adapter_image_embeds(
    method run_safety_checker (line 756) | def run_safety_checker(self, image, device, dtype):
    method decode_latents (line 770) | def decode_latents(self, latents):
    method prepare_extra_step_kwargs (line 781) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 798) | def check_inputs(
    method prepare_latents (line 857) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method enable_freeu (line 874) | def enable_freeu(self, s1: float, s2: float, b1: float, b2: float):
    method disable_freeu (line 893) | def disable_freeu(self):
    method fuse_qkv_projections (line 898) | def fuse_qkv_projections(self, unet: bool = True, vae: bool = True):
    method unfuse_qkv_projections (line 926) | def unfuse_qkv_projections(self, unet: bool = True, vae: bool = True):
    method get_guidance_scale_embedding (line 950) | def get_guidance_scale_embedding(self, w, embedding_dim=512, dtype=tor...
    method pred_z0 (line 976) | def pred_z0(self, sample, model_output, timestep):
    method pred_x0 (line 996) | def pred_x0(self, latents, noise_pred, t, generator, device, prompt_em...
    method guidance_scale (line 1006) | def guidance_scale(self):
    method guidance_rescale (line 1010) | def guidance_rescale(self):
    method clip_skip (line 1014) | def clip_skip(self):
    method do_classifier_free_guidance (line 1021) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 1025) | def cross_attention_kwargs(self):
    method num_timesteps (line 1029) | def num_timesteps(self):
    method interrupt (line 1033) | def interrupt(self):
    method pag_scale (line 1037) | def pag_scale(self):
    method do_perturbed_attention_guidance (line 1041) | def do_perturbed_attention_guidance(self):
    method pag_adaptive_scaling (line 1045) | def pag_adaptive_scaling(self):
    method do_pag_adaptive_scaling (line 1049) | def do_pag_adaptive_scaling(self):
    method pag_applied_layers_index (line 1053) | def pag_applied_layers_index(self):
    method __call__ (line 1058) | def __call__(

FILE: modules/pag/pipe_sdxl.py
  class PAGIdentitySelfAttnProcessor (line 67) | class PAGIdentitySelfAttnProcessor:
    method __init__ (line 72) | def __init__(self):
    method __call__ (line 76) | def __call__(
  class PAGCFGIdentitySelfAttnProcessor (line 180) | class PAGCFGIdentitySelfAttnProcessor:
    method __init__ (line 185) | def __init__(self):
    method __call__ (line 189) | def __call__(
  function rescale_noise_cfg (line 302) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 316) | def retrieve_timesteps(
  class StableDiffusionXLPAGPipeline (line 359) | class StableDiffusionXLPAGPipeline(
    method __init__ (line 431) | def __init__(
    method encode_prompt (line 472) | def encode_prompt(
    method encode_image (line 707) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 732) | def prepare_ip_adapter_image_embeds(
    method prepare_extra_step_kwargs (line 784) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 801) | def check_inputs(
    method prepare_latents (line 898) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 915) | def _get_add_time_ids(
    method upcast_vae (line 933) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 952) | def get_guidance_scale_embedding(
    method pred_z0 (line 982) | def pred_z0(self, sample, model_output, timestep):
    method pred_x0 (line 1002) | def pred_x0(self, latents, noise_pred, t, generator, device, prompt_em...
    method guidance_scale (line 1016) | def guidance_scale(self):
    method guidance_rescale (line 1020) | def guidance_rescale(self):
    method clip_skip (line 1024) | def clip_skip(self):
    method do_classifier_free_guidance (line 1031) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 1035) | def cross_attention_kwargs(self):
    method denoising_end (line 1039) | def denoising_end(self):
    method num_timesteps (line 1043) | def num_timesteps(self):
    method interrupt (line 1047) | def interrupt(self):
    method pag_scale (line 1051) | def pag_scale(self):
    method do_adversarial_guidance (line 1055) | def do_adversarial_guidance(self):
    method pag_adaptive_scaling (line 1059) | def pag_adaptive_scaling(self):
    method do_pag_adaptive_scaling (line 1063) | def do_pag_adaptive_scaling(self):
    method pag_drop_rate (line 1067) | def pag_drop_rate(self):
    method pag_applied_layers (line 1071) | def pag_applied_layers(self):
    method pag_applied_layers_index (line 1075) | def pag_applied_layers_index(self):
    method __call__ (line 1080) | def __call__(

FILE: modules/para_attention.py
  function apply_first_block_cache (line 7) | def apply_first_block_cache():

FILE: modules/patches.py
  function patch (line 6) | def patch(key, obj, field, replacement, add_if_not_exists:bool = False):
  function undo (line 31) | def undo(key, obj, field):
  function original (line 52) | def original(key, obj, field):
  function patch_method (line 58) | def patch_method(cls, key:Optional[str]=None):
  function add_method (line 64) | def add_method(cls, key:Optional[str]=None):

FILE: modules/paths.py
  function create_path (line 53) | def create_path(folder):
  function resolve_output_path (line 65) | def resolve_output_path(base_path: str, specific_path: str) -> str:
  function create_paths (line 82) | def create_paths(opts):
  class Prioritize (line 153) | class Prioritize:
    method __init__ (line 154) | def __init__(self, name):
    method __enter__ (line 158) | def __enter__(self):
    method __exit__ (line 162) | def __exit__(self, exc_type, exc_val, exc_tb):

FILE: modules/postprocess/aurasr_arch.py
  function get_same_padding (line 19) | def get_same_padding(size, kernel, dilation, stride):
  class AdaptiveConv2DMod (line 23) | class AdaptiveConv2DMod(nn.Module):
    method __init__ (line 24) | def __init__(
    method forward (line 56) | def forward(
  class Attend (line 127) | class Attend(nn.Module):
    method __init__ (line 128) | def __init__(self, dropout=0.0, flash=False):
    method flash_attn (line 135) | def flash_attn(self, q, k, v):
    method forward (line 142) | def forward(self, q, k, v):
  function exists (line 161) | def exists(x):
  function default (line 165) | def default(val, d):
  function cast_tuple (line 171) | def cast_tuple(t, length=1):
  function identity (line 177) | def identity(t, *args, **kwargs):
  function is_power_of_two (line 181) | def is_power_of_two(n):
  function null_iterator (line 185) | def null_iterator():
  function Downsample (line 189) | def Downsample(dim, dim_out=None):
  class RMSNorm (line 196) | class RMSNorm(nn.Module):
    method __init__ (line 197) | def __init__(self, dim):
    method forward (line 202) | def forward(self, x):
  class Block (line 209) | class Block(nn.Module):
    method __init__ (line 210) | def __init__(self, dim, dim_out, groups=8, num_conv_kernels=0):
    method forward (line 221) | def forward(self, x, conv_mods_iter: Optional[Iterable] = None):
  class ResnetBlock (line 230) | class ResnetBlock(nn.Module):
    method __init__ (line 231) | def __init__(
    method forward (line 245) | def forward(self, x, conv_mods_iter: Optional[Iterable] = None):
  class LinearAttention (line 252) | class LinearAttention(nn.Module):
    method __init__ (line 253) | def __init__(self, dim, heads=4, dim_head=32):
    method forward (line 264) | def forward(self, x):
  class Attention (line 286) | class Attention(nn.Module):
    method __init__ (line 287) | def __init__(self, dim, heads=4, dim_head=32, flash=False):
    method forward (line 298) | def forward(self, x):
  function FeedForward (line 314) | def FeedForward(dim, mult=4):
  class Transformer (line 324) | class Transformer(nn.Module):
    method __init__ (line 325) | def __init__(self, dim, dim_head=64, heads=8, depth=1, flash_attn=True...
    method forward (line 341) | def forward(self, x):
  class LinearTransformer (line 349) | class LinearTransformer(nn.Module):
    method __init__ (line 350) | def __init__(self, dim, dim_head=64, heads=8, depth=1, ff_mult=4):
    method forward (line 364) | def forward(self, x):
  class NearestNeighborhoodUpsample (line 372) | class NearestNeighborhoodUpsample(nn.Module):
    method __init__ (line 373) | def __init__(self, dim, dim_out=None):
    method forward (line 378) | def forward(self, x):
  class EqualLinear (line 388) | class EqualLinear(nn.Module):
    method __init__ (line 389) | def __init__(self, dim, dim_out, lr_mul=1, bias=True):
    method forward (line 397) | def forward(self, input):
  class StyleGanNetwork (line 401) | class StyleGanNetwork(nn.Module):
    method __init__ (line 402) | def __init__(self, dim_in=128, dim_out=512, depth=8, lr_mul=0.1, dim_t...
    method forward (line 425) | def forward(self, x, text_latent=None):
  class UnetUpsampler (line 433) | class UnetUpsampler(torch.nn.Module):
    method __init__ (line 435) | def __init__(
    method allowable_rgb_resolutions (line 611) | def allowable_rgb_resolutions(self):
    method device (line 618) | def device(self):
    method total_params (line 622) | def total_params(self):
    method resize_image_to (line 625) | def resize_image_to(self, x, size):
    method forward (line 628) | def forward(
  function tile_image (line 710) | def tile_image(image, chunk_size=64):
  function merge_tiles (line 722) | def merge_tiles(tiles, h_chunks, w_chunks, chunk_size=64):
  class AuraSR (line 745) | class AuraSR:
    method __init__ (line 746) | def __init__(self, config: dict[str, Any], device: str = "cuda"):
    method from_pretrained (line 751) | def from_pretrained(cls, model_id: str = "fal-ai/AuraSR", use_safetens...
    method upscale_4x (line 803) | def upscale_4x(self, image: Image.Image, max_batch_size=8) -> Image.Im...

FILE: modules/postprocess/aurasr_model.py
  class UpscalerAuraSR (line 8) | class UpscalerAuraSR(Upscaler):
    method __init__ (line 9) | def __init__(self, dirname): # pylint: disable=super-init-not-called
    method callback (line 17) | def callback(self, _step: int, _timestep: int, _latents: torch.FloatTe...
    method do_upscale (line 20) | def do_upscale(self, img: Image.Image, selected_model):

FILE: modules/postprocess/codeformer_arch.py
  function calc_mean_std (line 10) | def calc_mean_std(feat, eps=1e-5):
  function adaptive_instance_normalization (line 27) | def adaptive_instance_normalization(content_feat, style_feat):
  class PositionEmbeddingSine (line 44) | class PositionEmbeddingSine(nn.Module):
    method __init__ (line 50) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 61) | def forward(self, x, mask=None):
  function _get_activation_fn (line 86) | def _get_activation_fn(activation):
  class TransformerSALayer (line 97) | class TransformerSALayer(nn.Module):
    method __init__ (line 98) | def __init__(self, embed_dim, nhead=8, dim_mlp=2048, dropout=0.0, acti...
    method with_pos_embed (line 113) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward (line 116) | def forward(self, tgt,
  class Fuse_sft_block (line 133) | class Fuse_sft_block(nn.Module):
    method __init__ (line 134) | def __init__(self, in_ch, out_ch):
    method forward (line 148) | def forward(self, enc_feat, dec_feat, w=1):
  class CodeFormer (line 157) | class CodeFormer(VQAutoEncoder):
    method __init__ (line 158) | def __init__(self, dim_embd=512, n_head=8, n_layers=9,
    method _init_weights (line 206) | def _init_weights(self, module):
    method forward (line 215) | def forward(self, x, w=0, detach_16=True, code_only=False, adain=False):

FILE: modules/postprocess/codeformer_model.py
  function setup_model (line 20) | def setup_model(dirname):

FILE: modules/postprocess/dcc.py
  function DetectDirect (line 4) | def DetectDirect(A, dcc_type, k, T):
  function PixelValue (line 43) | def PixelValue(A, mode, w, n, f):
  function PadLeftTop (line 60) | def PadLeftTop(img_pad, H, W):
  function PadRightBottom (line 74) | def PadRightBottom(img_pad, H, W):
  function _DCC (line 88) | def _DCC(I, k, T):
  function DCC (line 117) | def DCC(img, level):

FILE: modules/postprocess/esrgan_model.py
  function mod2normal (line 10) | def mod2normal(state_dict):
  function resrgan2normal (line 43) | def resrgan2normal(state_dict, nb=23):
  function infer_params (line 86) | def infer_params(state_dict):
  class UpscalerESRGAN (line 118) | class UpscalerESRGAN(Upscaler):
    method __init__ (line 119) | def __init__(self, dirname):
    method do_upscale (line 126) | def do_upscale(self, img, selected_model):
    method load_model (line 138) | def load_model(self, path: str):
  function upscale_without_tiling (line 176) | def upscale_without_tiling(model, img):
  function esrgan_upscale (line 191) | def esrgan_upscale(model, img):

FILE: modules/postprocess/esrgan_model_arch.py
  class RRDBNet (line 13) | class RRDBNet(nn.Module):
    method __init__ (line 14) | def __init__(self, in_nc, out_nc, nf, nb, nr=3, gc=32, upscale=4, norm...
    method forward (line 52) | def forward(self, x, outm=None):
  class RRDB (line 63) | class RRDB(nn.Module):
    method __init__ (line 69) | def __init__(self, nf, nr=3, kernel_size=3, gc=32, stride=1, bias=1, p...
    method forward (line 90) | def forward(self, x):
  class ResidualDenseBlock_5C (line 100) | class ResidualDenseBlock_5C(nn.Module):
    method __init__ (line 111) | def __init__(self, nf=64, kernel_size=3, gc=32, stride=1, bias=1, pad_...
    method forward (line 139) | def forward(self, x):
  class GaussianNoise (line 159) | class GaussianNoise(nn.Module):
    method __init__ (line 160) | def __init__(self, sigma=0.1, is_relative_detach=False):
    method forward (line 166) | def forward(self, x):
  function conv1x1 (line 174) | def conv1x1(in_planes, out_planes, stride=1):
  class SRVGGNetCompact (line 182) | class SRVGGNetCompact(nn.Module):
    method __init__ (line 187) | def __init__(self, num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16...
    method forward (line 225) | def forward(self, x):
  class Upsample (line 241) | class Upsample(nn.Module):
    method __init__ (line 247) | def __init__(self, size=None, scale_factor=None, mode="nearest", align...
    method forward (line 257) | def forward(self, x):
    method extra_repr (line 260) | def extra_repr(self):
  function pixel_unshuffle (line 269) | def pixel_unshuffle(x, scale):
  function pixelshuffle_block (line 286) | def pixelshuffle_block(in_nc, out_nc, upscale_factor=2, kernel_size=3, s...
  function upconv_block (line 302) | def upconv_block(in_nc, out_nc, upscale_factor=2, kernel_size=3, stride=...
  function make_layer (line 323) | def make_layer(basic_block, num_basic_block, **kwarg):
  function act (line 337) | def act(act_type, inplace=True, neg_slope=0.2, n_prelu=1, beta=1.0):
  class Identity (line 355) | class Identity(nn.Module):
    method __init__ (line 356) | def __init__(self, *kwargs):
    method forward (line 359) | def forward(self, x, *kwargs):
  function norm (line 363) | def norm(norm_type, nc):
  function pad (line 377) | def pad(pad_type, padding):
  function get_valid_padding (line 393) | def get_valid_padding(kernel_size, dilation):
  class ShortcutBlock (line 399) | class ShortcutBlock(nn.Module):
    method __init__ (line 401) | def __init__(self, submodule):
    method forward (line 405) | def forward(self, x):
    method __repr__ (line 409) | def __repr__(self):
  function sequential (line 413) | def sequential(*args):
  function conv_block (line 430) | def conv_block(in_nc, out_nc, kernel_size, stride=1, dilation=1, groups=...

FILE: modules/postprocess/gfpgan_model.py
  function gfpgann (line 14) | def gfpgann():
  function send_model_to (line 40) | def send_model_to(model, device):
  function gfpgan_fix_faces (line 46) | def gfpgan_fix_faces(np_image):
  function setup_model (line 68) | def setup_model(dirname):

FILE: modules/postprocess/hqx.py
  function RGBtoYUV (line 18) | def RGBtoYUV(c):
  function Diff (line 26) | def Diff(w1, w2):
  function Interp1 (line 33) | def Interp1( pc, c1, c2, dest ):
  function Interp2 (line 42) | def Interp2( pc, c1, c2, c3, dest ):
  function Interp3 (line 48) | def Interp3( pc, c1, c2, dest ):
  function Interp4 (line 57) | def Interp4( pc, c1, c2, c3, dest ):
  function Interp5 (line 63) | def Interp5( pc, c1, c2, dest ):
  function Interp6 (line 72) | def Interp6( pc, c1, c2, c3, dest ):
  function Interp7 (line 78) | def Interp7( pc, c1, c2, c3, dest ):
  function Interp8 (line 84) | def Interp8( pc, c1, c2, dest ):
  function Interp9 (line 93) | def Interp9( pc, c1, c2, c3, dest ):
  function Interp10 (line 99) | def Interp10( pc, c1, c2, c3, dest ):
  function hqx (line 105) | def hqx( img: cv2.Mat, scale_factor: int ) -> cv2.Mat:
  function hq2x (line 139) | def hq2x( width: int, height: int, src, dest ) -> None: # noqa:C901 # py...
  function hq3x (line 1561) | def hq3x( width: int, height: int, src, dest ) -> None: # noqa:C901 # py...
  function hq4x (line 3955) | def hq4x( width: int, height: int, src, dest ) -> None: # noqa:C901 # py...
  function main (line 7709) | def main():

FILE: modules/postprocess/icbi.py
  function icbi (line 11) | def icbi(IM,ZK = 1,SZ = 8,PF = 1,ST = 20,TM = 100,TC = 50,SC = 1,TS = 10...

FILE: modules/postprocess/pixelart.py
  function img_to_pixelart (line 18) | def img_to_pixelart(image: PipelineImageInput, sharpen: float = 0, block...
  function edge_detect_for_pixelart (line 50) | def edge_detect_for_pixelart(image: PipelineImageInput, image_weight: fl...
  function get_dct_harmonics (line 80) | def get_dct_harmonics(N: int, device: torch.device) -> torch.FloatTensor:
  function get_dct_norm (line 87) | def get_dct_norm(N: int, device: torch.device) -> torch.FloatTensor:
  function dct_2d (line 94) | def dct_2d(x: torch.FloatTensor, norm: str="ortho") -> torch.FloatTensor:
  function idct_2d (line 108) | def idct_2d(coeff: torch.FloatTensor, norm: str="ortho") -> torch.FloatT...
  function encode_single_channel_dct_2d (line 122) | def encode_single_channel_dct_2d(img: torch.FloatTensor, block_size: int...
  function decode_single_channel_dct_2d (line 136) | def decode_single_channel_dct_2d(img: torch.FloatTensor, norm: str="orth...
  function rgb_to_ycbcr_tensor (line 148) | def rgb_to_ycbcr_tensor(image: torch.ByteTensor) -> torch.FloatTensor:
  function ycbcr_tensor_to_rgb (line 155) | def ycbcr_tensor_to_rgb(ycbcr: torch.FloatTensor) -> torch.ByteTensor:
  function encode_jpeg_tensor (line 160) | def encode_jpeg_tensor(img: torch.FloatTensor, block_size: int=16, cbcr_...
  function decode_jpeg_tensor (line 172) | def decode_jpeg_tensor(jpeg_img: torch.FloatTensor, block_size: int=16, ...
  function process_image_input (line 189) | def process_image_input(images: PipelineImageInput) -> torch.ByteTensor:
  class JPEGEncoder (line 223) | class JPEGEncoder(ImageProcessingMixin, ConfigMixin):
    method __init__ (line 228) | def __init__(
    method encode (line 243) | def encode(self, images: PipelineImageInput, device: str="cpu") -> tor...
    method decode (line 268) | def decode(self, latents: torch.FloatTensor, return_type: str="pil") -...

FILE: modules/postprocess/realesrgan_model.py
  class UpscalerRealESRGAN (line 10) | class UpscalerRealESRGAN(Upscaler):
    method __init__ (line 11) | def __init__(self, dirname):
    method load_model (line 34) | def load_model(self, path): # pylint: disable=unused-argument
    method do_upscale (line 37) | def do_upscale(self, img, selected_model):

FILE: modules/postprocess/realesrgan_model_arch.py
  class RealESRGANer (line 17) | class RealESRGANer():
    method __init__ (line 32) | def __init__(self,
    method dni (line 84) | def dni(self, net_a, net_b, dni_weight, key='params', loc='cpu'):
    method pre_process (line 95) | def pre_process(self, img):
    method process (line 120) | def process(self):
    method tile_process (line 124) | def tile_process(self):
    method post_process (line 195) | def post_process(self):
    method enhance (line 207) | def enhance(self, img, outscale=None, alpha_upsampler='realesrgan'):
  class PrefetchReader (line 278) | class PrefetchReader(threading.Thread):
    method __init__ (line 286) | def __init__(self, img_list, num_prefetch_queue):
    method run (line 291) | def run(self):
    method __next__ (line 298) | def __next__(self):
    method __iter__ (line 304) | def __iter__(self):
  class IOConsumer (line 308) | class IOConsumer(threading.Thread):
    method __init__ (line 310) | def __init__(self, opt, que, qid):
    method run (line 316) | def run(self):
  class SRVGGNetCompact (line 327) | class SRVGGNetCompact(nn.Module):
    method __init__ (line 342) | def __init__(self, num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=16...
    method forward (line 380) | def forward(self, x):

FILE: modules/postprocess/restorer.py
  function restore (line 10) | def restore(np_image, name, session, strength): # pylint: disable=unused...

FILE: modules/postprocess/scunet_model.py
  class UpscalerSCUNet (line 11) | class UpscalerSCUNet(Upscaler):
    method __init__ (line 12) | def __init__(self, dirname):
    method load_model (line 19) | def load_model(self, path: str):
    method tiled_inference (line 40) | def tiled_inference(img, model):
    method do_upscale (line 71) | def do_upscale(self, img: Image.Image, selected_file):

FILE: modules/postprocess/scunet_model_arch.py
  class WMSA (line 10) | class WMSA(nn.Module):
    method __init__ (line 14) | def __init__(self, input_dim, output_dim, head_dim, window_size, type):
    method generate_mask (line 36) | def generate_mask(self, h, w, p, shift):
    method forward (line 56) | def forward(self, x):
    method relative_embedding (line 95) | def relative_embedding(self):
  class Block (line 102) | class Block(nn.Module):
    method __init__ (line 103) | def __init__(self, input_dim, output_dim, head_dim, window_size, drop_...
    method forward (line 124) | def forward(self, x):
  class ConvTransBlock (line 130) | class ConvTransBlock(nn.Module):
    method __init__ (line 131) | def __init__(self, conv_dim, trans_dim, head_dim, window_size, drop_pa...
    method forward (line 158) | def forward(self, x):
  class SCUNet (line 170) | class SCUNet(nn.Module):
    method __init__ (line 172) | def __init__(self, in_nc=3, config=None, dim=64, drop_path_rate=0.0, i...
    method forward (line 240) | def forward(self, x0):
    method _init_weights (line 261) | def _init_weights(self, m):

FILE: modules/postprocess/sdupscaler_model.py
  class UpscalerDiffusion (line 8) | class UpscalerDiffusion(Upscaler):
    method __init__ (line 9) | def __init__(self, dirname): # pylint: disable=super-init-not-called
    method load_model (line 22) | def load_model(self, path: str):
    method callback (line 40) | def callback(self, _step: int, _timestep: int, _latents: torch.FloatTe...
    method do_upscale (line 43) | def do_upscale(self, img: Image.Image, selected_model):

FILE: modules/postprocess/seedvr_model.py
  class UpscalerSeedVR (line 20) | class UpscalerSeedVR(Upscaler):
    method __init__ (line 21) | def __init__(self, dirname=None):
    method load_model (line 32) | def load_model(self, path: str):
    method vae_encode (line 66) | def vae_encode(self, samples):
    method vae_decode (line 93) | def vae_decode(self, latents, target_dtype: torch.dtype = None):
    method model_step (line 121) | def model_step(self, *args, **kwargs):
    method do_upscale (line 134) | def do_upscale(self, img: Image.Image, selected_file):

FILE: modules/postprocess/swinir_model.py
  class UpscalerSwinIR (line 11) | class UpscalerSwinIR(Upscaler):
    method __init__ (line 12) | def __init__(self, dirname):
    method load_model (line 19) | def load_model(self, path, scale=4):
    method do_upscale (line 68) | def do_upscale(self, img, selected_model):
  function upscale (line 81) | def upscale(
  function inference (line 113) | def inference(img, model, tile, tile_overlap, window_size, scale):

FILE: modules/postprocess/swinir_model_arch.py
  class Mlp (line 14) | class Mlp(nn.Module):
    method __init__ (line 15) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 24) | def forward(self, x):
  function window_partition (line 33) | def window_partition(x, window_size):
  function window_reverse (line 48) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 65) | class WindowAttention(nn.Module):
    method __init__ (line 79) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 114) | def forward(self, x, mask=None):
    method extra_repr (line 147) | def extra_repr(self) -> str:
    method flops (line 150) | def flops(self, N):
  class SwinTransformerBlock (line 164) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 183) | def __init__(self, dim, input_resolution, num_heads, window_size=7, sh...
    method calculate_mask (line 216) | def calculate_mask(self, x_size):
    method forward (line 239) | def forward(self, x, x_size):
    method extra_repr (line 281) | def extra_repr(self) -> str:
    method flops (line 284) | def flops(self):
  class PatchMerging (line 299) | class PatchMerging(nn.Module):
    method __init__ (line 308) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 315) | def forward(self, x):
    method extra_repr (line 338) | def extra_repr(self) -> str:
    method flops (line 341) | def flops(self):
  class BasicLayer (line 348) | class BasicLayer(nn.Module):
    method __init__ (line 368) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
    method forward (line 396) | def forward(self, x, x_size):
    method extra_repr (line 406) | def extra_repr(self) -> str:
    method flops (line 409) | def flops(self):
  class RSTB (line 418) | class RSTB(nn.Module):
    method __init__ (line 441) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
    method forward (line 480) | def forward(self, x, x_size):
    method flops (line 483) | def flops(self):
  class PatchEmbed (line 494) | class PatchEmbed(nn.Module):
    method __init__ (line 505) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 523) | def forward(self, x):
    method flops (line 529) | def flops(self):
  class PatchUnEmbed (line 537) | class PatchUnEmbed(nn.Module):
    method __init__ (line 548) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 561) | def forward(self, x, x_size):
    method flops (line 566) | def flops(self):
  class Upsample (line 571) | class Upsample(nn.Sequential):
    method __init__ (line 579) | def __init__(self, scale, num_feat):
  class UpsampleOneStep (line 593) | class UpsampleOneStep(nn.Sequential):
    method __init__ (line 603) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
    method flops (line 611) | def flops(self):
  class SwinIR (line 617) | class SwinIR(nn.Module):
    method __init__ (line 645) | def __init__(self, img_size=64, patch_size=1, in_chans=3,
    method _init_weights (line 765) | def _init_weights(self, m):
    method no_weight_decay (line 775) | def no_weight_decay(self):
    method no_weight_decay_keywords (line 779) | def no_weight_decay_keywords(self):
    method check_image_size (line 782) | def check_image_size(self, x):
    method forward_features (line 789) | def forward_features(self, x):
    method forward (line 804) | def forward(self, x):
    method flops (line 841) | def flops(self):

FILE: modules/postprocess/swinir_model_arch_v2.py
  class Mlp (line 15) | class Mlp(nn.Module):
    method __init__ (line 16) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 25) | def forward(self, x):
  function window_partition (line 34) | def window_partition(x, window_size):
  function window_reverse (line 48) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 63) | class WindowAttention(nn.Module):
    method __init__ (line 76) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, attn_dr...
    method forward (line 135) | def forward(self, x, mask=None):
    method extra_repr (line 176) | def extra_repr(self) -> str:
    method flops (line 179) | def flops(self, N):
  class SwinTransformerBlock (line 192) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 210) | def __init__(self, dim, input_resolution, num_heads, window_size=7, sh...
    method calculate_mask (line 244) | def calculate_mask(self, x_size):
    method forward (line 267) | def forward(self, x, x_size):
    method extra_repr (line 308) | def extra_repr(self) -> str:
    method flops (line 311) | def flops(self):
  class PatchMerging (line 325) | class PatchMerging(nn.Module):
    method __init__ (line 333) | def __init__(self, input_resolution, dim, norm_layer=nn.LayerNorm):
    method forward (line 340) | def forward(self, x):
    method extra_repr (line 363) | def extra_repr(self) -> str:
    method flops (line 366) | def flops(self):
  class BasicLayer (line 372) | class BasicLayer(nn.Module):
    method __init__ (line 391) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
    method forward (line 421) | def forward(self, x, x_size):
    method extra_repr (line 431) | def extra_repr(self) -> str:
    method flops (line 434) | def flops(self):
    method _init_respostnorm (line 442) | def _init_respostnorm(self):
  class PatchEmbed (line 449) | class PatchEmbed(nn.Module):
    method __init__ (line 459) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 478) | def forward(self, x):
    method flops (line 488) | def flops(self):
  class RSTB (line 495) | class RSTB(nn.Module):
    method __init__ (line 517) | def __init__(self, dim, input_resolution, depth, num_heads, window_size,
    method forward (line 556) | def forward(self, x, x_size):
    method flops (line 559) | def flops(self):
  class PatchUnEmbed (line 569) | class PatchUnEmbed(nn.Module):
    method __init__ (line 580) | def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=9...
    method forward (line 593) | def forward(self, x, x_size):
    method flops (line 598) | def flops(self):
  class Upsample (line 603) | class Upsample(nn.Sequential):
    method __init__ (line 611) | def __init__(self, scale, num_feat):
  class Upsample_hf (line 624) | class Upsample_hf(nn.Sequential):
    method __init__ (line 632) | def __init__(self, scale, num_feat):
  class UpsampleOneStep (line 646) | class UpsampleOneStep(nn.Sequential):
    method __init__ (line 656) | def __init__(self, scale, num_feat, num_out_ch, input_resolution=None):
    method flops (line 664) | def flops(self):
  class Swin2SR (line 671) | class Swin2SR(nn.Module):
    method __init__ (line 698) | def __init__(self, img_size=64, patch_size=1, in_chans=3,
    method _init_weights (line 868) | def _init_weights(self, m):
    method no_weight_decay (line 878) | def no_weight_decay(self):
    method no_weight_decay_keywords (line 882) | def no_weight_decay_keywords(self):
    method check_image_size (line 885) | def check_image_size(self, x):
    method forward_features (line 892) | def forward_features(self, x):
    method forward_features_hf (line 907) | def forward_features_hf(self, x):
    method forward (line 922) | def forward(self, x):
    method flops (line 990) | def flops(self):

FILE: modules/postprocess/vqgan_arch.py
  function normalize (line 14) | def normalize(in_channels):
  function swish (line 19) | def swish(x):
  class VectorQuantizer (line 24) | class VectorQuantizer(nn.Module):
    method __init__ (line 25) | def __init__(self, codebook_size, emb_dim, beta):
    method forward (line 33) | def forward(self, z):
    method get_codebook_feat (line 73) | def get_codebook_feat(self, indices, shape):
  class GumbelQuantizer (line 88) | class GumbelQuantizer(nn.Module):
    method __init__ (line 89) | def __init__(self, codebook_size, emb_dim, num_hiddens, straight_throu...
    method forward (line 99) | def forward(self, z):
  class Downsample (line 118) | class Downsample(nn.Module):
    method __init__ (line 119) | def __init__(self, in_channels):
    method forward (line 123) | def forward(self, x):
  class Upsample (line 130) | class Upsample(nn.Module):
    method __init__ (line 131) | def __init__(self, in_channels):
    method forward (line 135) | def forward(self, x):
  class ResBlock (line 142) | class ResBlock(nn.Module):
    method __init__ (line 143) | def __init__(self, in_channels, out_channels=None):
    method forward (line 154) | def forward(self, x_in):
  class AttnBlock (line 168) | class AttnBlock(nn.Module):
    method __init__ (line 169) | def __init__(self, in_channels):
    method forward (line 203) | def forward(self, x):
  class Encoder (line 230) | class Encoder(nn.Module):
    method __init__ (line 231) | def __init__(self, in_channels, nf, emb_dim, ch_mult, num_res_blocks, ...
    method forward (line 270) | def forward(self, x):
  class Generator (line 277) | class Generator(nn.Module):
    method __init__ (line 278) | def __init__(self, nf, emb_dim, ch_mult, res_blocks, img_size, attn_re...
    method forward (line 320) | def forward(self, x):
  class VQAutoEncoder (line 328) | class VQAutoEncoder(nn.Module):
    method __init__ (line 329) | def __init__(self, img_size, nf, ch_mult, quantizer="nearest", res_blo...
    method forward (line 386) | def forward(self, x):
  class VQGANDiscriminator (line 396) | class VQGANDiscriminator(nn.Module):
    method __init__ (line 397) | def __init__(self, nc=3, ndf=64, n_layers=4, model_path=None):
    method forward (line 434) | def forward(self, x):

FILE: modules/postprocess/yolo.py
  class YoloResult (line 32) | class YoloResult:
    method __init__ (line 33) | def __init__(self, cls: int, label: str, score: float, box: list[int],...
    method __repl__ (line 44) | def __repl__(self):
  class YoloRestorer (line 48) | class YoloRestorer(Detailer):
    method __init__ (line 49) | def __init__(self):
    method name (line 57) | def name(self):
    method enumerate (line 60) | def enumerate(self):
    method dependencies (line 78) | def dependencies(self):
    method predict (line 82) | def predict(
    method load (line 186) | def load(self, model_name: str = None):
    method merge (line 224) | def merge(self, items: list[YoloResult]) -> list[YoloResult]:
    method draw_masks (line 243) | def draw_masks(self, image: Image.Image, items: list[YoloResult]) -> I...
    method restore (line 269) | def restore(self, np_image, p: processing.StableDiffusionProcessing = ...
    method change_mode (line 470) | def change_mode(self, dropdown, text):
    method ui (line 479) | def ui(self, tab: str):
  function initialize (line 563) | def initialize():

FILE: modules/postprocessing.py
  function run_postprocessing (line 12) | def run_postprocessing(extras_mode, image, image_folder: List[tempfile.N...
  function run_extras (line 103) | def run_extras(extras_mode, resize_mode, image, image_folder, input_dir,...

FILE: modules/processing.py
  class Processed (line 33) | class Processed:
    method __init__ (line 34) | def __init__(self, p: StableDiffusionProcessing, images_list, seed=-1,...
    method js (line 88) | def js(self):
    method infotext (line 121) | def infotext(self, p: StableDiffusionProcessing, index):
    method __str___ (line 124) | def __str___(self):
  function get_processed (line 128) | def get_processed(*args, **kwargs):
  function process_images (line 134) | def process_images(p: StableDiffusionProcessing) -> Processed:
  function process_init (line 242) | def process_init(p: StableDiffusionProcessing):
  function process_samples (line 278) | def process_samples(p: StableDiffusionProcessing, samples):
  function process_images_inner (line 390) | def process_images_inner(p: StableDiffusionProcessing) -> Processed:

FILE: modules/processing_args.py
  function task_modular_kwargs (line 22) | def task_modular_kwargs(p, model): # pylint: disable=unused-argument
  function task_specific_kwargs (line 42) | def task_specific_kwargs(p, model):
  function get_params (line 178) | def get_params(model):
  function set_pipeline_args (line 188) | def set_pipeline_args(p, model, prompts:list, negative_prompts:list, pro...

FILE: modules/processing_callbacks.py
  function set_callbacks_p (line 15) | def set_callbacks_p(processing):
  function prompt_callback (line 21) | def prompt_callback(step, kwargs):
  function diffusers_callback_legacy (line 36) | def diffusers_callback_legacy(step: int, timestep: int, latents: typing....
  function diffusers_callback (line 54) | def diffusers_callback(pipe, step: int = 0, timestep: int = 0, kwargs: d...

FILE: modules/processing_class.py
  class StableDiffusionProcessing (line 17) | class StableDiffusionProcessing:
    method __init__ (line 18) | def __init__(self,
    method __repr__ (line 388) | def __repr__(self):
    method sd_model (line 392) | def sd_model(self):
    method scripts (line 396) | def scripts(self):
    method scripts (line 400) | def scripts(self, value):
    method script_args (line 406) | def script_args(self):
    method script_args (line 410) | def script_args(self, value):
    method setup_scripts (line 415) | def setup_scripts(self):
    method comment (line 419) | def comment(self, text):
    method init (line 422) | def init(self, all_prompts=None, all_seeds=None, all_subseeds=None):
    method close (line 425) | def close(self):
  class StableDiffusionProcessingVideo (line 430) | class StableDiffusionProcessingVideo(StableDiffusionProcessing):
    method __init__ (line 431) | def __init__(self, **kwargs):
  class StableDiffusionProcessingTxt2Img (line 441) | class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
    method __init__ (line 442) | def __init__(self, **kwargs):
    method init (line 446) | def init(self, all_prompts=None, all_seeds=None, all_subseeds=None):
    method init_hr (line 457) | def init_hr(self, scale = None, upscaler = None, force = False): # pyl...
  class StableDiffusionProcessingImg2Img (line 476) | class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
    method __init__ (line 477) | def __init__(self, **kwargs):
    method init (line 481) | def init(self, all_prompts=None, all_seeds=None, all_subseeds=None):
  class StableDiffusionProcessingControl (line 573) | class StableDiffusionProcessingControl(StableDiffusionProcessingImg2Img):
    method __init__ (line 574) | def __init__(self, **kwargs):
    method init_hr (line 578) | def init_hr(self, scale:float=None, upscaler:str=None, force:bool=False):
  function switch_class (line 596) | def switch_class(p: StableDiffusionProcessing, new_class: type, dct: dic...

FILE: modules/processing_correction.py
  function warn_once (line 19) | def warn_once(message):
  function sharpen_tensor (line 26) | def sharpen_tensor(tensor, ratio=0):
  function soft_clamp_tensor (line 41) | def soft_clamp_tensor(tensor, threshold=0.8, boundary=4):
  function center_tensor (line 58) | def center_tensor(tensor, channel_shift=0.0, full_shift=0.0, offset=0.0):
  function maximize_tensor (line 69) | def maximize_tensor(tensor, boundary=1.0):
  function get_color (line 81) | def get_color(colorstr):
  function color_adjust (line 88) | def color_adjust(tensor, colorstr, ratio):
  function correction (line 96) | def correction(p, timestep, latent):
  function correction_callback (line 121) | def correction_callback(p, timestep, kwargs, initial: bool = False):

FILE: modules/processing_diffusers.py
  function restore_state (line 21) | def restore_state(p: processing.StableDiffusionProcessing):
  function process_pre (line 70) | def process_pre(p: processing.StableDiffusionProcessing):
  function process_post (line 113) | def process_post(p: processing.StableDiffusionProcessing):
  function process_base (line 133) | def process_base(p: processing.StableDiffusionProcessing):
  function process_hires (line 237) | def process_hires(p: processing.StableDiffusionProcessing, output):
  function process_refine (line 352) | def process_refine(p: processing.StableDiffusionProcessing, output):
  function process_decode (line 438) | def process_decode(p: processing.StableDiffusionProcessing, output):
  function update_pipeline (line 496) | def update_pipeline(sd_model, p: processing.StableDiffusionProcessing):
  function validate_pipeline (line 512) | def validate_pipeline(p: processing.StableDiffusionProcessing):
  function process_diffusers (line 533) | def process_diffusers(p: processing.StableDiffusionProcessing):

FILE: modules/processing_helpers.py
  function is_modular (line 20) | def is_modular():
  function is_txt2img (line 24) | def is_txt2img():
  function is_refiner_enabled (line 28) | def is_refiner_enabled(p):
  function setup_color_correction (line 32) | def setup_color_correction(image):
  function apply_color_correction (line 38) | def apply_color_correction(correction, original_image):
  function apply_overlay (line 50) | def apply_overlay(image: Image, paste_loc, index, overlays):
  function create_binary_mask (line 75) | def create_binary_mask(image):
  function images_tensor_to_samples (line 83) | def images_tensor_to_samples(image, approximation=None, model=None): # p...
  function get_sampler_name (line 99) | def get_sampler_name(sampler_index: int, img: bool = False) -> str:
  function get_sampler_index (line 112) | def get_sampler_index(sampler_name: str) -> int:
  function slerp (line 121) | def slerp(val, lo, hi): # from https://discuss.pytorch.org/t/help-regard...
  function slerp_alt (line 140) | def slerp_alt(val, lo, hi): # from https://discuss.pytorch.org/t/help-re...
  function create_random_tensors (line 159) | def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=...
  function decode_first_stage (line 208) | def decode_first_stage(model, x):
  function get_fixed_seed (line 229) | def get_fixed_seed(seed):
  function fix_seed (line 236) | def fix_seed(p):
  function old_hires_fix_first_pass_dimensions (line 251) | def old_hires_fix_first_pass_dimensions(width, height):
  function validate_sample (line 261) | def validate_sample(tensor):
  function decode_images (line 293) | def decode_images(image):
  function resize_init_images (line 322) | def resize_init_images(p):
  function resize_hires (line 352) | def resize_hires(p, latents): # input=latents output=pil if not latent_u...
  function calculate_base_steps (line 385) | def calculate_base_steps(p, use_denoise_start, use_refiner_start):
  function calculate_hires_steps (line 410) | def calculate_hires_steps(p):
  function calculate_refiner_steps (line 426) | def calculate_refiner_steps(p):
  function get_generator (line 443) | def get_generator(p):
  function set_latents (line 462) | def set_latents(p):
  function apply_circular (line 476) | def apply_circular(enable: bool, model):
  function save_intermediate (line 497) | def save_intermediate(p, latents, suffix):
  function update_sampler (line 506) | def update_sampler(p, sd_model, second_pass=False):
  function get_job_name (line 533) | def get_job_name(p, model):

FILE: modules/processing_info.py
  function get_last_args (line 12) | def get_last_args():
  function create_infotext (line 16) | def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_...

FILE: modules/processing_prompt.py
  function fix_prompt_batch (line 10) | def fix_prompt_batch(p, prompts, negative_prompts, prompts_2, negative_p...
  function fix_prompt_model (line 48) | def fix_prompt_model(cls, prompts, negative_prompts, prompts_2, negative...
  function set_fallback_prompt (line 56) | def set_fallback_prompt(args: dict, possible: list[str], prompts, negati...
  function set_prompt (line 72) | def set_prompt(p,

FILE: modules/processing_vae.py
  function create_latents (line 14) | def create_latents(image, p, dtype=None, device=None):
  function full_vqgan_decode (line 36) | def full_vqgan_decode(latents, model):
  function full_vae_decode (line 88) | def full_vae_decode(latents, model):
  function full_vae_encode (line 183) | def full_vae_encode(image, model):
  function taesd_vae_decode (line 216) | def taesd_vae_decode(latents):
  function taesd_vae_encode (line 231) | def taesd_vae_encode(image):
  function vae_postprocess (line 237) | def vae_postprocess(tensor, model, output_type='np'):
  function vae_decode (line 271) | def vae_decode(latents, model, output_type='np', vae_type='Full', width=...
  function vae_encode (line 335) | def vae_encode(image, model, vae_type='Full'): # pylint: disable=unused-...
  function reprocess (line 359) | def reprocess(gallery):

FILE: modules/progress.py
  function start_task (line 19) | def start_task(id_task):
  function record_results (line 25) | def record_results(id_task, res):
  function finish_task (line 31) | def finish_task(id_task):
  function add_task_to_queue (line 40) | def add_task_to_queue(id_job):
  class ProgressRequest (line 44) | class ProgressRequest(BaseModel):
  class InternalProgressResponse (line 49) | class InternalProgressResponse(BaseModel):
  function api_progress (line 71) | def api_progress(req: ProgressRequest):
  function setup_progress_api (line 130) | def setup_progress_api():

FILE: modules/prompt_parser.py
  function get_learned_conditioning_prompt_schedules (line 87) | def get_learned_conditioning_prompt_schedules(prompts, steps):
  function get_learned_conditioning (line 168) | def get_learned_conditioning(model, prompts, steps):
  function get_multicond_prompt_list (line 200) | def get_multicond_prompt_list(prompts):
  class ComposableScheduledPromptConditioning (line 221) | class ComposableScheduledPromptConditioning:
    method __init__ (line 222) | def __init__(self, schedules, weight=1.0):
  class MulticondLearnedConditioning (line 227) | class MulticondLearnedConditioning:
    method __init__ (line 228) | def __init__(self, shape, batch):
  function get_multicond_learned_conditioning (line 233) | def get_multicond_learned_conditioning(model, prompts, steps) -> Multico...
  function reconstruct_cond_batch (line 246) | def reconstruct_cond_batch(c: List[List[ScheduledPromptConditioning]], c...
  function reconstruct_multicond_batch (line 259) | def reconstruct_multicond_batch(c: MulticondLearnedConditioning, current...
  function parse_prompt_attention (line 284) | def parse_prompt_attention(text):

FILE: modules/prompt_parser_diffusers.py
  function prompt_compatible (line 23) | def prompt_compatible(pipe = None):
  function prepare_model (line 38) | def prepare_model(pipe = None):
  class PromptEmbedder (line 50) | class PromptEmbedder:
    method __init__ (line 51) | def __init__(self,
    method checkcache (line 108) | def checkcache(self, p) -> bool:
    method compare_prompts (line 162) | def compare_prompts(self):
    method prepare_schedule (line 169) | def prepare_schedule(self, prompt, negative_prompt):
    method scheduled_encode (line 175) | def scheduled_encode(self, pipe, batchidx):
    method extend_embeds (line 188) | def extend_embeds(self, batchidx, idx):  # Extends scheduled prompt vi...
    method encode (line 202) | def encode(self, pipe, positive_prompt, negative_prompt, batchidx):
    method clone_embeds (line 247) | def clone_embeds(self, batchidx, idx):
    method __call__ (line 264) | def __call__(self, key, step=0):
  function compel_hijack (line 303) | def compel_hijack(self, token_ids: torch.Tensor, attention_mask: typing....
  function sd3_compel_hijack (line 326) | def sd3_compel_hijack(self, token_ids: torch.Tensor, attention_mask: typ...
  function insert_parser_highjack (line 334) | def insert_parser_highjack(pipename):
  class DiffusersTextualInversionManager (line 347) | class DiffusersTextualInversionManager(BaseTextualInversionManager):
    method __init__ (line 348) | def __init__(self, pipe, tokenizer):
    method maybe_convert_prompt (line 356) | def maybe_convert_prompt(self, prompt: typing.Union[str, typing.List[s...
    method _maybe_convert_prompt (line 363) | def _maybe_convert_prompt(self, prompt: str, tokenizer: PreTrainedToke...
    method expand_textual_inversion_token_ids_if_necessary (line 381) | def expand_textual_inversion_token_ids_if_necessary(self, token_ids: t...
  function get_prompt_schedule (line 390) | def get_prompt_schedule(prompt, steps):
  function get_tokens (line 402) | def get_tokens(pipe, msg, prompt):
  function normalize_prompt (line 449) | def normalize_prompt(pairs: list):
  function get_prompts_with_weights (line 466) | def get_prompts_with_weights(pipe, prompt: str):
  function prepare_embedding_providers (line 499) | def prepare_embedding_providers(pipe, clip_skip) -> list[EmbeddingsProvi...
  function pad_to_same_length (line 537) | def pad_to_same_length(pipe, embeds, empty_embedding_providers=None):
  function split_prompts (line 562) | def split_prompts(pipe, prompt, SD3 = False):
  function get_weighted_text_embeddings (line 595) | def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str...
  function get_xhinker_text_embeddings (line 746) | def get_xhinker_text_embeddings(pipe, prompt: str = "", neg_prompt: str ...

FILE: modules/prompt_parser_xhinker.py
  function get_prompts_tokens_with_weights (line 30) | def get_prompts_tokens_with_weights(
  function get_prompts_tokens_with_weights_t5 (line 90) | def get_prompts_tokens_with_weights_t5(
  function group_tokens_and_weights (line 128) | def group_tokens_and_weights(
  function get_weighted_text_embeddings_sd15 (line 185) | def get_weighted_text_embeddings_sd15(
  function get_weighted_text_embeddings_sdxl (line 321) | def get_weighted_text_embeddings_sdxl(
  function get_weighted_text_embeddings_sdxl_refiner (line 577) | def get_weighted_text_embeddings_sdxl_refiner(
  function get_weighted_text_embeddings_sdxl_2p (line 757) | def get_weighted_text_embeddings_sdxl_2p(
  function get_weighted_text_embeddings_sd3 (line 1035) | def get_weighted_text_embeddings_sd3(
  function get_weighted_text_embeddings_flux1 (line 1348) | def get_weighted_text_embeddings_flux1(
  function get_weighted_text_embeddings_chroma (line 1434) | def get_weighted_text_embeddings_chroma(
  function get_weighted_prompt_embeds_with_attention_mask_chroma (line 1501) | def get_weighted_prompt_embeds_with_attention_mask_chroma(
  function pad_prompt_tokens_to_length_chroma (line 1519) | def pad_prompt_tokens_to_length_chroma(pipe, input_tokens, input_weights...

FILE: modules/ras/__init__.py
  function apply (line 7) | def apply(pipe, p: processing.StableDiffusionProcessing):
  function unapply (line 30) | def unapply(pipe):

FILE: modules/ras/ras_attention.py
  class RASLuminaAttnProcessor2_0 (line 23) | class RASLuminaAttnProcessor2_0:
    method __init__ (line 29) | def __init__(self):
    method __call__ (line 36) | def __call__(
  class RASJointAttnProcessor2_0 (line 153) | class RASJointAttnProcessor2_0:
    method __init__ (line 156) | def __init__(self):
    method __call__ (line 163) | def __call__(

FILE: modules/ras/ras_forward.py
  function ras_forward (line 22) | def ras_forward(

FILE: modules/ras/ras_manager.py
  class ras_manager (line 1) | class ras_manager:
    method __init__ (line 2) | def __init__(self):
    method __str__ (line 33) | def __str__(self):
    method set_parameters (line 36) | def set_parameters(self, args):
    method generate_skip_token_list (line 52) | def generate_skip_token_list(self):
    method reset_cache (line 76) | def reset_cache(self):
    method increase_step (line 93) | def increase_step(self):

FILE: modules/ras/ras_scheduler.py
  class RASFlowMatchEulerDiscreteSchedulerOutput (line 30) | class RASFlowMatchEulerDiscreteSchedulerOutput(BaseOutput):
  class RASFlowMatchEulerDiscreteScheduler (line 43) | class RASFlowMatchEulerDiscreteScheduler(FlowMatchEulerDiscreteScheduler):
    method __init__ (line 64) | def __init__(
    method _init_ras_config (line 87) | def _init_ras_config(self, latents):
    method extract_latents_index_from_patched_latents_index (line 90) | def extract_latents_index_from_patched_latents_index(self, indices, he...
    method ras_selection (line 95) | def ras_selection(self, sample, diff, height, width):
    method step (line 120) | def step(

FILE: modules/res4lyf/abnorsett_scheduler.py
  class ABNorsettScheduler (line 29) | class ABNorsettScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 38) | def __init__(
    method step_index (line 90) | def step_index(self) -> Optional[int]:
    method begin_index (line 94) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 97) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 100) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 171) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 177) | def add_noise(
    method scale_model_input (line 186) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 195) | def step(
    method _init_step_index (line 331) | def _init_step_index(self, timestep):
    method __len__ (line 339) | def __len__(self):

FILE: modules/res4lyf/bong_tangent_scheduler.py
  class BongTangentScheduler (line 27) | class BongTangentScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 36) | def __init__(
    method step_index (line 89) | def step_index(self) -> Optional[int]:
    method begin_index (line 93) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 96) | def set_begin_index(self, begin_index: int = 0) -> None:
    method scale_model_input (line 99) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method set_timesteps (line 108) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 198) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 204) | def add_noise(
    method _get_bong_tangent_sigmas (line 213) | def _get_bong_tangent_sigmas(self, steps: int, slope: float, pivot: in...
    method step (line 228) | def step(
    method _init_step_index (line 269) | def _init_step_index(self, timestep):
    method __len__ (line 277) | def __len__(self):

FILE: modules/res4lyf/common_sigma_scheduler.py
  class CommonSigmaScheduler (line 28) | class CommonSigmaScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 37) | def __init__(
    method step_index (line 91) | def step_index(self) -> Optional[int]:
    method begin_index (line 95) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 98) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 101) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 188) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 194) | def add_noise(
    method scale_model_input (line 203) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 212) | def step(
    method _init_step_index (line 254) | def _init_step_index(self, timestep):
    method __len__ (line 262) | def __len__(self):

FILE: modules/res4lyf/deis_scheduler_alt.py
  function get_def_integral_2 (line 11) | def get_def_integral_2(a, b, start, end, c):
  function get_def_integral_3 (line 16) | def get_def_integral_3(a, b, c, start, end, d):
  class RESDEISMultistepScheduler (line 21) | class RESDEISMultistepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 30) | def __init__(
    method set_timesteps (line 87) | def set_timesteps(
    method step_index (line 212) | def step_index(self):
    method index_for_timestep (line 218) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 224) | def _init_step_index(self, timestep):
    method scale_model_input (line 228) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 236) | def step(
    method add_noise (line 393) | def add_noise(
    method __len__ (line 402) | def __len__(self):

FILE: modules/res4lyf/etdrk_scheduler.py
  class ETDRKScheduler (line 29) | class ETDRKScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 38) | def __init__(
    method step_index (line 90) | def step_index(self) -> Optional[int]:
    method begin_index (line 94) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 97) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 100) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 159) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 165) | def add_noise(
    method scale_model_input (line 174) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 183) | def step(
    method _init_step_index (line 276) | def _init_step_index(self, timestep):
    method __len__ (line 284) | def __len__(self):

FILE: modules/res4lyf/gauss_legendre_scheduler.py
  class GaussLegendreScheduler (line 9) | class GaussLegendreScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 19) | def __init__(
    method _get_tableau (line 72) | def _get_tableau(self):
    method set_timesteps (line 147) | def set_timesteps(
    method step_index (line 233) | def step_index(self):
    method index_for_timestep (line 239) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 245) | def _init_step_index(self, timestep):
    method scale_model_input (line 251) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 259) | def step(
    method add_noise (line 374) | def add_noise(
    method __len__ (line 383) | def __len__(self):

FILE: modules/res4lyf/langevin_dynamics_scheduler.py
  class LangevinDynamicsScheduler (line 28) | class LangevinDynamicsScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 37) | def __init__(
    method step_index (line 88) | def step_index(self) -> Optional[int]:
    method begin_index (line 92) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 95) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 98) | def set_timesteps(
    method index_for_timestep (line 175) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 181) | def add_noise(
    method scale_model_input (line 190) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 199) | def step(
    method _init_step_index (line 240) | def _init_step_index(self, timestep):
    method __len__ (line 248) | def __len__(self):

FILE: modules/res4lyf/lawson_scheduler.py
  class LawsonScheduler (line 27) | class LawsonScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 36) | def __init__(
    method step_index (line 88) | def step_index(self) -> Optional[int]:
    method begin_index (line 92) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 95) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 98) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 157) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 163) | def add_noise(
    method scale_model_input (line 172) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 181) | def step(
    method _init_step_index (line 268) | def _init_step_index(self, timestep):
    method __len__ (line 276) | def __len__(self):

FILE: modules/res4lyf/linear_rk_scheduler.py
  class LinearRKScheduler (line 9) | class LinearRKScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 19) | def __init__(
    method _get_tableau (line 72) | def _get_tableau(self):
    method set_timesteps (line 103) | def set_timesteps(
    method step_index (line 189) | def step_index(self):
    method index_for_timestep (line 195) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 201) | def _init_step_index(self, timestep):
    method scale_model_input (line 207) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 215) | def step(
    method add_noise (line 311) | def add_noise(
    method __len__ (line 320) | def __len__(self):

FILE: modules/res4lyf/lobatto_scheduler.py
  class LobattoScheduler (line 10) | class LobattoScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 20) | def __init__(
    method _get_tableau (line 73) | def _get_tableau(self):
    method set_timesteps (line 103) | def set_timesteps(
    method step_index (line 189) | def step_index(self):
    method index_for_timestep (line 195) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 201) | def _init_step_index(self, timestep):
    method scale_model_input (line 207) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 215) | def step(
    method add_noise (line 311) | def add_noise(
    method __len__ (line 320) | def __len__(self):

FILE: modules/res4lyf/pec_scheduler.py
  class PECScheduler (line 29) | class PECScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 38) | def __init__(
    method step_index (line 90) | def step_index(self) -> Optional[int]:
    method begin_index (line 94) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 97) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 100) | def set_timesteps(
    method index_for_timestep (line 165) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 171) | def add_noise(
    method scale_model_input (line 180) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 188) | def step(
    method _init_step_index (line 268) | def _init_step_index(self, timestep):
    method __len__ (line 274) | def __len__(self):

FILE: modules/res4lyf/phi_functions.py
  function calculate_gamma (line 27) | def calculate_gamma(c2: float, c3: float) -> float:
  function _torch_factorial (line 32) | def _torch_factorial(n: int) -> float:
  function phi_standard_torch (line 36) | def phi_standard_torch(j: int, neg_h: torch.Tensor) -> torch.Tensor:
  function phi_mpmath_series (line 70) | def phi_mpmath_series(j: int, neg_h: float) -> float:
  class Phi (line 86) | class Phi:
    method __init__ (line 92) | def __init__(self, h: torch.Tensor, c: List[Union[float, mpf]], analyt...
    method __call__ (line 105) | def __call__(self, j: int, i: int = -1) -> Union[float, torch.Tensor]:

FILE: modules/res4lyf/radau_iia_scheduler.py
  class RadauIIAScheduler (line 10) | class RadauIIAScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 20) | def __init__(
    method _get_tableau (line 73) | def _get_tableau(self):
    method set_timesteps (line 137) | def set_timesteps(
    method step_index (line 223) | def step_index(self):
    method index_for_timestep (line 229) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method scale_model_input (line 241) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method _init_step_index (line 251) | def _init_step_index(self, timestep):
    method step (line 257) | def step(
    method add_noise (line 354) | def add_noise(
    method __len__ (line 363) | def __len__(self):

FILE: modules/res4lyf/res_multistep_scheduler.py
  class RESMultistepScheduler (line 29) | class RESMultistepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 56) | def __init__(
    method step_index (line 105) | def step_index(self) -> Optional[int]:
    method begin_index (line 109) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 112) | def set_begin_index(self, begin_index: int = 0) -> None:
    method scale_model_input (line 115) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method set_timesteps (line 123) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 193) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 199) | def add_noise(
    method step (line 208) | def step(
    method _get_res_coefficients (line 383) | def _get_res_coefficients(self, rk_type, h, c2, c3):
    method _get_deis_coefficients (line 402) | def _get_deis_coefficients(self, order, sigma, sigma_next):
    method _init_step_index (line 444) | def _init_step_index(self, timestep):
    method __len__ (line 450) | def __len__(self):

FILE: modules/res4lyf/res_multistep_sde_scheduler.py
  class RESMultistepSDEScheduler (line 28) | class RESMultistepSDEScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 45) | def __init__(
    method step_index (line 95) | def step_index(self) -> Optional[int]:
    method begin_index (line 99) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 102) | def set_begin_index(self, begin_index: int = 0) -> None:
    method scale_model_input (line 105) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method set_timesteps (line 114) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 173) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 179) | def add_noise(
    method step (line 188) | def step(
    method _get_res_coefficients (line 301) | def _get_res_coefficients(self, rk_type, h, c2, c3):
    method _init_step_index (line 321) | def _init_step_index(self, timestep):
    method __len__ (line 329) | def __len__(self):

FILE: modules/res4lyf/res_singlestep_scheduler.py
  class RESSinglestepScheduler (line 27) | class RESSinglestepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 36) | def __init__(
    method step_index (line 81) | def step_index(self) -> Optional[int]:
    method begin_index (line 85) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 88) | def set_begin_index(self, begin_index: int = 0) -> None:
    method scale_model_input (line 91) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method set_timesteps (line 99) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 168) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 174) | def add_noise(
    method step (line 183) | def step(
    method _init_step_index (line 236) | def _init_step_index(self, timestep):
    method __len__ (line 242) | def __len__(self):

FILE: modules/res4lyf/res_singlestep_sde_scheduler.py
  class RESSinglestepSDEScheduler (line 28) | class RESSinglestepSDEScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 37) | def __init__(
    method step_index (line 83) | def step_index(self) -> Optional[int]:
    method begin_index (line 87) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 90) | def set_begin_index(self, begin_index: int = 0) -> None:
    method scale_model_input (line 93) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method set_timesteps (line 102) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 158) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 164) | def add_noise(
    method step (line 173) | def step(
    method _init_step_index (line 230) | def _init_step_index(self, timestep):
    method __len__ (line 236) | def __len__(self):

FILE: modules/res4lyf/res_unified_scheduler.py
  class RESUnifiedScheduler (line 11) | class RESUnifiedScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 22) | def __init__(
    method set_sigmas (line 72) | def set_sigmas(self, sigmas: torch.Tensor):
    method step_index (line 77) | def step_index(self) -> Optional[int]:
    method begin_index (line 81) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 84) | def set_begin_index(self, begin_index: int = 0) -> None:
    method scale_model_input (line 87) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method set_timesteps (line 95) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 165) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 171) | def add_noise(
    method _get_coefficients (line 180) | def _get_coefficients(self, sigma, sigma_next):
    method step (line 236) | def step(
    method _init_step_index (line 333) | def _init_step_index(self, timestep):
    method __len__ (line 341) | def __len__(self):

FILE: modules/res4lyf/riemannian_flow_scheduler.py
  class RiemannianFlowScheduler (line 27) | class RiemannianFlowScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 36) | def __init__(
    method step_index (line 87) | def step_index(self) -> Optional[int]:
    method begin_index (line 91) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 94) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 97) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 190) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 196) | def add_noise(
    method scale_model_input (line 205) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 214) | def step(
    method _init_step_index (line 255) | def _init_step_index(self, timestep):
    method __len__ (line 263) | def __len__(self):

FILE: modules/res4lyf/rungekutta_44s_scheduler.py
  class RungeKutta44Scheduler (line 9) | class RungeKutta44Scheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 20) | def __init__(
    method set_timesteps (line 72) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method step_index (line 125) | def step_index(self):
    method index_for_timestep (line 131) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 139) | def _init_step_index(self, timestep):
    method scale_model_input (line 144) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 152) | def step(
    method add_noise (line 241) | def add_noise(
    method __len__ (line 250) | def __len__(self):

FILE: modules/res4lyf/rungekutta_57s_scheduler.py
  class RungeKutta57Scheduler (line 9) | class RungeKutta57Scheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 18) | def __init__(
    method set_timesteps (line 72) | def set_timesteps(
    method step_index (line 163) | def step_index(self):
    method index_for_timestep (line 169) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 175) | def _init_step_index(self, timestep):
    method scale_model_input (line 181) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 189) | def step(
    method add_noise (line 289) | def add_noise(
    method __len__ (line 298) | def __len__(self):

FILE: modules/res4lyf/rungekutta_67s_scheduler.py
  class RungeKutta67Scheduler (line 9) | class RungeKutta67Scheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 19) | def __init__(
    method set_timesteps (line 72) | def set_timesteps(
    method step_index (line 162) | def step_index(self):
    method index_for_timestep (line 168) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 174) | def _init_step_index(self, timestep):
    method scale_model_input (line 180) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 188) | def step(
    method add_noise (line 291) | def add_noise(
    method __len__ (line 300) | def __len__(self):

FILE: modules/res4lyf/scheduler_utils.py
  function betas_for_alpha_bar (line 13) | def betas_for_alpha_bar(
  function rescale_zero_terminal_snr (line 40) | def rescale_zero_terminal_snr(betas: torch.Tensor) -> torch.Tensor:
  function get_sigmas_karras (line 54) | def get_sigmas_karras(n, sigma_min, sigma_max, rho=7.0, device="cpu", dt...
  function get_sigmas_exponential (line 61) | def get_sigmas_exponential(n, sigma_min, sigma_max, device="cpu", dtype:...
  function get_sigmas_beta (line 65) | def get_sigmas_beta(n, sigma_min, sigma_max, alpha=0.6, beta=0.6, device...
  function get_sigmas_flow (line 79) | def get_sigmas_flow(n, sigma_min, sigma_max, device="cpu", dtype: torch....
  function apply_shift (line 84) | def apply_shift(sigmas, shift):
  function get_dynamic_shift (line 87) | def get_dynamic_shift(mu, base_shift, max_shift, base_seq_len, max_seq_l...
  function index_for_timestep (line 92) | def index_for_timestep(timestep, timesteps):
  function add_noise_to_sample (line 108) | def add_noise_to_sample(

FILE: modules/res4lyf/simple_exponential_scheduler.py
  class SimpleExponentialScheduler (line 27) | class SimpleExponentialScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 36) | def __init__(
    method step_index (line 88) | def step_index(self) -> Optional[int]:
    method begin_index (line 92) | def begin_index(self) -> Optional[int]:
    method set_begin_index (line 95) | def set_begin_index(self, begin_index: int = 0) -> None:
    method set_timesteps (line 98) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method index_for_timestep (line 140) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method add_noise (line 146) | def add_noise(
    method scale_model_input (line 155) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 164) | def step(
    method _init_step_index (line 205) | def _init_step_index(self, timestep):
    method __len__ (line 213) | def __len__(self):

FILE: modules/res4lyf/specialized_rk_scheduler.py
  class SpecializedRKScheduler (line 10) | class SpecializedRKScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 20) | def __init__(
    method _get_tableau (line 73) | def _get_tableau(self):
    method set_timesteps (line 107) | def set_timesteps(
    method step_index (line 196) | def step_index(self):
    method index_for_timestep (line 202) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 208) | def _init_step_index(self, timestep):
    method scale_model_input (line 214) | def scale_model_input(self, sample: torch.Tensor, timestep: Union[floa...
    method step (line 222) | def step(
    method add_noise (line 335) | def add_noise(
    method __len__ (line 344) | def __len__(self):

FILE: modules/res4lyf/variants.py
  class RESUnified2MScheduler (line 25) | class RESUnified2MScheduler(RESUnifiedScheduler):
    method __init__ (line 26) | def __init__(self, **kwargs):
  class RESUnified3MScheduler (line 31) | class RESUnified3MScheduler(RESUnifiedScheduler):
    method __init__ (line 32) | def __init__(self, **kwargs):
  class RESUnified2SScheduler (line 37) | class RESUnified2SScheduler(RESUnifiedScheduler):
    method __init__ (line 38) | def __init__(self, **kwargs):
  class RESUnified3SScheduler (line 43) | class RESUnified3SScheduler(RESUnifiedScheduler):
    method __init__ (line 44) | def __init__(self, **kwargs):
  class RESUnified5SScheduler (line 49) | class RESUnified5SScheduler(RESUnifiedScheduler):
    method __init__ (line 50) | def __init__(self, **kwargs):
  class RESUnified6SScheduler (line 55) | class RESUnified6SScheduler(RESUnifiedScheduler):
    method __init__ (line 56) | def __init__(self, **kwargs):
  class DEISUnified1SScheduler (line 61) | class DEISUnified1SScheduler(RESUnifiedScheduler):
    method __init__ (line 62) | def __init__(self, **kwargs):
  class DEISUnified2MScheduler (line 67) | class DEISUnified2MScheduler(RESUnifiedScheduler):
    method __init__ (line 68) | def __init__(self, **kwargs):
  class DEISUnified3MScheduler (line 73) | class DEISUnified3MScheduler(RESUnifiedScheduler):
    method __init__ (line 74) | def __init__(self, **kwargs):
  class RES2MScheduler (line 80) | class RES2MScheduler(RESMultistepScheduler):
    method __init__ (line 81) | def __init__(self, **kwargs):
  class RES3MScheduler (line 86) | class RES3MScheduler(RESMultistepScheduler):
    method __init__ (line 87) | def __init__(self, **kwargs):
  class DEIS2MScheduler (line 92) | class DEIS2MScheduler(RESMultistepScheduler):
    method __init__ (line 93) | def __init__(self, **kwargs):
  class DEIS3MScheduler (line 98) | class DEIS3MScheduler(RESMultistepScheduler):
    method __init__ (line 99) | def __init__(self, **kwargs):
  class RES2MSDEScheduler (line 105) | class RES2MSDEScheduler(RESMultistepSDEScheduler):
    method __init__ (line 106) | def __init__(self, **kwargs):
  class RES3MSDEScheduler (line 111) | class RES3MSDEScheduler(RESMultistepSDEScheduler):
    method __init__ (line 112) | def __init__(self, **kwargs):
  class RES2SScheduler (line 118) | class RES2SScheduler(RESSinglestepScheduler):
    method __init__ (line 119) | def __init__(self, **kwargs):
  class RES3SScheduler (line 124) | class RES3SScheduler(RESSinglestepScheduler):
    method __init__ (line 125) | def __init__(self, **kwargs):
  class RES5SScheduler (line 130) | class RES5SScheduler(RESSinglestepScheduler):
    method __init__ (line 131) | def __init__(self, **kwargs):
  class RES6SScheduler (line 136) | class RES6SScheduler(RESSinglestepScheduler):
    method __init__ (line 137) | def __init__(self, **kwargs):
  class RES2SSDEScheduler (line 143) | class RES2SSDEScheduler(RESSinglestepSDEScheduler):
    method __init__ (line 144) | def __init__(self, **kwargs):
  class RES3SSDEScheduler (line 149) | class RES3SSDEScheduler(RESSinglestepSDEScheduler):
    method __init__ (line 150) | def __init__(self, **kwargs):
  class RES5SSDEScheduler (line 155) | class RES5SSDEScheduler(RESSinglestepSDEScheduler):
    method __init__ (line 156) | def __init__(self, **kwargs):
  class RES6SSDEScheduler (line 161) | class RES6SSDEScheduler(RESSinglestepSDEScheduler):
    method __init__ (line 162) | def __init__(self, **kwargs):
  class ETDRK2Scheduler (line 168) | class ETDRK2Scheduler(ETDRKScheduler):
    method __init__ (line 169) | def __init__(self, **kwargs):
  class ETDRK3AScheduler (line 174) | class ETDRK3AScheduler(ETDRKScheduler):
    method __init__ (line 175) | def __init__(self, **kwargs):
  class ETDRK3BScheduler (line 180) | class ETDRK3BScheduler(ETDRKScheduler):
    method __init__ (line 181) | def __init__(self, **kwargs):
  class ETDRK4Scheduler (line 186) | class ETDRK4Scheduler(ETDRKScheduler):
    method __init__ (line 187) | def __init__(self, **kwargs):
  class ETDRK4AltScheduler (line 192) | class ETDRK4AltScheduler(ETDRKScheduler):
    method __init__ (line 193) | def __init__(self, **kwargs):
  class Lawson2AScheduler (line 199) | class Lawson2AScheduler(LawsonScheduler):
    method __init__ (line 200) | def __init__(self, **kwargs):
  class Lawson2BScheduler (line 205) | class Lawson2BScheduler(LawsonScheduler):
    method __init__ (line 206) | def __init__(self, **kwargs):
  class Lawson4Scheduler (line 211) | class Lawson4Scheduler(LawsonScheduler):
    method __init__ (line 212) | def __init__(self, **kwargs):
  class ABNorsett2MScheduler (line 218) | class ABNorsett2MScheduler(ABNorsettScheduler):
    method __init__ (line 219) | def __init__(self, **kwargs):
  class ABNorsett3MScheduler (line 224) | class ABNorsett3MScheduler(ABNorsettScheduler):
    method __init__ (line 225) | def __init__(self, **kwargs):
  class ABNorsett4MScheduler (line 230) | class ABNorsett4MScheduler(ABNorsettScheduler):
    method __init__ (line 231) | def __init__(self, **kwargs):
  class PEC2H2SScheduler (line 237) | class PEC2H2SScheduler(PECScheduler):
    method __init__ (line 238) | def __init__(self, **kwargs):
  class PEC2H3SScheduler (line 243) | class PEC2H3SScheduler(PECScheduler):
    method __init__ (line 244) | def __init__(self, **kwargs):
  class FlowEuclideanScheduler (line 250) | class FlowEuclideanScheduler(RiemannianFlowScheduler):
    method __init__ (line 251) | def __init__(self, **kwargs):
  class FlowHyperbolicScheduler (line 256) | class FlowHyperbolicScheduler(RiemannianFlowScheduler):
    method __init__ (line 257) | def __init__(self, **kwargs):
  class FlowSphericalScheduler (line 262) | class FlowSphericalScheduler(RiemannianFlowScheduler):
    method __init__ (line 263) | def __init__(self, **kwargs):
  class FlowLorentzianScheduler (line 268) | class FlowLorentzianScheduler(RiemannianFlowScheduler):
    method __init__ (line 269) | def __init__(self, **kwargs):
  class SigmaSigmoidScheduler (line 275) | class SigmaSigmoidScheduler(CommonSigmaScheduler):
    method __init__ (line 276) | def __init__(self, **kwargs):
  class SigmaSineScheduler (line 281) | class SigmaSineScheduler(CommonSigmaScheduler):
    method __init__ (line 282) | def __init__(self, **kwargs):
  class SigmaEasingScheduler (line 287) | class SigmaEasingScheduler(CommonSigmaScheduler):
    method __init__ (line 288) | def __init__(self, **kwargs):
  class SigmaArcsineScheduler (line 293) | class SigmaArcsineScheduler(CommonSigmaScheduler):
    method __init__ (line 294) | def __init__(self, **kwargs):
  class SigmaSmoothScheduler (line 299) | class SigmaSmoothScheduler(CommonSigmaScheduler):
    method __init__ (line 300) | def __init__(self, **kwargs):
  class DEIS1MultistepScheduler (line 305) | class DEIS1MultistepScheduler(RESDEISMultistepScheduler):
    method __init__ (line 306) | def __init__(self, **kwargs):
  class DEIS2MultistepScheduler (line 310) | class DEIS2MultistepScheduler(RESDEISMultistepScheduler):
    method __init__ (line 311) | def __init__(self, **kwargs):
  class DEIS3MultistepScheduler (line 315) | class DEIS3MultistepScheduler(RESDEISMultistepScheduler):
    method __init__ (line 316) | def __init__(self, **kwargs):
  class LinearRKEulerScheduler (line 321) | class LinearRKEulerScheduler(LinearRKScheduler):
    method __init__ (line 322) | def __init__(self, **kwargs):
  class LinearRKHeunScheduler (line 326) | class LinearRKHeunScheduler(LinearRKScheduler):
    method __init__ (line 327) | def __init__(self, **kwargs):
  class LinearRK2Scheduler (line 331) | class LinearRK2Scheduler(LinearRKScheduler):
    method __init__ (line 332) | def __init__(self, **kwargs):
  class LinearRK3Scheduler (line 336) | class LinearRK3Scheduler(LinearRKScheduler):
    method __init__ (line 337) | def __init__(self, **kwargs):
  class LinearRK4Scheduler (line 341) | class LinearRK4Scheduler(LinearRKScheduler):
    method __init__ (line 342) | def __init__(self, **kwargs):
  class LinearRKRalsstonScheduler (line 346) | class LinearRKRalsstonScheduler(LinearRKScheduler):
    method __init__ (line 347) | def __init__(self, **kwargs):
  class LinearRKMidpointScheduler (line 351) | class LinearRKMidpointScheduler(LinearRKScheduler):
    method __init__ (line 352) | def __init__(self, **kwargs):
  class Lobatto2Scheduler (line 357) | class Lobatto2Scheduler(LobattoScheduler):
    method __init__ (line 358) | def __init__(self, **kwargs):
  class Lobatto3Scheduler (line 362) | class Lobatto3Scheduler(LobattoScheduler):
    method __init__ (line 363) | def __init__(self, **kwargs):
  class Lobatto4Scheduler (line 367) | class Lobatto4Scheduler(LobattoScheduler):
    method __init__ (line 368) | def __init__(self, **kwargs):
  class RadauIIA2Scheduler (line 373) | class RadauIIA2Scheduler(RadauIIAScheduler):
    method __init__ (line 374) | def __init__(self, **kwargs):
  class RadauIIA3Scheduler (line 378) | class RadauIIA3Scheduler(RadauIIAScheduler):
    method __init__ (line 379) | def __init__(self, **kwargs):
  class GaussLegendre2SScheduler (line 384) | class GaussLegendre2SScheduler(GaussLegendreScheduler):
    method __init__ (line 385) | def __init__(self, **kwargs):
  class GaussLegendre3SScheduler (line 389) | class GaussLegendre3SScheduler(GaussLegendreScheduler):
    method __init__ (line 390) | def __init__(self, **kwargs):
  class GaussLegendre4SScheduler (line 394) | class GaussLegendre4SScheduler(GaussLegendreScheduler):
    method __init__ (line 395) | def __init__(self, **kwargs):

FILE: modules/rife/__init__.py
  function load (line 22) | def load(model_path: str = 'rife/flownet-v46.pkl'):
  function interpolate (line 35) | def interpolate(images: list, count: int = 2, scale: float = 1.0, pad: i...
  function interpolate_nchw (line 121) | def interpolate_nchw(images: list, count: int = 2, scale: float = 1.0):

FILE: modules/rife/loss.py
  class EPE (line 9) | class EPE(nn.Module):
    method __init__ (line 10) | def __init__(self):
    method forward (line 13) | def forward(self, flow, gt, loss_mask):
  class Ternary (line 19) | class Ternary(nn.Module):
    method __init__ (line 20) | def __init__(self):
    method transform (line 29) | def transform(self, img):
    method rgb2gray (line 35) | def rgb2gray(self, rgb):
    method hamming (line 40) | def hamming(self, t1, t2):
    method valid_mask (line 45) | def valid_mask(self, t, padding):
    method forward (line 51) | def forward(self, img0, img1):
  class SOBEL (line 57) | class SOBEL(nn.Module):
    method __init__ (line 58) | def __init__(self):
    method forward (line 69) | def forward(self, pred, gt):
  class MeanShift (line 82) | class MeanShift(nn.Conv2d):
    method __init__ (line 83) | def __init__(self, data_mean, data_std, data_range=1, norm=True):
  class VGGPerceptualLoss (line 98) | class VGGPerceptualLoss(torch.nn.Module):
    method __init__ (line 99) | def __init__(self, rank=0): # pylint: disable=unused-argument
    method forward (line 108) | def forward(self, X, Y, indices=None):

FILE: modules/rife/model_ifnet.py
  function conv (line 14) | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dila...
  function conv_bn (line 21) | def conv_bn(in_planes, out_planes, kernel_size=3, stride=1, padding=1, d...
  class ResConv (line 29) | class ResConv(nn.Module):
    method __init__ (line 30) | def __init__(self, c, dilation=1):
    method forward (line 37) | def forward(self, x):
  class IFBlock (line 40) | class IFBlock(nn.Module):
    method __init__ (line 41) | def __init__(self, in_planes, c=64):
    method forward (line 62) | def forward(self, x, flow=None, scale=1):
  class IFNet (line 75) | class IFNet(nn.Module):
    method __init__ (line 76) | def __init__(self):
    method forward (line 85) | def forward( self, x, timestep=0.5, scale_list=[8, 4, 2, 1], training=...

FILE: modules/rife/model_rife.py
  class RifeModel (line 9) | class RifeModel:
    method __init__ (line 10) | def __init__(self, local_rank=-1):
    method train (line 21) | def train(self):
    method eval (line 24) | def eval(self):
    method device (line 27) | def device(self):
    method load_model (line 31) | def load_model(self, model_file, rank=0):
    method save_model (line 43) | def save_model(self, model_file, rank=0):
    method inference (line 47) | def inference(self, img0, img1, timestep=0.5, scale=1.0):
    method update (line 53) | def update(self, imgs, gt, learning_rate=0, mul=1, training=True, flow...

FILE: modules/rife/refine.py
  function conv (line 10) | def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dila...
  function conv_woact (line 17) | def conv_woact(in_planes, out_planes, kernel_size=3, stride=1, padding=1...
  function deconv (line 23) | def deconv(in_planes, out_planes, kernel_size=4, stride=2, padding=1): #...
  class Conv2 (line 30) | class Conv2(nn.Module):
    method __init__ (line 31) | def __init__(self, in_planes, out_planes, stride=2):
    method forward (line 36) | def forward(self, x):
  class Contextnet (line 42) | class Contextnet(nn.Module):
    method __init__ (line 43) | def __init__(self):
    method forward (line 50) | def forward(self, x, flow):
  class Unet (line 66) | class Unet(nn.Module):
    method __init__ (line 67) | def __init__(self):
    method forward (line 79) | def forward(self, img0, img1, warped_img0, warped_img1, mask, flow, c0...

FILE: modules/rife/ssim.py
  function gaussian (line 7) | def gaussian(window_size, sigma):
  function create_window (line 12) | def create_window(window_size, channel=1):
  function create_window_3d (line 19) | def create_window_3d(window_size, channel=1):
  function ssim (line 27) | def ssim(img1, img2, window_size=11, window=None, size_average=True, ful...
  function ssim_matlab (line 72) | def ssim_matlab(img1, img2, window_size=11, window=None, size_average=Tr...
  function msssim (line 117) | def msssim(img1, img2, window_size=11, size_average=True, val_range=None...
  class SSIM (line 143) | class SSIM(torch.nn.Module):
    method __init__ (line 144) | def __init__(self, window_size=11, size_average=True, val_range=None):
    method forward (line 153) | def forward(self, img1, img2):
  class MSSSIM (line 166) | class MSSSIM(torch.nn.Module):
    method __init__ (line 167) | def __init__(self, window_size=11, size_average=True, channel=3):
    method forward (line 173) | def forward(self, img1, img2):

FILE: modules/rife/warplayer.py
  function warp (line 8) | def warp(tenInput, tenFlow):

FILE: modules/rocm.py
  function resolve_link (line 18) | def resolve_link(path_: str) -> str:
  function dirname (line 24) | def dirname(path_: str, r: int = 1) -> str:
  function spawn (line 30) | def spawn(command: Union[str, list[str]], cwd: os.PathLike = '.') -> str:
  function load_library_global (line 35) | def load_library_global(path_: str):
  class Environment (line 39) | class Environment:
  class ROCmEnvironment (line 44) | class ROCmEnvironment(Environment):
    method __init__ (line 47) | def __init__(self, path: str):
  class PythonPackageEnvironment (line 52) | class PythonPackageEnvironment(Environment):
    method __init__ (line 55) | def __init__(self, rocm_sdk_module: ModuleType):
  class MicroArchitecture (line 65) | class MicroArchitecture(Enum):
  class Agent (line 71) | class Agent:
    method parse_gfx_version (line 79) | def parse_gfx_version(name: str) -> int:
    method __init__ (line 94) | def __init__(self, name: str): ...
    method __init__ (line 96) | def __init__(self, device: 'torch.types.Device'): ...
    method __init__ (line 98) | def __init__(self, arg):
    method __str__ (line 115) | def __str__(self) -> str:
    method therock (line 119) | def therock(self) -> Union[str, None]:
    method get_gfx_version (line 144) | def get_gfx_version(self) -> Union[str, None]:
  function find (line 156) | def find() -> Union[ROCmEnvironment, None]:
  function get_version (line 208) | def get_version() -> str:
  function get_flash_attention_command (line 230) | def get_flash_attention_command(agent: Agent) -> str:
  function refresh (line 239) | def refresh():
  function get_agents (line 266) | def get_agents() -> list[Agent]:
  function postinstall (line 279) | def postinstall():
  function rocm_init (line 292) | def rocm_init():
  function get_agents (line 344) | def get_agents() -> list[Agent]:
  function postinstall (line 353) | def postinstall():
  function rocm_init (line 365) | def rocm_init():

FILE: modules/rocm_triton_windows.py
  class DeviceProperties (line 37) | class DeviceProperties:
    method __init__ (line 44) | def __init__(self, props: torch._C._CudaDeviceProperties):
    method __getattr__ (line 47) | def __getattr__(self, name):
  function torch_cuda__get_device_properties (line 53) | def torch_cuda__get_device_properties(device):
  function torch__C__cuda_getCurrentRawStream (line 57) | def torch__C__cuda_getCurrentRawStream(device):
  function get_default_agent (line 61) | def get_default_agent() -> Union[Agent, None]:
  function apply_triton_patches (line 68) | def apply_triton_patches():

FILE: modules/safe.py
  function encode (line 16) | def encode(*args):
  class RestrictedUnpickler (line 21) | class RestrictedUnpickler(pickle.Unpickler):
    method persistent_load (line 24) | def persistent_load(self, pid):
    method find_class (line 31) | def find_class(self, module, name):
  function check_zip_filenames (line 68) | def check_zip_filenames(filename, names):
  function check_pt (line 76) | def check_pt(filename, extra_handler):
  function load (line 104) | def load(filename, *args, **kwargs):
  function load_with_extra (line 108) | def load_with_extra(filename, extra_handler=None, *args, **kwargs): # py...
  class Extra (line 142) | class Extra:
    method __init__ (line 162) | def __init__(self, handler):
    method __enter__ (line 165) | def __enter__(self):
    method __exit__ (line 171) | def __exit__(self, exc_type, exc_val, exc_tb):

FILE: modules/schedulers/perflow/pfode_solver.py
  class PFODESolver (line 5) | class PFODESolver():
    method __init__ (line 6) | def __init__(self, scheduler, t_initial=1, t_terminal=0,) -> None:
    method get_timesteps (line 15) | def get_timesteps(self, t_start, t_end, num_steps):
    method solve (line 29) | def solve(self,
  class PFODESolverSDXL (line 121) | class PFODESolverSDXL():
    method __init__ (line 122) | def __init__(self, scheduler, t_initial=1, t_terminal=0,) -> None:
    method get_timesteps (line 132) | def get_timesteps(self, t_start, t_end, num_steps):
    method _get_add_time_ids (line 146) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method solve (line 152) | def solve(self,

FILE: modules/schedulers/perflow/scheduler_perflow.py
  class Time_Windows (line 28) | class Time_Windows():
    method __init__ (line 29) | def __init__(self, t_initial=1, t_terminal=0, num_windows=4, precision...
    method get_window (line 37) | def get_window(self, tp):
    method lookup_window (line 44) | def lookup_window(self, timepoint):
  class PeRFlowSchedulerOutput (line 62) | class PeRFlowSchedulerOutput(BaseOutput):
  function betas_for_alpha_bar (line 80) | def betas_for_alpha_bar(
  class PeRFlowScheduler (line 125) | class PeRFlowScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 156) | def __init__(
    method scale_model_input (line 201) | def scale_model_input(self, sample: torch.FloatTensor, timestep: Optio...
    method set_timesteps (line 219) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method get_window_alpha (line 249) | def get_window_alpha(self, timepoints):
    method step (line 268) | def step(
    method add_noise (line 344) | def add_noise(
    method __len__ (line 367) | def __len__(self):

FILE: modules/schedulers/perflow/utils_perflow.py
  function merge_delta_weights_into_unet (line 10) | def merge_delta_weights_into_unet(pipe, delta_weights):
  function load_delta_weights_into_unet (line 21) | def load_delta_weights_into_unet(
  function load_dreambooth_into_pipeline (line 60) | def load_dreambooth_into_pipeline(pipe, sd_dreambooth):

FILE: modules/schedulers/scheduler_bdia.py
  class DDIMSchedulerOutput (line 33) | class DDIMSchedulerOutput(BaseOutput):
  function betas_for_alpha_bar (line 51) | def betas_for_alpha_bar(
  function rescale_zero_terminal_snr (line 95) | def rescale_zero_terminal_snr(betas):
  class BDIA_DDIMScheduler (line 130) | class BDIA_DDIMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 184) | def __init__(
    method scale_model_input (line 240) | def scale_model_input(self, sample: torch.Tensor, timestep: Optional[i...
    method _get_variance (line 257) | def _get_variance(self, timestep, prev_timestep):
    method _threshold_sample (line 268) | def _threshold_sample(self, sample: torch.Tensor) -> torch.Tensor:
    method set_timesteps (line 301) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method step (line 346) | def step(
    method add_noise (line 500) | def add_noise(
    method get_velocity (line 527) | def get_velocity(self, sample: torch.Tensor, noise: torch.Tensor, time...
    method update_next_sample_BDIA (line 546) | def update_next_sample_BDIA(self, new_value):
    method __len__ (line 550) | def __len__(self):

FILE: modules/schedulers/scheduler_dc.py
  function betas_for_alpha_bar (line 33) | def betas_for_alpha_bar(
  class DCSolverMultistepScheduler (line 77) | class DCSolverMultistepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 143) | def __init__(
    method step_index (line 226) | def step_index(self):
    method set_timesteps (line 232) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method _threshold_sample (line 298) | def _threshold_sample(self, sample: torch.FloatTensor) -> torch.FloatT...
    method _sigma_to_t (line 332) | def _sigma_to_t(self, sigma, log_sigmas):
    method _sigma_to_alpha_sigma_t (line 356) | def _sigma_to_alpha_sigma_t(self, sigma):
    method _convert_to_karras (line 363) | def _convert_to_karras(self, in_sigmas: torch.FloatTensor, num_inferen...
    method convert_model_output (line 376) | def convert_model_output(
    method multistep_uni_p_bh_update (line 447) | def multistep_uni_p_bh_update(
    method multistep_uni_c_bh_update (line 576) | def multistep_uni_c_bh_update(
    method _init_step_index (line 713) | def _init_step_index(self, timestep):
    method dynamic_compensation (line 732) | def dynamic_compensation(self, model_prev_list, t_prev_list, ratio):
    method find_optim_ratio (line 754) | def find_optim_ratio(self, sample, ratio_initial=1.0):
    method cascade_polynomial_regression (line 824) | def cascade_polynomial_regression(self, test_CFG, test_NFE, cpr_path):
    method step (line 862) | def step(self, *args, **kwargs):
    method _step_search (line 869) | def _step_search(
    method _step (line 961) | def _step(
    method scale_model_input (line 1049) | def scale_model_input(self, sample: torch.FloatTensor, *args, **kwargs...
    method add_noise (line 1065) | def add_noise(
    method __len__ (line 1091) | def __len__(self):

FILE: modules/schedulers/scheduler_dpm_flowmatch.py
  class BatchedBrownianTree (line 18) | class BatchedBrownianTree:
    method __init__ (line 21) | def __init__(self, x, t0, t1, seed=None, **kwargs):
    method sort (line 50) | def sort(a, b):
    method __call__ (line 53) | def __call__(self, t0, t1):
  class BrownianTreeNoiseSampler (line 58) | class BrownianTreeNoiseSampler:
    method __init__ (line 73) | def __init__(self, x, sigma_min, sigma_max, seed=None, transform=lambd...
    method __call__ (line 78) | def __call__(self, sigma, sigma_next):
  class FlowMatchDPMSolverMultistepSchedulerOutput (line 83) | class FlowMatchDPMSolverMultistepSchedulerOutput(BaseOutput):
  class FlowMatchDPMSolverMultistepScheduler (line 95) | class FlowMatchDPMSolverMultistepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 147) | def __init__(
    method step_index (line 204) | def step_index(self):
    method begin_index (line 211) | def begin_index(self):
    method set_begin_index (line 217) | def set_begin_index(self, begin_index: int = 0):
    method time_shift (line 227) | def time_shift(self, mu: float, sigma: float, t: torch.FloatTensor):
    method set_timesteps (line 230) | def set_timesteps(self,
    method _convert_to_beta (line 379) | def _convert_to_beta(self, sigma_min, sigma_max, num_inference_steps, ...
    method _convert_to_lu (line 392) | def _convert_to_lu(self, in_lambdas: torch.Tensor, num_inference_steps...
    method _convert_to_karras (line 406) | def _convert_to_karras(self, sigma_min, sigma_max, num_inference_steps...
    method _convert_to_exponential (line 414) | def _convert_to_exponential(self, sigma_min, sigma_max, num_inference_...
    method index_for_timestep (line 418) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 432) | def _init_step_index(self, timestep):
    method step (line 440) | def step(
    method scale_model_input (line 809) | def scale_model_input(self, sample: torch.FloatTensor, *args, **kwargs...
    method scale_noise (line 824) | def scale_noise(
    method __len__ (line 872) | def __len__(self):

FILE: modules/schedulers/scheduler_flashflow.py
  class FlashFlowMatchEulerDiscreteSchedulerOutput (line 33) | class FlashFlowMatchEulerDiscreteSchedulerOutput(BaseOutput):
  class FlashFlowMatchEulerDiscreteScheduler (line 46) | class FlashFlowMatchEulerDiscreteScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 67) | def __init__(
    method step_index (line 107) | def step_index(self):
    method begin_index (line 114) | def begin_index(self):
    method set_begin_index (line 121) | def set_begin_index(self, begin_index: int = 0):
    method scale_noise (line 131) | def scale_noise(
    method _sigma_to_t (line 179) | def _sigma_to_t(self, sigma):
    method time_shift (line 182) | def time_shift(self, mu: float, sigma: float, t: torch.Tensor):
    method set_timesteps (line 185) | def set_timesteps(
    method index_for_timestep (line 244) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 258) | def _init_step_index(self, timestep):
    method scale_model_input (line 266) | def scale_model_input(self, sample: torch.FloatTensor, timestep: Optio...
    method step (line 282) | def step(
    method _convert_to_karras (line 366) | def _convert_to_karras(self, in_sigmas: torch.Tensor, num_inference_st...
    method _convert_to_exponential (line 391) | def _convert_to_exponential(self, in_sigmas: torch.Tensor, num_inferen...
    method _convert_to_beta (line 412) | def _convert_to_beta(
    method __len__ (line 442) | def __len__(self):

FILE: modules/schedulers/scheduler_tcd.py
  class TCDSchedulerOutput (line 38) | class TCDSchedulerOutput(BaseOutput):
  function betas_for_alpha_bar (line 55) | def betas_for_alpha_bar(
  function rescale_zero_terminal_snr (line 100) | def rescale_zero_terminal_snr(betas: torch.FloatTensor) -> torch.FloatTe...
  class TCDScheduler (line 136) | class TCDScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 200) | def __init__(
    method _init_step_index (line 257) | def _init_step_index(self, timestep):
    method step_index (line 275) | def step_index(self):
    method scale_model_input (line 278) | def scale_model_input(self, sample: torch.FloatTensor, timestep: Optio...
    method _get_variance (line 294) | def _get_variance(self, timestep, prev_timestep):
    method _threshold_sample (line 305) | def _threshold_sample(self, sample: torch.FloatTensor) -> torch.FloatT...
    method set_timesteps (line 338) | def set_timesteps(
    method step (line 495) | def step(
    method add_noise (line 598) | def add_noise(
    method get_velocity (line 622) | def get_velocity(
    method __len__ (line 642) | def __len__(self):
    method previous_timestep (line 646) | def previous_timestep(self, timestep):

FILE: modules/schedulers/scheduler_tdd.py
  class TDDScheduler (line 16) | class TDDScheduler(DPMSolverSinglestepScheduler):
    method __init__ (line 18) | def __init__(
    method set_timesteps (line 101) | def set_timesteps(self, num_inference_steps: int, device: Union[str, t...
    method set_timesteps_s (line 173) | def set_timesteps_s(self, eta: float = 0.0):
    method step (line 222) | def step(
    method dpm_solver_first_order_update (line 281) | def dpm_solver_first_order_update(
    method singlestep_dpm_solver_second_order_update (line 320) | def singlestep_dpm_solver_second_order_update(
    method singlestep_dpm_solver_update (line 396) | def singlestep_dpm_solver_update(
    method convert_model_output (line 437) | def convert_model_output(

FILE: modules/schedulers/scheduler_ufogen.py
  class UFOGenSchedulerOutput (line 35) | class UFOGenSchedulerOutput(BaseOutput):
  function betas_for_alpha_bar (line 53) | def betas_for_alpha_bar(
  function rescale_zero_terminal_snr (line 98) | def rescale_zero_terminal_snr(betas):
  class UFOGenScheduler (line 134) | class UFOGenScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 192) | def __init__(
    method scale_model_input (line 248) | def scale_model_input(self, sample: torch.FloatTensor, timestep: Optio...
    method set_timesteps (line 265) | def set_timesteps(
    method _threshold_sample (line 345) | def _threshold_sample(self, sample: torch.FloatTensor) -> torch.FloatT...
    method step (line 378) | def step(
    method add_noise (line 462) | def add_noise(
    method get_velocity (line 486) | def get_velocity(
    method __len__ (line 506) | def __len__(self):
    method previous_timestep (line 510) | def previous_timestep(self, timestep):

FILE: modules/schedulers/scheduler_unipc_flowmatch.py
  class FlowUniPCMultistepScheduler (line 17) | class FlowUniPCMultistepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 74) | def __init__(
    method step_index (line 133) | def step_index(self):
    method begin_index (line 140) | def begin_index(self):
    method set_begin_index (line 147) | def set_begin_index(self, begin_index: int = 0):
    method set_timesteps (line 158) | def set_timesteps(
    method _threshold_sample (line 228) | def _threshold_sample(self, sample: torch.Tensor) -> torch.Tensor:
    method _sigma_to_t (line 267) | def _sigma_to_t(self, sigma):
    method _sigma_to_alpha_sigma_t (line 270) | def _sigma_to_alpha_sigma_t(self, sigma):
    method time_shift (line 274) | def time_shift(self, mu: float, sigma: float, t: torch.Tensor):
    method convert_model_output (line 277) | def convert_model_output(
    method multistep_uni_p_bh_update (line 348) | def multistep_uni_p_bh_update(
    method multistep_uni_c_bh_update (line 484) | def multistep_uni_c_bh_update(
    method index_for_timestep (line 626) | def index_for_timestep(self, timestep, schedule_timesteps=None):
    method _init_step_index (line 641) | def _init_step_index(self, timestep):
    method step (line 653) | def step(self,
    method scale_model_input (line 739) | def scale_model_input(self, sample: torch.Tensor, *args,
    method add_noise (line 756) | def add_noise(
    method __len__ (line 797) | def __len__(self):

FILE: modules/schedulers/scheduler_vdm.py
  function log_snr (line 32) | def log_snr(t: torch.Tensor, beta_schedule: str) -> torch.Tensor:
  class VDMSchedulerOutput (line 68) | class VDMSchedulerOutput(BaseOutput):
  class VDMScheduler (line 85) | class VDMScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 123) | def __init__(
    method log_snr (line 154) | def log_snr(self, timesteps: torch.Tensor) -> torch.Tensor:
    method get_timesteps (line 174) | def get_timesteps(self, num_steps: Optional[int] = None) -> np.ndarray:
    method set_timesteps (line 200) | def set_timesteps(self, num_inference_steps: int, device: Optional[Uni...
    method _threshold_sample (line 247) | def _threshold_sample(self, sample: torch.Tensor) -> torch.Tensor:
    method scale_model_input (line 281) | def scale_model_input(self, sample: torch.Tensor, timestep: Optional[i...
    method step (line 298) | def step(
    method add_noise (line 389) | def add_noise(self, original_samples: torch.Tensor, noise: torch.Tenso...
    method get_velocity (line 413) | def get_velocity(self, sample: torch.Tensor, noise: torch.Tensor, time...
    method __len__ (line 423) | def __len__(self) -> int:

FILE: modules/script_callbacks.py
  function report_exception (line 11) | def report_exception(e, c, job):
  class ImageSaveParams (line 15) | class ImageSaveParams:
    method __init__ (line 16) | def __init__(self, image, p, filename, pnginfo):
  class ExtraNoiseParams (line 30) | class ExtraNoiseParams:
    method __init__ (line 31) | def __init__(self, noise, x, xi):
  class CFGDenoiserParams (line 42) | class CFGDenoiserParams:
    method __init__ (line 43) | def __init__(self, x, image_cond, sigma, sampling_step, total_sampling...
  class CFGDenoisedParams (line 66) | class CFGDenoisedParams:
    method __init__ (line 67) | def __init__(self, x, sampling_step, total_sampling_steps, inner_model):
  class AfterCFGCallbackParams (line 81) | class AfterCFGCallbackParams:
    method __init__ (line 82) | def __init__(self, x, sampling_step, total_sampling_steps):
  class UiTrainTabParams (line 93) | class UiTrainTabParams:
    method __init__ (line 94) | def __init__(self, txt2img_preview_params):
  class ImageGridLoopParams (line 98) | class ImageGridLoopParams:
    method __init__ (line 99) | def __init__(self, imgs, cols, rows):
  function timer (line 130) | def timer(t0: float, script, callback: str):
  function print_timers (line 138) | def print_timers():
  function clear_callbacks (line 147) | def clear_callbacks():
  function app_started_callback (line 152) | def app_started_callback(demo: Optional[Blocks], app: FastAPI):
  function before_process_callback (line 162) | def before_process_callback(p):
  function after_process_callback (line 172) | def after_process_callback(p):
  function app_reload_callback (line 182) | def app_reload_callback():
  function model_loaded_callback (line 192) | def model_loaded_callback(sd_model):
  function ui_tabs_callback (line 202) | def ui_tabs_callback():
  function ui_settings_callback (line 214) | def ui_settings_callback():
  function before_image_saved_callback (line 224) | def before_image_saved_callback(params: ImageSaveParams):
  function image_saved_callback (line 234) | def image_saved_callback(params: ImageSaveParams):
  function image_save_btn_callback (line 244) | def image_save_btn_callback(filename: str):
  function extra_noise_callback (line 254) | def extra_noise_callback(params: ExtraNoiseParams):
  function cfg_denoiser_callback (line 262) | def cfg_denoiser_callback(params: CFGDenoiserParams):
  function cfg_denoised_callback (line 272) | def cfg_denoised_callback(params: CFGDenoisedParams):
  function cfg_after_cfg_callback (line 282) | def cfg_after_cfg_callback(params: AfterCFGCallbackParams):
  function before_component_callback (line 292) | def before_component_callback(component, **kwargs):
  function after_component_callback (line 302) | def after_component_callback(component, **kwargs):
  function image_grid_callback (line 312) | def image_grid_callback(params: ImageGridLoopParams):
  function infotext_pasted_callback (line 322) | def infotext_pasted_callback(infotext: str, params: Dict[str, Any]):
  function script_unloaded_callback (line 332) | def script_unloaded_callback():
  function before_ui_callback (line 342) | def before_ui_callback():
  function after_ui_callback (line 352) | def after_ui_callback():
  function add_callback (line 362) | def add_callback(callbacks, fun):
  function remove_current_script_callbacks (line 369) | def remove_current_script_callbacks():
  function remove_callbacks_for_function (line 380) | def remove_callbacks_for_function(callback_func):
  function on_app_started (line 386) | def on_app_started(callback):
  function on_before_process (line 392) | def on_before_process(callback):
  function on_after_process (line 397) | def on_after_process(callback):
  function on_before_reload (line 402) | def on_before_reload(callback):
  function on_model_loaded (line 407) | def on_model_loaded(callback):
  function on_ui_tabs (line 413) | def on_ui_tabs(callback):
  function on_ui_settings (line 426) | def on_ui_settings(callback):
  function on_before_image_saved (line 432) | def on_before_image_saved(callback):
  function on_image_saved (line 440) | def on_image_saved(callback):
  function on_image_save_btn (line 448) | def on_image_save_btn(callback):
  function on_extra_noise (line 456) | def on_extra_noise(callback):
  function on_cfg_denoiser (line 464) | def on_cfg_denoiser(callback):
  function on_cfg_denoised (line 472) | def on_cfg_denoised(callback):
  function on_cfg_after_cfg (line 480) | def on_cfg_after_cfg(callback):
  function on_before_component (line 488) | def on_before_component(callback):
  function on_after_component (line 500) | def on_after_component(callback):
  function on_image_grid (line 505) | def on_image_grid(callback):
  function on_infotext_pasted (line 513) | def on_infotext_pasted(callback):
  function on_script_unloaded (line 522) | def on_script_unloaded(callback):
  function on_before_ui (line 529) | def on_before_ui(callback):
  function on_after_ui (line 534) | def on_after_ui(callback):

FILE: modules/script_loading.py
  function load_module (line 13) | def load_module(path):
  function preload_extensions (line 38) | def preload_extensions(extensions_dir, parser):

FILE: modules/scripts.py
  function register_runners (line 13) | def register_runners():

FILE: modules/scripts_auto_postprocessing.py
  class ScriptPostprocessingForMainUI (line 4) | class ScriptPostprocessingForMainUI(scripts_manager.Script):
    method __init__ (line 5) | def __init__(self, script_postproc):
    method title (line 9) | def title(self):
    method show (line 12) | def show(self, is_img2img): # pylint: disable=unused-argument
    method ui (line 15) | def ui(self, is_img2img): # pylint: disable=unused-argument
    method postprocess_image (line 19) | def postprocess_image(self, p, script_pp, *args): # pylint: disable=ar...
  function create_auto_preprocessing_script_data (line 28) | def create_auto_preprocessing_script_data():

FILE: modules/scripts_manager.py
  class PostprocessImageArgs (line 18) | class PostprocessImageArgs:
    method __init__ (line 19) | def __init__(self, image):
  class PostprocessBatchListArgs (line 23) | class PostprocessBatchListArgs:
    method __init__ (line 24) | def __init__(self, images):
  class OnComponent (line 29) | class OnComponent:
  class Script (line 33) | class Script:
    method title (line 51) | def title(self):
    method ui (line 55) | def ui(self, is_img2img):
    method show (line 62) | def show(self, is_img2img): # pylint: disable=unused-argument
    method run (line 72) | def run(self, p, *args):
    method setup (line 82) | def setup(self, p, *args):
    method before_process (line 88) | def before_process(self, p, *args):
    method process (line 96) | def process(self, p, *args):
    method process_images (line 104) | def process_images(self, p, *args):
    method before_process_batch (line 112) | def before_process_batch(self, p, *args, **kwargs):
    method process_batch (line 124) | def process_batch(self, p, *args, **kwargs):
    method postprocess_batch (line 135) | def postprocess_batch(self, p, *args, **kwargs):
    method postprocess_image (line 144) | def postprocess_image(self, p, pp: PostprocessImageArgs, *args):
    method postprocess_batch_list (line 150) | def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, *arg...
    method postprocess (line 166) | def postprocess(self, p, processed, *args):
    method before_component (line 173) | def before_component(self, component, **kwargs):
    method after_component (line 182) | def after_component(self, component, **kwargs):
    method describe (line 188) | def describe(self):
    method elem_id (line 192) | def elem_id(self, item_id):
  function basedir (line 201) | def basedir():
  function list_scripts (line 215) | def list_scripts(scriptdirname, extension):
  function list_files_with_name (line 248) | def list_files_with_name(filename):
  function load_scripts (line 260) | def load_scripts():
  function wrap_call (line 303) | def wrap_call(func, filename, funcname, *args, default=None, **kwargs):
  class ScriptSummary (line 312) | class ScriptSummary:
    method __init__ (line 313) | def __init__(self, op):
    method record (line 319) | def record(self, script):
    method report (line 323) | def report(self):
  class ScriptRunner (line 331) | class ScriptRunner:
    method __init__ (line 332) | def __init__(self, name=''):
    method add_script (line 347) | def add_script(self, script_class, path, is_img2img, is_control):
    method initialize_scripts (line 373) | def initialize_scripts(self, is_img2img=False, is_control=False):
    method prepare_ui (line 404) | def prepare_ui(self):
    method setup_ui (line 407) | def setup_ui(self, parent='unknown', accordion=True):
    method run (line 535) | def run(self, p, *args):
    method after (line 560) | def after(self, p, processed, *args):
    method before_process (line 578) | def before_process(self, p, **kwargs):
    method process (line 590) | def process(self, p, **kwargs):
    method process_images (line 602) | def process_images(self, p, **kwargs):
    method before_process_batch (line 618) | def before_process_batch(self, p, **kwargs):
    method process_batch (line 630) | def process_batch(self, p, **kwargs):
    method postprocess (line 642) | def postprocess(self, p, processed):
    method postprocess_batch (line 654) | def postprocess_batch(self, p, images, **kwargs):
    method postprocess_batch_list (line 666) | def postprocess_batch_list(self, p, pp: PostprocessBatchListArgs, **kw...
    method postprocess_image (line 678) | def postprocess_image(self, p, pp: PostprocessImageArgs):
    method before_component (line 690) | def before_component(self, component, **kwargs):
    method after_component (line 700) | def after_component(self, component, **kwargs):
    method reload_sources (line 716) | def reload_sources(self, cache):
  function reload_script_body_only (line 745) | def reload_script_body_only():

FILE: modules/scripts_postprocessing.py
  class PostprocessedImage (line 6) | class PostprocessedImage:
    method __init__ (line 7) | def __init__(self, image, info = {}):
  class ScriptPostprocessing (line 12) | class ScriptPostprocessing:
    method ui (line 21) | def ui(self):
    method process (line 29) | def process(self, pp: PostprocessedImage, **args):
    method image_changed (line 36) | def image_changed(self):
  function wrap_call (line 40) | def wrap_call(func, filename, funcname, *args, default=None, **kwargs):
  class ScriptPostprocessingRunner (line 50) | class ScriptPostprocessingRunner:
    method __init__ (line 51) | def __init__(self):
    method initialize_scripts (line 55) | def initialize_scripts(self, scripts_data):
    method create_script_ui (line 64) | def create_script_ui(self, script, inputs):
    method scripts_in_preferred_order (line 73) | def scripts_in_preferred_order(self):
    method setup_ui (line 88) | def setup_ui(self):
    method run (line 97) | def run(self, pp: PostprocessedImage, args):
    method create_args_for_run (line 108) | def create_args_for_run(self, scripts_args):
    method image_changed (line 121) | def image_changed(self):
    method postprocess (line 125) | def postprocess(self, filenames, args):

FILE: modules/sd_checkpoint.py
  class CheckpointInfo (line 24) | class CheckpointInfo:
    method __init__ (line 25) | def __init__(self, filename, sha=None, subfolder=None):
    method register (line 92) | def register(self):
    method calculate_shorthash (line 98) | def calculate_shorthash(self):
    method __str__ (line 109) | def __str__(self):
  function setup_model (line 113) | def setup_model():
  function checkpoint_titles (line 119) | def checkpoint_titles(use_short=False):
  function list_models (line 131) | def list_models():
  function update_model_hashes (line 161) | def update_model_hashes():
  function remove_hash (line 200) | def remove_hash(s):
  function get_closest_checkpoint_match (line 204) | def get_closest_checkpoint_match(s: str) -> CheckpointInfo:
  function model_hash (line 290) | def model_hash(filename):
  function select_checkpoint (line 306) | def select_checkpoint(op='model', sd_model_checkpoint=None):
  function init_metadata (line 333) | def init_metadata():
  function extract_thumbnail (line 339) | def extract_thumbnail(filename, data):
  function read_metadata_from_safetensors (line 353) | def read_metadata_from_safetensors(filename):
  function scrub_dict (line 410) | def scrub_dict(dict_obj, keys):
  function write_metadata (line 423) | def write_metadata():

FILE: modules/sd_detect.py
  function guess_by_size (line 11) | def guess_by_size(fn, current_guess):
  function guess_by_name (line 47) | def guess_by_name(fn, current_guess):
  function guess_by_diffusers (line 157) | def guess_by_diffusers(fn, current_guess):
  function guess_variant (line 208) | def guess_variant(fn, current_guess):
  function detect_pipeline (line 225) | def detect_pipeline(f: str, op: str = 'model'):
  function get_load_config (line 263) | def get_load_config(model_file, model_type, config_type='yaml'):

FILE: modules/sd_hijack.py
  function model_hijack (line 7) | def model_hijack(): # a111 compatibility item
  function register_buffer (line 11) | def register_buffer(self, name, attr):
  function fft_fftn (line 26) | def fft_fftn(input, s=None, dim=None, norm=None, *, out=None): # pylint:...
  function fft_ifftn (line 36) | def fft_ifftn(input, s=None, dim=None, norm=None, *, out=None): # pylint...
  function fourier_filter (line 47) | def fourier_filter(x_in, threshold, scale):
  class AutoencoderKLOutput (line 70) | class AutoencoderKLOutput(diffusers.utils.BaseOutput):

FILE: modules/sd_hijack_accelerate.py
  function hijack_set_module_tensor (line 17) | def hijack_set_module_tensor(
  function hijack_set_module_tensor_simple (line 46) | def hijack_set_module_tensor_simple(
  function hijack_accelerate (line 74) | def hijack_accelerate():
  function restore_accelerate (line 80) | def restore_accelerate():
  function hijack_hfhub (line 84) | def hijack_hfhub():
  function torch_conv_forward (line 90) | def torch_conv_forward(self, input, weight, bias): # pylint: disable=red...
  function hijack_torch_conv (line 97) | def hijack_torch_conv():
  function restore_torch_conv (line 100) | def restore_torch_conv():

FILE: modules/sd_hijack_dynamic_atten.py
  function find_split_size (line 11) | def find_split_size(original_size: int, slice_block_size: int, slice_rat...
  function find_sdpa_slice_sizes (line 24) | def find_sdpa_slice_sizes(query_shape: Tuple[int], key_shape: Tuple[int]...
  function dynamic_scaled_dot_product_attention (line 58) | def dynamic_scaled_dot_product_attention(query: torch.FloatTensor, key: ...
  function find_bmm_slice_sizes (line 123) | def find_bmm_slice_sizes(query_shape, query_element_size, slice_rate=2, ...
  class DynamicAttnProcessorBMM (line 156) | class DynamicAttnProcessorBMM:
    method __call__ (line 165) | def __call__(self, attn, hidden_states: torch.Tensor, encoder_hidden_s...

FILE: modules/sd_hijack_freeu.py
  function to_denoising_step (line 21) | def to_denoising_step(number, steps=None) -> int:
  function get_schedule_ratio (line 29) | def get_schedule_ratio():
  function lerp (line 42) | def lerp(a, b, r):
  function free_u_cat_hijack (line 46) | def free_u_cat_hijack(hs, *args, original_function, **kwargs):
  function get_fft_device (line 77) | def get_fft_device():
  function no_gpu_complex_support (line 94) | def no_gpu_complex_support():
  function filter_skip (line 105) | def filter_skip(x, threshold, scale, scale_high):
  function ratio_to_region (line 127) | def ratio_to_region(width: float, offset: float, n: int):
  function apply_freeu (line 146) | def apply_freeu(p):

FILE: modules/sd_hijack_hypertile.py
  function iterative_closest_divisors (line 26) | def iterative_closest_divisors(hw:int, aspect_ratio:float) -> tuple[int,...
  function find_hw_candidates (line 40) | def find_hw_candidates(hw:int, aspect_ratio:float) -> tuple[int, int]:
  function possible_tile_sizes (line 61) | def possible_tile_sizes(dimension: int, tile_size: int, min_tile_size: i...
  function parse_list (line 73) | def parse_list(x: list[int], /) -> str:
  function split_attention (line 80) | def split_attention(layer: nn.Module, tile_size: int=256, min_tile_size:...
  function context_hypertile_vae (line 177) | def context_hypertile_vae(p):
  function context_hypertile_unet (line 206) | def context_hypertile_unet(p):
  function hypertile_set (line 235) | def hypertile_set(p, hr=False):
  function set_resolution (line 246) | def set_resolution(p, hr=False):

FILE: modules/sd_hijack_safetensors.py
  function hijacked_load_file (line 11) | def hijacked_load_file(checkpoint_file, device="cpu"):
  function hijacked_load_state_dict (line 29) | def hijacked_load_state_dict(checkpoint_file, is_quantized: bool = False...
  function hijack_safetensors (line 47) | def hijack_safetensors(_diffusers: bool = True, _transformers: bool = Tr...
  function restore_safetensors (line 54) | def restore_safetensors():

FILE: modules/sd_hijack_te.py
  function hijack_encode_prompt (line 6) | def hijack_encode_prompt(*args, **kwargs):
  function init_hijack (line 29) | def init_hijack(pipe):

FILE: modules/sd_hijack_utils.py
  class CondFunc (line 3) | class CondFunc:
    method __new__ (line 4) | def __new__(cls, orig_func, sub_func, cond_func):
    method __init__ (line 20) | def __init__(self, orig_func, sub_func, cond_func):
    method __call__ (line 24) | def __call__(self, *args, **kwargs):

FILE: modules/sd_hijack_vae.py
  function hijack_vae_upscale (line 10) | def hijack_vae_upscale(*args, **kwargs):
  function hijack_vae_decode (line 18) | def hijack_vae_decode(*args, **kwargs):
  function hijack_vae_encode (line 48) | def hijack_vae_encode(*args, **kwargs):
  function init_hijack (line 72) | def init_hijack(pipe):

FILE: modules/sd_models.py
  function set_huggingface_options (line 62) | def set_huggingface_options():
  function set_vae_options (line 74) | def set_vae_options(sd_model, vae=None, op:str='model', quiet:bool=False):
  function set_diffuser_options (line 129) | def set_diffuser_options(sd_model, vae=None, op:str='model', offload:boo...
  function move_model (line 185) | def move_model(model, device=None, force=False):
  function move_base (line 276) | def move_base(model, device):
  function load_diffuser_initial (line 291) | def load_diffuser_initial(diffusers_load_config, op='model'):
  function load_diffuser_force (line 311) | def load_diffuser_force(detected_model_type, checkpoint_info, diffusers_...
  function load_diffuser_folder (line 508) | def load_diffuser_folder(model_type, pipeline, checkpoint_info, diffuser...
  function load_diffuser_file (line 583) | def load_diffuser_file(model_type, pipeline, checkpoint_info, diffusers_...
  function load_sdnq_module (line 640) | def load_sdnq_module(fn: str, module_name: str, load_method: str):
  function load_sdnq_model (line 669) | def load_sdnq_model(checkpoint_info, pipeline, diffusers_load_config, op):
  function set_overrides (line 714) | def set_overrides(sd_model, checkpoint_info, model_type):
  function set_defaults (line 758) | def set_defaults(sd_model, checkpoint_info):
  function load_diffuser (line 775) | def load_diffuser(checkpoint_info=None, op='model', revision=None): # py...
  class DiffusersTaskType (line 944) | class DiffusersTaskType(Enum):
  function get_diffusers_task (line 952) | def get_diffusers_task(pipe: diffusers.DiffusionPipeline) -> DiffusersTa...
  function switch_pipe (line 970) | def switch_pipe(cls: type[diffusers.DiffusionPipeline] | str, pipeline: ...
  function clean_diffuser_pipe (line 1079) | def clean_diffuser_pipe(pipe):
  function copy_diffuser_options (line 1089) | def copy_diffuser_options(new_pipe, orig_pipe):
  function backup_pipe_components (line 1113) | def backup_pipe_components(pipe):
  function restore_pipe_components (line 1133) | def restore_pipe_components(pipe, components):
  function set_diffuser_pipe (line 1161) | def set_diffuser_pipe(pipe, new_pipe_type):
  function add_noise_pred_to_diffusers_callback (line 1258) | def add_noise_pred_to_diffusers_callback(pipe):
  function get_native (line 1279) | def get_native(pipe: diffusers.DiffusionPipeline):
  function reload_text_encoder (line 1291) | def reload_text_encoder(initial=False):
  function reload_model_weights (line 1311) | def reload_model_weights(sd_model=None, info=None, op='model', force=Fal...
  function clear_caches (line 1347) | def clear_caches(full:bool=False):
  function unload_model_weights (line 1360) | def unload_model_weights(op='model'):
  function hf_auth_check (line 1384) | def hf_auth_check(checkpoint_info, force:bool=False):
  function save_model (line 1406) | def save_model(name: str, path: str = None, shard: str = None, overwrite...

FILE: modules/sd_models_compile.py
  class CompiledModelState (line 9) | class CompiledModelState:
    method __init__ (line 10) | def __init__(self):
  function ipex_optimize (line 30) | def ipex_optimize(sd_model, apply_to_components=True, op="Model"):
  function optimize_openvino (line 66) | def optimize_openvino(sd_model, clear_cache=True):
  function compile_onediff (line 85) | def compile_onediff(sd_model):
  function compile_stablefast (line 119) | def compile_stablefast(sd_model):
  function compile_torch (line 159) | def compile_torch(sd_model, apply_to_components=True, op="Model"):
  function check_deepcache (line 236) | def check_deepcache(enable: bool):
  function compile_deepcache (line 244) | def compile_deepcache(sd_model):
  function compile_diffusers (line 264) | def compile_diffusers(sd_model, apply_to_components=True, op="Model"):
  function openvino_recompile_model (line 281) | def openvino_recompile_model(p, hires=False, refiner=False): # recompile...
  function openvino_post_compile (line 319) | def openvino_post_compile(op="base"): # delete unet after OpenVINO compile

FILE: modules/sd_models_utils.py
  class NoWatermark (line 15) | class NoWatermark:
    method apply_watermark (line 16) | def apply_watermark(self, img):
  function get_signature (line 20) | def get_signature(cls):
  function get_call (line 27) | def get_call(cls):
  function path_to_repo (line 34) | def path_to_repo(checkpoint_info):
  function convert_to_faketensors (line 54) | def convert_to_faketensors(tensor):
  function read_state_dict (line 65) | def read_state_dict(checkpoint_file, map_location=None, what:str='model'...
  function get_state_dict_from_checkpoint (line 96) | def get_state_dict_from_checkpoint(pl_sd):
  function patch_diffuser_config (line 121) | def patch_diffuser_config(sd_model, model_file):
  function apply_function_to_model (line 159) | def apply_function_to_model(sd_model, function, options, op=None):

FILE: modules/sd_modules.py
  class ModuleStats (line 7) | class ModuleStats:
    method __init__ (line 15) | def __init__(self, module: str, cls: str, params: float, size: float, ...
    method __str__ (line 23) | def __str__(self):
  function get_signature (line 27) | def get_signature(cls):
  function get_module_stats (line 32) | def get_module_stats(name, module):
  function get_model_stats (line 47) | def get_model_stats(model, exclude=None):

FILE: modules/sd_offload.py
  function dtype_byte_size (line 30) | def dtype_byte_size(dtype: torch.dtype):
  function get_signature (line 39) | def get_signature(cls):
  function disable_offload (line 44) | def disable_offload(sd_model):
  function set_accelerate (line 60) | def set_accelerate(sd_model):
  function apply_group_offload (line 77) | def apply_group_offload(sd_model, op:str='model'):
  function apply_model_offload (line 99) | def apply_model_offload(sd_model, op:str='model', quiet:bool=False):
  function apply_sequential_offload (line 116) | def apply_sequential_offload(sd_model, op:str='model', quiet:bool=False):
  function apply_none_offload (line 138) | def apply_none_offload(sd_model, op:str='model', quiet:bool=False):
  function set_diffuser_offload (line 153) | def set_diffuser_offload(sd_model, op:str='model', quiet:bool=False, for...
  class OffloadHook (line 183) | class OffloadHook(accelerate.hooks.ModelHook):
    method __init__ (line 184) | def __init__(self, checkpoint_name):
    method validate (line 207) | def validate(self):
    method model_size (line 222) | def model_size(self):
    method init_hook (line 225) | def init_hook(self, module):
    method offload_allowed (line 228) | def offload_allowed(self, module):
    method pre_forward (line 238) | def pre_forward(self, module, *args, **kwargs):
    method post_forward (line 301) | def post_forward(self, module, output):
    method detach_hook (line 308) | def detach_hook(self, module):
  function get_pipe_variants (line 312) | def get_pipe_variants(pipe=None):
  function get_module_names (line 328) | def get_module_names(pipe=None, exclude=None):
  function get_module_sizes (line 362) | def get_module_sizes(pipe=None, exclude=None):
  function move_module_to_cpu (line 385) | def move_module_to_cpu(module, op='unk', force:bool=False):
  function apply_balanced_offload_to_module (line 433) | def apply_balanced_offload_to_module(module, op="apply", force:bool=False):
  function report_model_stats (line 459) | def report_model_stats(module_name, module):
  function apply_balanced_offload (line 469) | def apply_balanced_offload(sd_model=None, exclude:list[str]=None, force:...

FILE: modules/sd_samplers.py
  function find_sampler (line 17) | def find_sampler(name:str):
  function list_samplers (line 28) | def list_samplers():
  function find_sampler_config (line 44) | def find_sampler_config(name):
  function restore_default (line 52) | def restore_default(model):
  function create_sampler (line 69) | def create_sampler(name, model):
  function set_samplers (line 132) | def set_samplers():

FILE: modules/sd_samplers_common.py
  function warn_once (line 18) | def warn_once(message):
  function setup_img2img_steps (line 25) | def setup_img2img_steps(p, steps=None):
  function single_sample_to_image (line 37) | def single_sample_to_image(sample, approximation=None):
  function sample_to_image (line 96) | def sample_to_image(samples, index=0, approximation=None):
  function samples_to_image_grid (line 100) | def samples_to_image_grid(samples, approximation=None):
  function images_tensor_to_samples (line 104) | def images_tensor_to_samples(image, approximation=None, model=None):
  function store_latent (line 125) | def store_latent(decoded):
  function is_sampler_using_eta_noise_seed_delta (line 133) | def is_sampler_using_eta_noise_seed_delta(p):
  class InterruptedException (line 150) | class InterruptedException(BaseException):

FILE: modules/sd_samplers_diffusers.py
  class DiffusionSampler (line 347) | class DiffusionSampler:
    method __init__ (line 348) | def __init__(self, name, constructor, model, **kwargs):

FILE: modules/sd_te_remote.py
  function get_t5_prompt_embeds (line 10) | def get_t5_prompt_embeds(

FILE: modules/sd_unet.py
  function load_unet_sdxl_nunchaku (line 14) | def load_unet_sdxl_nunchaku(repo_id):
  function load_unet (line 36) | def load_unet(model, repo_id:str=None):
  function refresh_unet_list (line 96) | def refresh_unet_list():

FILE: modules/sd_vae.py
  function get_vae_scale_factor (line 21) | def get_vae_scale_factor(model=None):
  function load_vae_dict (line 50) | def load_vae_dict(filename):
  function get_filename (line 56) | def get_filename(filepath):
  function refresh_vae_list (line 63) | def refresh_vae_list():
  function find_vae_near_checkpoint (line 94) | def find_vae_near_checkpoint(checkpoint_file):
  function resolve_vae (line 102) | def resolve_vae(checkpoint_file):
  function apply_vae_config (line 127) | def apply_vae_config(model_file, vae_file, sd_model):
  function load_vae_diffusers (line 147) | def load_vae_diffusers(model_file, vae_file=None, vae_source="unknown-so...
  function reload_vae_weights (line 203) | def reload_vae_weights(sd_model=None, vae_file=unspecified):

FILE: modules/sdnq/common.py
  function check_torch_compile (line 190) | def check_torch_compile(): # dynamo can be disabled after startup
  function fp_mm_torch (line 221) | def fp_mm_torch(x: torch.Tensor, y: torch.Tensor) -> torch.FloatTensor:
  function compile_func (line 239) | def compile_func(fn, **kwargs):
  function compile_func (line 246) | def compile_func(fn, **kwargs): # pylint: disable=unused-argument

FILE: modules/sdnq/dequantizer.py
  function dequantize_asymmetric (line 16) | def dequantize_asymmetric(weight: torch.ByteTensor, scale: torch.FloatTe...
  function dequantize_symmetric (line 37) | def dequantize_symmetric(weight: torch.CharTensor, scale: torch.FloatTen...
  function dequantize_symmetric_with_bias (line 60) | def dequantize_symmetric_with_bias(weight: torch.CharTensor, scale: torc...
  function dequantize_packed_int_asymmetric (line 70) | def dequantize_packed_int_asymmetric(weight: torch.ByteTensor, scale: to...
  function dequantize_packed_int_symmetric (line 75) | def dequantize_packed_int_symmetric(weight: torch.ByteTensor, scale: tor...
  function dequantize_packed_float_asymmetric (line 80) | def dequantize_packed_float_asymmetric(weight: torch.ByteTensor, scale: ...
  function dequantize_packed_float_symmetric (line 85) | def dequantize_packed_float_symmetric(weight: torch.ByteTensor, scale: t...
  function quantize_int_mm (line 90) | def quantize_int_mm(input: torch.FloatTensor, dim: int = -1, matmul_dtyp...
  function quantize_int_mm_sr (line 97) | def quantize_int_mm_sr(input: torch.FloatTensor, dim: int = -1, matmul_d...
  function quantize_fp_mm (line 104) | def quantize_fp_mm(input: torch.FloatTensor, dim: int = -1, matmul_dtype...
  function quantize_fp_mm_sr (line 111) | def quantize_fp_mm_sr(input: torch.FloatTensor, dim: int = -1, matmul_dt...
  function re_quantize_int_mm (line 121) | def re_quantize_int_mm(weight: torch.FloatTensor) -> Tuple[torch.Tensor,...
  function re_quantize_fp_mm (line 133) | def re_quantize_fp_mm(weight: torch.FloatTensor, matmul_dtype: str = "fl...
  function re_quantize_matmul_asymmetric (line 144) | def re_quantize_matmul_asymmetric(weight: torch.ByteTensor, scale: torch...
  function re_quantize_matmul_symmetric (line 153) | def re_quantize_matmul_symmetric(weight: torch.CharTensor, scale: torch....
  function re_quantize_matmul_packed_int_asymmetric (line 162) | def re_quantize_matmul_packed_int_asymmetric(weight: torch.ByteTensor, s...
  function re_quantize_matmul_packed_int_symmetric (line 167) | def re_quantize_matmul_packed_int_symmetric(weight: torch.ByteTensor, sc...
  function re_quantize_matmul_packed_float_asymmetric (line 172) | def re_quantize_matmul_packed_float_asymmetric(weight: torch.ByteTensor,...
  function re_quantize_matmul_packed_float_symmetric (line 177) | def re_quantize_matmul_packed_float_symmetric(weight: torch.ByteTensor, ...
  function dequantize_sdnq_module (line 182) | def dequantize_sdnq_module(model: torch.nn.Module):
  function dequantize_sdnq_model (line 197) | def dequantize_sdnq_model(model: torch.nn.Module):
  class SDNQDequantizer (line 219) | class SDNQDequantizer:
    method __init__ (line 239) | def __init__(
    method re_quantize_matmul (line 276) | def re_quantize_matmul(self, weight, scale, zero_point, svd_up, svd_do...
    method __call__ (line 295) | def __call__(self, weight, scale, zero_point, svd_up, svd_down, skip_q...

FILE: modules/sdnq/file_loader.py
  function map_keys (line 6) | def map_keys(key: str, key_mapping: dict) -> str:
  function load_safetensors (line 16) | def load_safetensors(files: list[str], state_dict: dict = None, key_mapp...
  function load_threaded (line 26) | def load_threaded(files: list[str], state_dict: dict = None, key_mapping...
  function load_streamer (line 37) | def load_streamer(files: list[str], state_dict: dict = None, key_mapping...
  function load_files (line 48) | def load_files(files: list[str], state_dict: dict = None, key_mapping: d...

FILE: modules/sdnq/forward.py
  function get_forward_func (line 8) | def get_forward_func(layer_class_name: str, quantized_matmul_dtype: str,...

FILE: modules/sdnq/layers/__init__.py
  class SDNQLayer (line 4) | class SDNQLayer(torch.nn.Module):
    method __init__ (line 5) | def __init__(self, original_layer, forward_func):
    method dequantize (line 13) | def dequantize(self: torch.nn.Module):
    method forward (line 23) | def forward(self, *args, **kwargs) -> torch.Tensor:
    method __repr__ (line 26) | def __repr__(self):
  class SDNQLinear (line 30) | class SDNQLinear(SDNQLayer, torch.nn.Linear):
  class SDNQConv1d (line 33) | class SDNQConv1d(SDNQLayer, torch.nn.Conv1d):
  class SDNQConv2d (line 36) | class SDNQConv2d(SDNQLayer, torch.nn.Conv2d):
  class SDNQConv3d (line 39) | class SDNQConv3d(SDNQLayer, torch.nn.Conv3d):
  class SDNQConvTranspose1d (line 42) | class SDNQConvTranspose1d(SDNQLayer, torch.nn.ConvTranspose1d):
  class SDNQConvTranspose2d (line 45) | class SDNQConvTranspose2d(SDNQLayer, torch.nn.ConvTranspose2d):
  class SDNQConvTranspose3d (line 48) | class SDNQConvTranspose3d(SDNQLayer, torch.nn.ConvTranspose3d):
  function get_sdnq_wrapper_class (line 62) | def get_sdnq_wrapper_class(original_layer, forward_func):

FILE: modules/sdnq/layers/conv/conv_fp16.py
  function conv_fp16_matmul (line 16) | def conv_fp16_matmul(
  function quantized_conv_forward_fp16_matmul (line 71) | def quantized_conv_forward_fp16_matmul(self, input) -> torch.FloatTensor:

FILE: modules/sdnq/layers/conv/conv_fp8.py
  function conv_fp8_matmul (line 15) | def conv_fp8_matmul(
  function quantized_conv_forward_fp8_matmul (line 75) | def quantized_conv_forward_fp8_matmul(self, input) -> torch.FloatTensor:

FILE: modules/sdnq/layers/conv/conv_fp8_tensorwise.py
  function conv_fp8_matmul_tensorwise (line 16) | def conv_fp8_matmul_tensorwise(
  function quantized_conv_forward_fp8_matmul_tensorwise (line 70) | def quantized_conv_forward_fp8_matmul_tensorwise(self, input) -> torch.F...

FILE: modules/sdnq/layers/conv/conv_int8.py
  function conv_int8_matmul (line 16) | def conv_int8_matmul(
  function quantized_conv_forward_int8_matmul (line 69) | def quantized_conv_forward_int8_matmul(self, input) -> torch.FloatTensor:

FILE: modules/sdnq/layers/conv/forward.py
  function get_conv_args (line 8) | def get_conv_args(input_ndim: int, stride, padding, dilation):
  function process_conv_input (line 28) | def process_conv_input(conv_type, input, reversed_padding_repeated_twice...
  function quantized_conv_forward (line 77) | def quantized_conv_forward(self, input) -> torch.FloatTensor:
  function quantized_conv_transpose_1d_forward (line 81) | def quantized_conv_transpose_1d_forward(self, input: torch.FloatTensor, ...
  function quantized_conv_transpose_2d_forward (line 86) | def quantized_conv_transpose_2d_forward(self, input: torch.FloatTensor, ...
  function quantized_conv_transpose_3d_forward (line 91) | def quantized_conv_transpose_3d_forward(self, input: torch.FloatTensor, ...

FILE: modules/sdnq/layers/linear/forward.py
  function check_mats (line 10) | def check_mats(input: torch.Tensor, weight: torch.Tensor, allow_contiguo...
  function quantized_linear_forward (line 19) | def quantized_linear_forward(self, input: torch.FloatTensor) -> torch.Fl...

FILE: modules/sdnq/layers/linear/linear_fp16.py
  function fp16_matmul (line 13) | def fp16_matmul(
  function quantized_linear_forward_fp16_matmul (line 44) | def quantized_linear_forward_fp16_matmul(self, input: torch.FloatTensor)...

FILE: modules/sdnq/layers/linear/linear_fp8.py
  function quantize_fp_mm_input (line 14) | def quantize_fp_mm_input(input: torch.FloatTensor, matmul_dtype: str = "...
  function fp8_matmul (line 20) | def fp8_matmul(
  function quantized_linear_forward_fp8_matmul (line 49) | def quantized_linear_forward_fp8_matmul(self, input: torch.FloatTensor) ...

FILE: modules/sdnq/layers/linear/linear_fp8_tensorwise.py
  function quantize_fp_mm_input_tensorwise (line 14) | def quantize_fp_mm_input_tensorwise(input: torch.FloatTensor, scale: tor...
  function fp8_matmul_tensorwise (line 23) | def fp8_matmul_tensorwise(
  function quantized_linear_forward_fp8_matmul_tensorwise (line 53) | def quantized_linear_forward_fp8_matmul_tensorwise(self, input: torch.Fl...

FILE: modules/sdnq/layers/linear/linear_int8.py
  function quantize_int_mm_input (line 14) | def quantize_int_mm_input(input: torch.FloatTensor, scale: torch.FloatTe...
  function int8_matmul (line 23) | def int8_matmul(
  function quantized_linear_forward_int8_matmul (line 52) | def quantized_linear_forward_int8_matmul(self, input: torch.FloatTensor)...

FILE: modules/sdnq/loader.py
  function get_module_names (line 12) | def get_module_names(model: ModelMixin) -> list:
  function unset_config_on_save (line 20) | def unset_config_on_save(quantization_config: SDNQConfig) -> SDNQConfig:
  function save_sdnq_model (line 28) | def save_sdnq_model(model: ModelMixin, model_path: str, max_shard_size: ...
  function load_sdnq_model (line 66) | def load_sdnq_model(model_path: str, model_cls: ModelMixin = None, file_...
  function post_process_model (line 143) | def post_process_model(model):
  function apply_sdnq_options_to_module (line 165) | def apply_sdnq_options_to_module(model, dtype: torch.dtype = None, dequa...
  function apply_sdnq_options_to_model (line 225) | def apply_sdnq_options_to_model(model, dtype: torch.dtype = None, dequan...

FILE: modules/sdnq/packed_float.py
  function pack_float (line 18) | def pack_float(x: torch.FloatTensor, weights_dtype: str) -> torch.Tensor:
  function unpack_float (line 62) | def unpack_float(x: torch.Tensor, shape: torch.Size, weights_dtype: str)...

FILE: modules/sdnq/packed_int.py
  function pack_int_symetric (line 10) | def pack_int_symetric(tensor: torch.CharTensor, weights_dtype: str) -> t...
  function pack_int_asymetric (line 14) | def pack_int_asymetric(tensor: torch.CharTensor, weights_dtype: str) -> ...
  function unpack_int_symetric (line 18) | def unpack_int_symetric(packed_tensor: torch.ByteTensor, shape: torch.Si...
  function unpack_int_asymetric (line 24) | def unpack_int_asymetric(packed_tensor: torch.ByteTensor, shape: torch.S...
  function pack_uint7 (line 28) | def pack_uint7(tensor: torch.ByteTensor) -> torch.ByteTensor:
  function pack_uint6 (line 51) | def pack_uint6(tensor: torch.ByteTensor) -> torch.ByteTensor:
  function pack_uint5 (line 75) | def pack_uint5(tensor: torch.ByteTensor) -> torch.ByteTensor:
  function pack_uint4 (line 100) | def pack_uint4(tensor: torch.ByteTensor) -> torch.ByteTensor:
  function pack_uint3 (line 106) | def pack_uint3(tensor: torch.ByteTensor) -> torch.ByteTensor:
  function pack_uint2 (line 124) | def pack_uint2(tensor: torch.ByteTensor) -> torch.ByteTensor:
  function pack_uint1 (line 133) | def pack_uint1(tensor: torch.Tensor) -> torch.Tensor:
  function unpack_uint7 (line 148) | def unpack_uint7(packed_tensor: torch.ByteTensor, shape: torch.Size) -> ...
  function unpack_uint6 (line 177) | def unpack_uint6(packed_tensor: torch.ByteTensor, shape: torch.Size) -> ...
  function unpack_uint5 (line 194) | def unpack_uint5(packed_tensor: torch.ByteTensor, shape: torch.Size) -> ...
  function unpack_uint4 (line 216) | def unpack_uint4(packed_tensor: torch.ByteTensor, shape: torch.Size) -> ...
  function unpack_uint3 (line 221) | def unpack_uint3(packed_tensor: torch.ByteTensor, shape: torch.Size) -> ...
  function unpack_uint2 (line 248) | def unpack_uint2(packed_tensor: torch.ByteTensor, shape: torch.Size) -> ...
  function unpack_uint1 (line 264) | def unpack_uint1(packed_tensor: torch.Tensor, shape: torch.Size) -> torc...

FILE: modules/sdnq/quantizer.py
  class QuantizationMethod (line 26) | class QuantizationMethod(str, Enum):
  function get_scale_asymmetric (line 32) | def get_scale_asymmetric(weight: torch.FloatTensor, reduction_axes: Unio...
  function get_scale_symmetric (line 41) | def get_scale_symmetric(weight: torch.FloatTensor, reduction_axes: Union...
  function quantize_weight (line 46) | def quantize_weight(weight: torch.FloatTensor, reduction_axes: Union[int...
  function apply_svdquant (line 76) | def apply_svdquant(weight: torch.FloatTensor, rank: int = 32, niter: int...
  function prepare_weight_for_matmul (line 96) | def prepare_weight_for_matmul(weight: torch.Tensor) -> torch.Tensor:
  function prepare_svd_for_matmul (line 105) | def prepare_svd_for_matmul(svd_up: torch.FloatTensor, svd_down: torch.Fl...
  function check_param_name_in (line 116) | def check_param_name_in(param_name: str, param_list: List[str]) -> str:
  function get_quant_args_from_config (line 133) | def get_quant_args_from_config(quantization_config: Union["SDNQConfig", ...
  function get_minimum_dtype (line 156) | def get_minimum_dtype(weights_dtype: str, param_name: str, modules_dtype...
  function get_quant_kwargs (line 183) | def get_quant_kwargs(quant_kwargs: dict, modules_quant_config: Dict[str,...
  function add_module_skip_keys (line 192) | def add_module_skip_keys(model, modules_to_not_convert: List[str] = None...
  function sdnq_quantize_layer_weight (line 228) | def sdnq_quantize_layer_weight(weight, layer_class_name=None, weights_dt...
  function sdnq_quantize_layer_weight_dynamic (line 419) | def sdnq_quantize_layer_weight_dynamic(weight, layer_class_name=None, we...
  function sdnq_quantize_layer (line 471) | def sdnq_quantize_layer(layer, weights_dtype="int8", quantized_matmul_dt...
  function apply_sdnq_to_module (line 555) | def apply_sdnq_to_module(model, weights_dtype="int8", quantized_matmul_d...
  function sdnq_post_load_quant (line 633) | def sdnq_post_load_quant(
  class SDNQQuantize (line 736) | class SDNQQuantize():
    method __init__ (line 737) | def __init__(self, hf_quantizer):
    method convert (line 740) | def convert(
    method reverse_op (line 756) | def reverse_op(self):
  class SDNQQuantizer (line 760) | class SDNQQuantizer(DiffusersQuantizer, HfQuantizer):
    method check_if_quantized_param (line 771) | def check_if_quantized_param(
    method check_quantized_param (line 793) | def check_quantized_param(self, *args, **kwargs) -> bool:
    method param_needs_quantization (line 799) | def param_needs_quantization(self, model, param_name: str, *args, **kw...
    method create_quantized_param (line 806) | def create_quantized_param( # pylint: disable=arguments-differ
    method get_quantize_ops (line 887) | def get_quantize_ops(self):
    method adjust_max_memory (line 890) | def adjust_max_memory(self, max_memory: Dict[str, Union[int, str]]) ->...
    method adjust_target_dtype (line 894) | def adjust_target_dtype(self, target_dtype: torch.dtype) -> torch.dtyp...
    method update_torch_dtype (line 897) | def update_torch_dtype(self, torch_dtype: torch.dtype = None) -> torch...
    method update_dtype (line 901) | def update_dtype(self, dtype: torch.dtype = None) -> torch.dtype:
    method _process_model_before_weight_loading (line 907) | def _process_model_before_weight_loading( # pylint: disable=arguments-...
    method _process_model_after_weight_loading (line 943) | def _process_model_after_weight_loading(self, model, **kwargs): # pyli...
    method get_accelerator_warm_up_factor (line 966) | def get_accelerator_warm_up_factor(self):
    method get_cuda_warm_up_factor (line 969) | def get_cuda_warm_up_factor(self):
    method _dequantize (line 975) | def _dequantize(self, model):
    method is_serializable (line 978) | def is_serializable(self, *args, **kwargs) -> bool:  # pylint: disable...
    method is_trainable (line 982) | def is_trainable(self):
    method is_qat_trainable (line 986) | def is_qat_trainable(self) -> bool:
    method is_compileable (line 990) | def is_compileable(self):
  class SDNQConfig (line 995) | class SDNQConfig(QuantizationConfigMixin):
    method __init__ (line 1051) | def __init__( # pylint: disable=super-init-not-called
    method post_init (line 1109) | def post_init(self):
    method to_dict (line 1152) | def to_dict(self):

FILE: modules/sdnq/triton_mm.py
  function get_autotune_config (line 14) | def get_autotune_config():
  function int_mm_kernel (line 59) | def int_mm_kernel(
  function int_mm (line 108) | def int_mm(a, b):
  function fp_mm_kernel (line 128) | def fp_mm_kernel(
  function fp_mm (line 177) | def fp_mm(a, b):

FILE: modules/seedvr/rotary_embedding.py
  function exists (line 12) | def exists(val):
  function default (line 15) | def default(val, d):
  function broadcat (line 20) | def broadcat(tensors, dim = -1):
  function slice_at_dim (line 24) | def slice_at_dim(t, dim_slice: slice, *, dim):
  function rotate_half (line 32) | def rotate_half(x):
  function apply_rotary_emb (line 39) | def apply_rotary_emb(
  function apply_learned_rotations (line 75) | def apply_learned_rotations(rotations, t, start_index = 0, freq_ranges =...
  class RotaryEmbedding (line 85) | class RotaryEmbedding(Module):
    method __init__ (line 86) | def __init__(
    method device (line 164) | def device(self):
    method get_seq_pos (line 167) | def get_seq_pos(self, seq_len, device = None, dtype = None, offset = 0):
    method rotate_queries_or_keys (line 173) | def rotate_queries_or_keys(self, t, seq_dim = None, offset = 0, scale ...
    method rotate_queries_with_cached_keys (line 189) | def rotate_queries_with_cached_keys(self, q, k, seq_dim = None, offset...
    method rotate_queries_and_keys (line 211) | def rotate_queries_and_keys(self, q, k, seq_dim = None):
    method get_scale (line 234) | def get_scale(
    method get_axial_freqs (line 267) | def get_axial_freqs(
    method forward (line 316) | def forward(

FILE: modules/seedvr/src/common/cache.py
  class Cache (line 4) | class Cache:
    method __init__ (line 7) | def __init__(self, disable=False, prefix="", cache=None):
    method __call__ (line 12) | def __call__(self, key: str, fn: Callable):
    method namespace (line 24) | def namespace(self, namespace: str):
    method get (line 31) | def get(self, key: str):

FILE: modules/seedvr/src/common/config.py
  function load_config (line 13) | def load_config(path: str, argv: List[str] = None) -> Union[DictConfig, ...
  function resolve_recursive (line 26) | def resolve_recursive(
  function resolve_inheritance (line 44) | def resolve_inheritance(config: Union[DictConfig, ListConfig]) -> Any:
  function import_item (line 71) | def import_item(path: Union[str, List[str]], name: str) -> Any:
  function create_object (line 107) | def create_object(config: DictConfig) -> Any:

FILE: modules/seedvr/src/common/decorators.py
  function log_on_entry (line 12) | def log_on_entry(func: Callable) -> Callable:
  function barrier_on_entry (line 25) | def barrier_on_entry(func: Callable) -> Callable:
  function _conditional_execute_wrapper_factory (line 37) | def _conditional_execute_wrapper_factory(execute: bool, func: Callable) ...
  function _asserted_wrapper_factory (line 53) | def _asserted_wrapper_factory(condition: bool, func: Callable, err_msg: ...
  function local_rank_zero_only (line 68) | def local_rank_zero_only(func: Callable) -> Callable:
  function global_rank_zero_only (line 75) | def global_rank_zero_only(func: Callable) -> Callable:
  function assert_only_global_rank_zero (line 82) | def assert_only_global_rank_zero(func: Callable) -> Callable:
  function assert_only_local_rank_zero (line 91) | def assert_only_local_rank_zero(func: Callable) -> Callable:
  function new_thread (line 100) | def new_thread(func: Callable) -> Callable:
  function log_runtime (line 114) | def log_runtime(func: Callable) -> Callable:

FILE: modules/seedvr/src/common/diffusion/config.py
  function create_schedule_from_config (line 30) | def create_schedule_from_config(
  function create_sampler_from_config (line 42) | def create_sampler_from_config(
  function create_sampling_timesteps_from_config (line 59) | def create_sampling_timesteps_from_config(

FILE: modules/seedvr/src/common/diffusion/samplers/base.py
  class SamplerModelArgs (line 32) | class SamplerModelArgs:
  class Sampler (line 38) | class Sampler(ABC):
    method __init__ (line 43) | def __init__(
    method sample (line 60) | def sample(
    method get_next_timestep (line 69) | def get_next_timestep(
    method get_endpoint (line 88) | def get_endpoint(
    method get_progress_bar (line 100) | def get_progress_bar(self):

FILE: modules/seedvr/src/common/diffusion/samplers/euler.py
  class EulerSampler (line 32) | class EulerSampler(Sampler):
    method sample (line 38) | def sample(
    method step (line 77) | def step(
    method step_to (line 88) | def step_to(

FILE: modules/seedvr/src/common/diffusion/schedules/base.py
  class Schedule (line 27) | class Schedule(ABC):
    method T (line 37) | def T(self) -> Union[int, float]:
    method A (line 44) | def A(self, t: torch.Tensor) -> torch.Tensor:
    method B (line 51) | def B(self, t: torch.Tensor) -> torch.Tensor:
    method snr (line 59) | def snr(self, t: torch.Tensor) -> torch.Tensor:
    method isnr (line 66) | def isnr(self, snr: torch.Tensor) -> torch.Tensor:
    method is_continuous (line 76) | def is_continuous(self) -> bool:
    method forward (line 82) | def forward(self, x_0: torch.Tensor, x_T: torch.Tensor, t: torch.Tenso...
    method convert_from_pred (line 89) | def convert_from_pred(
    method convert_to_pred (line 116) | def convert_to_pred(

FILE: modules/seedvr/src/common/diffusion/schedules/lerp.py
  class LinearInterpolationSchedule (line 25) | class LinearInterpolationSchedule(Schedule):
    method __init__ (line 37) | def __init__(self, T: Union[int, float] = 1.0):
    method T (line 41) | def T(self) -> Union[int, float]:
    method A (line 44) | def A(self, t: torch.Tensor) -> torch.Tensor:
    method B (line 47) | def B(self, t: torch.Tensor) -> torch.Tensor:
    method isnr (line 52) | def isnr(self, snr: torch.Tensor) -> torch.Tensor:

FILE: modules/seedvr/src/common/diffusion/timesteps/base.py
  class Timesteps (line 8) | class Timesteps(ABC):
    method __init__ (line 13) | def __init__(self, T: Union[int, float]):
    method T (line 18) | def T(self) -> Union[int, float]:
    method is_continuous (line 25) | def is_continuous(self) -> bool:
  class SamplingTimesteps (line 32) | class SamplingTimesteps(Timesteps):
    method __init__ (line 38) | def __init__(
    method __len__ (line 49) | def __len__(self) -> int:
    method __getitem__ (line 55) | def __getitem__(self, idx: Union[int, torch.IntTensor]) -> torch.Tensor:
    method index (line 63) | def index(self, t: torch.Tensor) -> torch.Tensor:

FILE: modules/seedvr/src/common/diffusion/timesteps/sampling/trailing.py
  class UniformTrailingSamplingTimesteps (line 21) | class UniformTrailingSamplingTimesteps(SamplingTimesteps):
    method __init__ (line 30) | def __init__(

FILE: modules/seedvr/src/common/diffusion/types.py
  class PredictionType (line 22) | class PredictionType(str, Enum):
  class SamplingDirection (line 44) | class SamplingDirection(str, Enum):
    method reverse (line 54) | def reverse(direction):

FILE: modules/seedvr/src/common/diffusion/utils.py
  function expand_dims (line 23) | def expand_dims(tensor: torch.Tensor, ndim: int):
  function assert_schedule_timesteps_compatible (line 32) | def assert_schedule_timesteps_compatible(schedule, timesteps):
  function classifier_free_guidance (line 42) | def classifier_free_guidance(
  function classifier_free_guidance_dispatcher (line 65) | def classifier_free_guidance_dispatcher(

FILE: modules/seedvr/src/common/distributed/advanced.py
  function get_data_parallel_group (line 38) | def get_data_parallel_group() -> Optional[dist.ProcessGroup]:
  function get_sequence_parallel_group (line 45) | def get_sequence_parallel_group() -> Optional[dist.ProcessGroup]:
  function get_sequence_parallel_cpu_group (line 52) | def get_sequence_parallel_cpu_group() -> Optional[dist.ProcessGroup]:
  function get_data_parallel_rank (line 59) | def get_data_parallel_rank() -> int:
  function get_data_parallel_world_size (line 67) | def get_data_parallel_world_size() -> int:
  function get_sequence_parallel_rank (line 75) | def get_sequence_parallel_rank() -> int:
  function get_sequence_parallel_world_size (line 83) | def get_sequence_parallel_world_size() -> int:
  function get_model_shard_cpu_intra_group (line 91) | def get_model_shard_cpu_intra_group() -> Optional[dist.ProcessGroup]:
  function get_model_shard_cpu_inter_group (line 98) | def get_model_shard_cpu_inter_group() -> Optional[dist.ProcessGroup]:
  function get_model_shard_intra_group (line 105) | def get_model_shard_intra_group() -> Optional[dist.ProcessGroup]:
  function get_model_shard_inter_group (line 112) | def get_model_shard_inter_group() -> Optional[dist.ProcessGroup]:
  function init_sequence_parallel (line 119) | def init_sequence_parallel(sequence_parallel_size: int):
  function init_model_shard_group (line 143) | def init_model_shard_group(
  function get_sequence_parallel_global_ranks (line 179) | def get_sequence_parallel_global_ranks() -> List[int]:
  function get_next_sequence_parallel_rank (line 189) | def get_next_sequence_parallel_rank() -> int:
  function get_prev_sequence_parallel_rank (line 200) | def get_prev_sequence_parallel_rank() -> int:

FILE: modules/seedvr/src/common/distributed/basic.py
  function get_global_rank (line 23) | def get_global_rank() -> int:
  function get_local_rank (line 30) | def get_local_rank() -> int:
  function get_world_size (line 37) | def get_world_size() -> int:
  function get_device (line 44) | def get_device() -> torch.device:
  function barrier_if_distributed (line 51) | def barrier_if_distributed(*args, **kwargs):
  function convert_to_ddp (line 60) | def convert_to_ddp(module: torch.nn.Module, **kwargs):

FILE: modules/seedvr/src/common/distributed/meta_init_utils.py
  function meta_non_persistent_buffer_init_fn (line 22) | def meta_non_persistent_buffer_init_fn(module: nn.Module) -> nn.Module:

FILE: modules/seedvr/src/common/distributed/ops.py
  function single_all_to_all (line 40) | def single_all_to_all(
  function _all_to_all (line 76) | def _all_to_all(
  class SeqAllToAll (line 91) | class SeqAllToAll(torch.autograd.Function):
    method forward (line 93) | def forward(
    method backward (line 115) | def backward(ctx: Any, *grad_output: Tensor) -> Tuple[None, Tensor, No...
  class Slice (line 131) | class Slice(torch.autograd.Function):
    method forward (line 133) | def forward(ctx: Any, group: dist.ProcessGroup, local_input: Tensor, d...
    method backward (line 143) | def backward(ctx: Any, grad_output: Tensor) -> Tuple[None, Tensor, None]:
  class Gather (line 152) | class Gather(torch.autograd.Function):
    method forward (line 154) | def forward(
    method backward (line 176) | def backward(ctx: Any, grad_output: Tensor) -> Tuple[None, Tensor]:
  function gather_seq_scatter_heads_qkv (line 187) | def gather_seq_scatter_heads_qkv(
  function slice_inputs (line 231) | def slice_inputs(x: Tensor, dim: int, padding: bool = True):
  function remove_seqeunce_parallel_padding (line 250) | def remove_seqeunce_parallel_padding(x: Tensor, dim: int, unpad_dim_size...
  function gather_heads_scatter_seq (line 265) | def gather_heads_scatter_seq(x: Tensor, head_dim: int, seq_dim: int) -> ...
  function gather_seq_scatter_heads (line 280) | def gather_seq_scatter_heads(x: Tensor, seq_dim: int, head_dim: int) -> ...
  function scatter_heads (line 290) | def scatter_heads(x: Tensor, dim: int) -> Tensor:
  function gather_heads (line 300) | def gather_heads(x: Tensor, dim: int, grad_scale: Optional[bool] = False...
  function gather_outputs (line 310) | def gather_outputs(
  function _pad_tensor (line 334) | def _pad_tensor(x: Tensor, dim: int, padding_size: int):
  function _unpad_tensor (line 341) | def _unpad_tensor(x: Tensor, dim: int, padding_size):
  function _broadcast_data (line 347) | def _broadcast_data(data, shape, dtype, src, group, async_op):
  function _traverse (line 360) | def _traverse(data: Any, op: Callable) -> Union[None, List, Dict, Any]:
  function _get_shapes (line 371) | def _get_shapes(data):
  function _get_dtypes (line 375) | def _get_dtypes(data):
  function _construct_broadcast_buffer (line 379) | def _construct_broadcast_buffer(shapes, dtypes, device):
  class SPDistForward (line 396) | class SPDistForward:
    method __init__ (line 407) | def __init__(
    method __call__ (line 420) | def __call__(self, inputs) -> Any:
  function sync_data (line 482) | def sync_data(data, sp_idx, name="tmp"):

FILE: modules/seedvr/src/common/half_precision_fixes.py
  function safe_pad_operation (line 4) | def safe_pad_operation(x, padding, mode='constant', value=0.0):
  function safe_interpolate_operation (line 23) | def safe_interpolate_operation(x, size=None, scale_factor=None, mode='ne...

FILE: modules/seedvr/src/common/logger.py
  function get_logger (line 37) | def get_logger(name: Optional[str] = None) -> logging.Logger:

FILE: modules/seedvr/src/common/partition.py
  function partition_by_size (line 22) | def partition_by_size(data: List[Any], size: int) -> List[List[Any]]:
  function partition_by_groups (line 36) | def partition_by_groups(data: List[Any], groups: int) -> List[List[Any]]:
  function shift_list (line 50) | def shift_list(data: List[Any], n: int) -> List[Any]:

FILE: modules/seedvr/src/common/seed.py
  function set_seed (line 22) | def set_seed(seed: Optional[int], same_across_ranks: bool = False):

FILE: modules/seedvr/src/core/generation.py
  function generation_step (line 11) | def generation_step(runner, text_embeds_dict, cond_latents, temporal_ove...
  function cut_videos (line 97) | def cut_videos(videos):
  function generation_loop (line 109) | def generation_loop(runner, images, cfg_scale=1.0, seed=666, res_w=720, ...
  function prepare_video_transforms (line 273) | def prepare_video_transforms(res_w):
  function calculate_optimal_batch_params (line 301) | def calculate_optimal_batch_params(total_frames, batch_size, temporal_ov...

FILE: modules/seedvr/src/core/infer.py
  function optimized_channels_to_last (line 9) | def optimized_channels_to_last(tensor: torch.Tensor) -> torch.Tensor:
  function optimized_channels_to_second (line 25) | def optimized_channels_to_second(tensor):
  class VideoDiffusionInfer (line 42) | class VideoDiffusionInfer():
    method __init__ (line 43) | def __init__(self, config: DictConfig, device: str, dtype: torch.dtype):
    method get_condition (line 51) | def get_condition(self, latent: torch.Tensor, latent_blur: torch.Tenso...
    method configure_diffusion (line 77) | def configure_diffusion(self):
    method vae_encode (line 95) | def vae_encode(self, samples: List[torch.Tensor]) -> List[torch.Tensor]:
    method vae_decode (line 139) | def vae_decode(self, latents: List[torch.Tensor], target_dtype: torch....
    method timestep_transform (line 189) | def timestep_transform(self, timesteps: torch.Tensor, latents_shapes: ...
    method inference (line 222) | def inference(

FILE: modules/seedvr/src/core/model_manager.py
  function configure_runner (line 11) | def configure_runner(model_name, cache_dir, device:str='cpu', dtype:torc...

FILE: modules/seedvr/src/data/image/transforms/area_resize.py
  class AreaResize (line 24) | class AreaResize:
    method __init__ (line 25) | def __init__(
    method __call__ (line 35) | def __call__(self, image: Union[torch.Tensor, Image.Image]):
  class AreaRandomCrop (line 58) | class AreaRandomCrop:
    method __init__ (line 59) | def __init__(
    method get_params (line 65) | def get_params(self, input_size, output_size):
    method __call__ (line 85) | def __call__(self, image: Union[torch.Tensor, Image.Image]):
  class ScaleResize (line 101) | class ScaleResize:
    method __init__ (line 102) | def __init__(
    method __call__ (line 108) | def __call__(self, image: Union[torch.Tensor, Image.Image]):

FILE: modules/seedvr/src/data/image/transforms/divisible_crop.py
  class DivisibleCrop (line 21) | class DivisibleCrop:
    method __init__ (line 22) | def __init__(self, factor):
    method __call__ (line 28) | def __call__(self, image: Union[torch.Tensor, Image.Image]):

FILE: modules/seedvr/src/data/image/transforms/na_resize.py
  function NaResize (line 22) | def NaResize(

FILE: modules/seedvr/src/data/image/transforms/side_resize.py
  class SideResize (line 22) | class SideResize:
    method __init__ (line 23) | def __init__(
    method __call__ (line 33) | def __call__(self, image: Union[torch.Tensor, Image.Image]):

FILE: modules/seedvr/src/models/dit/attention.py
  function pytorch_varlen_attention (line 23) | def pytorch_varlen_attention(q, k, v, cu_seqlens_q, cu_seqlens_k, max_se...
  class TorchAttention (line 65) | class TorchAttention(nn.Module):
    method tflops (line 66) | def tflops(self, args, kwargs, output) -> float:
    method forward (line 74) | def forward(self, *args, **kwargs):
  class FlashAttentionVarlen (line 79) | class FlashAttentionVarlen(nn.Module):
    method tflops (line 80) | def tflops(self, args, kwargs, output) -> float:
    method forward (line 88) | def forward(self, *args, **kwargs):

FILE: modules/seedvr/src/models/dit/blocks/__init__.py
  function get_block (line 22) | def get_block(block_type: str):

FILE: modules/seedvr/src/models/dit/blocks/mmdit_window_block.py
  class MMWindowAttention (line 31) | class MMWindowAttention(nn.Module):
    method __init__ (line 32) | def __init__(
    method forward (line 63) | def forward(
  class MMWindowTransformerBlock (line 157) | class MMWindowTransformerBlock(nn.Module):
    method __init__ (line 158) | def __init__(
    method forward (line 205) | def forward(

FILE: modules/seedvr/src/models/dit/embedding.py
  function emb_add (line 21) | def emb_add(emb1: torch.Tensor, emb2: Optional[torch.Tensor]):
  class TimeEmbedding (line 25) | class TimeEmbedding(nn.Module):
    method __init__ (line 26) | def __init__(
    method forward (line 39) | def forward(

FILE: modules/seedvr/src/models/dit/mlp.py
  function get_mlp (line 21) | def get_mlp(mlp_type: Optional[str] = "normal"):
  class MLP (line 28) | class MLP(nn.Module):
    method __init__ (line 29) | def __init__(
    method forward (line 39) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:
  class SwiGLUMLP (line 46) | class SwiGLUMLP(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 60) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:

FILE: modules/seedvr/src/models/dit/mm.py
  class MMArg (line 22) | class MMArg:
  function get_args (line 27) | def get_args(key: str, args: List[Any]) -> List[Any]:
  function get_kwargs (line 31) | def get_kwargs(key: str, kwargs: Dict[str, Any]) -> Dict[str, Any]:
  class MMModule (line 35) | class MMModule(nn.Module):
    method __init__ (line 36) | def __init__(
    method forward (line 53) | def forward(

FILE: modules/seedvr/src/models/dit/modulation.py
  function get_ada_layer (line 27) | def get_ada_layer(ada_layer: str) -> ada_layer_type:
  function expand_dims (line 33) | def expand_dims(x: torch.Tensor, dim: int, ndim: int):
  class AdaSingle (line 43) | class AdaSingle(nn.Module):
    method __init__ (line 44) | def __init__(
    method forward (line 60) | def forward(
    method extra_repr (line 96) | def extra_repr(self) -> str:

FILE: modules/seedvr/src/models/dit/na.py
  function flatten (line 21) | def flatten(
  function unflatten (line 33) | def unflatten(
  function concat (line 43) | def concat(
  function concat_idx (line 54) | def concat_idx(
  function unconcat (line 72) | def unconcat(
  function repeat_concat (line 87) | def repeat_concat(
  function repeat_concat_idx (line 101) | def repeat_concat_idx(
  function rearrange (line 143) | def rearrange(
  function rearrange_idx (line 155) | def rearrange_idx(
  function repeat (line 171) | def repeat(
  function pack (line 185) | def pack(
  function unpack (line 205) | def unpack(
  function window (line 216) | def window(
  function window_idx (line 228) | def window_idx(

FILE: modules/seedvr/src/models/dit/nablocks/__init__.py
  function get_nablock (line 22) | def get_nablock(block_type: str):

FILE: modules/seedvr/src/models/dit/nablocks/mmsr_block.py
  class NaSwinAttention (line 34) | class NaSwinAttention(MMWindowAttention):
    method __init__ (line 35) | def __init__(
    method forward (line 67) | def forward(
  class NaMMSRTransformerBlock (line 158) | class NaMMSRTransformerBlock(MMWindowTransformerBlock):
    method __init__ (line 159) | def __init__(
    method forward (line 211) | def forward(

FILE: modules/seedvr/src/models/dit/nadit.py
  function gradient_checkpointing (line 31) | def gradient_checkpointing(module: Union[Callable, nn.Module], *args, en...
  class NaDiTOutput (line 35) | class NaDiTOutput:
  class NaDiT (line 39) | class NaDiT(nn.Module):
    method __init__ (line 46) | def __init__(
    method set_gradient_checkpointing (line 147) | def set_gradient_checkpointing(self, enable: bool):
    method forward (line 150) | def forward(
  class NaDiTUpscaler (line 191) | class NaDiTUpscaler(nn.Module):
    method __init__ (line 198) | def __init__(
    method set_gradient_checkpointing (line 305) | def set_gradient_checkpointing(self, enable: bool):
    method forward (line 308) | def forward(

FILE: modules/seedvr/src/models/dit/normalization.py
  class CustomLayerNorm (line 28) | class CustomLayerNorm(nn.Module):
    method __init__ (line 32) | def __init__(self, normalized_shape, eps=1e-5, elementwise_affine=True):
    method reset_parameters (line 49) | def reset_parameters(self):
    method forward (line 54) | def forward(self, input):
  class CustomRMSNorm (line 59) | class CustomRMSNorm(nn.Module):
    method __init__ (line 63) | def __init__(self, normalized_shape, eps=1e-5, elementwise_affine=True):
    method forward (line 77) | def forward(self, input):
  function get_norm_layer (line 93) | def get_norm_layer(norm_type: Optional[str]) -> norm_layer_type:

FILE: modules/seedvr/src/models/dit/patch.py
  class PatchIn (line 27) | class PatchIn(nn.Module):
    method __init__ (line 28) | def __init__(
    method forward (line 39) | def forward(
  class PatchOut (line 49) | class PatchOut(nn.Module):
    method __init__ (line 50) | def __init__(
    method forward (line 61) | def forward(
  class NaPatchIn (line 71) | class NaPatchIn(PatchIn):
    method forward (line 72) | def forward(
  class NaPatchOut (line 88) | class NaPatchOut(PatchOut):
    method forward (line 89) | def forward(

FILE: modules/seedvr/src/models/dit/rope.py
  class RotaryEmbeddingBase (line 24) | class RotaryEmbeddingBase(nn.Module):
    method __init__ (line 25) | def __init__(self, dim: int, rope_dim: int):
    method get_axial_freqs (line 44) | def get_axial_freqs(self, *dims):
  class RotaryEmbedding3d (line 48) | class RotaryEmbedding3d(RotaryEmbeddingBase):
    method __init__ (line 49) | def __init__(self, dim: int):
    method forward (line 52) | def forward(
  class NaRotaryEmbedding3d (line 72) | class NaRotaryEmbedding3d(RotaryEmbedding3d):
    method forward (line 73) | def forward(
    method get_freqs (line 93) | def get_freqs(

FILE: modules/seedvr/src/models/dit/window.py
  function get_window_op (line 19) | def get_window_op(name: str):
  function make_720Pwindows_bysize (line 28) | def make_720Pwindows_bysize(size: Tuple[int, int, int], num_windows: Tup...
  function make_shifted_720Pwindows_bysize (line 51) | def make_shifted_720Pwindows_bysize(size: Tuple[int, int, int], num_wind...

FILE: modules/seedvr/src/models/dit_v2/attention.py
  function pytorch_varlen_attention (line 23) | def pytorch_varlen_attention(q, k, v, cu_seqlens_q, cu_seqlens_k, max_se...
  class TorchAttention (line 64) | class TorchAttention(nn.Module):
    method tflops (line 65) | def tflops(self, args, kwargs, output) -> float:
    method forward (line 73) | def forward(self, *args, **kwargs):
  class FlashAttentionVarlen (line 77) | class FlashAttentionVarlen(nn.Module):
    method tflops (line 78) | def tflops(self, args, kwargs, output) -> float:
    method forward (line 86) | def forward(self, *args, **kwargs):

FILE: modules/seedvr/src/models/dit_v2/embedding.py
  function emb_add (line 21) | def emb_add(emb1: torch.Tensor, emb2: Optional[torch.Tensor]):
  class TimeEmbedding (line 25) | class TimeEmbedding(nn.Module):
    method __init__ (line 26) | def __init__(
    method forward (line 39) | def forward(

FILE: modules/seedvr/src/models/dit_v2/mlp.py
  function get_mlp (line 21) | def get_mlp(mlp_type: Optional[str] = "normal"):
  class MLP (line 28) | class MLP(nn.Module):
    method __init__ (line 29) | def __init__(
    method forward (line 39) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:
  class SwiGLUMLP (line 46) | class SwiGLUMLP(nn.Module):
    method __init__ (line 47) | def __init__(
    method forward (line 60) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:

FILE: modules/seedvr/src/models/dit_v2/mm.py
  class MMArg (line 22) | class MMArg:
  function get_args (line 27) | def get_args(key: str, args: List[Any]) -> List[Any]:
  function get_kwargs (line 31) | def get_kwargs(key: str, kwargs: Dict[str, Any]) -> Dict[str, Any]:
  class MMModule (line 35) | class MMModule(nn.Module):
    method __init__ (line 36) | def __init__(
    method forward (line 59) | def forward(

FILE: modules/seedvr/src/models/dit_v2/modulation.py
  function get_ada_layer (line 27) | def get_ada_layer(ada_layer: str) -> ada_layer_type:
  function expand_dims (line 33) | def expand_dims(x: torch.Tensor, dim: int, ndim: int):
  class AdaSingle (line 43) | class AdaSingle(nn.Module):
    method __init__ (line 44) | def __init__(
    method forward (line 65) | def forward(
    method extra_repr (line 117) | def extra_repr(self) -> str:

FILE: modules/seedvr/src/models/dit_v2/na.py
  function flatten (line 21) | def flatten(
  function unflatten (line 33) | def unflatten(
  function concat (line 43) | def concat(
  function concat_idx (line 54) | def concat_idx(
  function unconcat (line 72) | def unconcat(
  function repeat_concat (line 87) | def repeat_concat(
  function repeat_concat_idx (line 101) | def repeat_concat_idx(
  function rearrange (line 143) | def rearrange(
  function rearrange_idx (line 155) | def rearrange_idx(
  function repeat (line 171) | def repeat(
  function pack (line 185) | def pack(
  function unpack (line 205) | def unpack(
  function window (line 216) | def window(
  function window_idx (line 228) | def window_idx(

FILE: modules/seedvr/src/models/dit_v2/nablocks/__init__.py
  function get_nablock (line 23) | def get_nablock(block_type: str):

FILE: modules/seedvr/src/models/dit_v2/nablocks/attention/__init__.py
  function get_attn (line 22) | def get_attn(attn_type: str):

FILE: modules/seedvr/src/models/dit_v2/nablocks/attention/mmattn.py
  class NaMMAttention (line 35) | class NaMMAttention(nn.Module):
    method __init__ (line 36) | def __init__(
    method forward (line 77) | def forward(
  class NaSwinAttention (line 143) | class NaSwinAttention(NaMMAttention):
    method __init__ (line 144) | def __init__(
    method forward (line 158) | def forward(

FILE: modules/seedvr/src/models/dit_v2/nablocks/mmsr_block.py
  class NaMMSRTransformerBlock (line 30) | class NaMMSRTransformerBlock(nn.Module):
    method __init__ (line 31) | def __init__(
    method forward (line 82) | def forward(

FILE: modules/seedvr/src/models/dit_v2/nadit.py
  function gradient_checkpointing (line 31) | def gradient_checkpointing(module: Union[Callable, nn.Module], *args, en...
  class NaDiTOutput (line 35) | class NaDiTOutput:
  class NaDiT (line 39) | class NaDiT(nn.Module):
    method __init__ (line 46) | def __init__(
    method set_gradient_checkpointing (line 185) | def set_gradient_checkpointing(self, enable: bool):
    method forward (line 188) | def forward(

FILE: modules/seedvr/src/models/dit_v2/normalization.py
  class CustomLayerNorm (line 28) | class CustomLayerNorm(nn.Module):
    method __init__ (line 32) | def __init__(self, normalized_shape, eps=1e-5, elementwise_affine=True):
    method reset_parameters (line 49) | def reset_parameters(self):
    method forward (line 54) | def forward(self, input):
  class CustomRMSNorm (line 70) | class CustomRMSNorm(nn.Module):
    method __init__ (line 74) | def __init__(self, normalized_shape, eps=1e-5, elementwise_affine=True):
    method forward (line 88) | def forward(self, input):
  function get_norm_layer (line 109) | def get_norm_layer(norm_type: Optional[str]) -> norm_layer_type:

FILE: modules/seedvr/src/models/dit_v2/patch/__init__.py
  function get_na_patch_layers (line 15) | def get_na_patch_layers(patch_type="v1"):

FILE: modules/seedvr/src/models/dit_v2/patch/patch_v1.py
  class PatchIn (line 27) | class PatchIn(nn.Module):
    method __init__ (line 28) | def __init__(
    method forward (line 39) | def forward(
  class PatchOut (line 52) | class PatchOut(nn.Module):
    method __init__ (line 53) | def __init__(
    method forward (line 64) | def forward(
  class NaPatchIn (line 76) | class NaPatchIn(PatchIn):
    method forward (line 77) | def forward(
  class NaPatchOut (line 100) | class NaPatchOut(PatchOut):
    method forward (line 101) | def forward(

FILE: modules/seedvr/src/models/dit_v2/rope.py
  class RotaryEmbeddingBase (line 24) | class RotaryEmbeddingBase(nn.Module):
    method __init__ (line 25) | def __init__(self, dim: int, rope_dim: int):
    method get_axial_freqs (line 44) | def get_axial_freqs(self, *dims):
  class RotaryEmbedding3d (line 48) | class RotaryEmbedding3d(RotaryEmbeddingBase):
    method __init__ (line 49) | def __init__(self, dim: int):
    method forward (line 53) | def forward(
  class MMRotaryEmbeddingBase (line 73) | class MMRotaryEmbeddingBase(RotaryEmbeddingBase):
    method __init__ (line 74) | def __init__(self, dim: int, rope_dim: int):
  class NaMMRotaryEmbedding3d (line 87) | class NaMMRotaryEmbedding3d(MMRotaryEmbeddingBase):
    method __init__ (line 88) | def __init__(self, dim: int):
    method forward (line 91) | def forward(
    method get_freqs (line 130) | def get_freqs(
  function get_na_rope (line 149) | def get_na_rope(rope_type: Optional[str], dim: int):

FILE: modules/seedvr/src/models/dit_v2/window.py
  function get_window_op (line 19) | def get_window_op(name: str):
  function make_720Pwindows_bysize (line 28) | def make_720Pwindows_bysize(size: Tuple[int, int, int], num_windows: Tup...
  function make_shifted_720Pwindows_bysize (line 51) | def make_shifted_720Pwindows_bysize(size: Tuple[int, int, int], num_wind...

FILE: modules/seedvr/src/models/video_vae_v3/modules/attn_video_vae.py
  class Upsample3D (line 40) | class Upsample3D(Upsample2D):
    method __init__ (line 43) | def __init__(
    method forward (line 92) | def forward(
  class Downsample3D (line 145) | class Downsample3D(Downsample2D):
    method __init__ (line 148) | def __init__(
    method forward (line 197) | def forward(
  class ResnetBlock3D (line 221) | class ResnetBlock3D(ResnetBlock2D):
    method __init__ (line 222) | def __init__(
    method forward (line 278) | def forward(
  class DownEncoderBlock3D (line 327) | class DownEncoderBlock3D(DownEncoderBlock2D):
    method __init__ (line 328) | def __init__(
    method forward (line 407) | def forward(
  class UpDecoderBlock3D (line 424) | class UpDecoderBlock3D(UpDecoderBlock2D):
    method __init__ (line 425) | def __init__(
    method forward (line 508) | def forward(
  class UNetMidBlock3D (line 525) | class UNetMidBlock3D(nn.Module):
    method __init__ (line 526) | def __init__(
    method forward (line 618) | def forward(self, hidden_states, temb=None, memory_state: MemoryState ...
  class Encoder3D (line 633) | class Encoder3D(nn.Module):
    method __init__ (line 662) | def __init__(
    method forward (line 770) | def forward(
  class Decoder3D (line 821) | class Decoder3D(nn.Module):
    method __init__ (line 847) | def __init__(
    method forward (line 944) | def forward(
  class AutoencoderKL (line 1004) | class AutoencoderKL(diffusers.AutoencoderKL):
    method __init__ (line 1009) | def __init__(self, attention: bool = True, *args, **kwargs):
    method load_state_dict (line 1017) | def load_state_dict(self, state_dict, strict=True):
  class VideoAutoencoderKL (line 1029) | class VideoAutoencoderKL(diffusers.AutoencoderKL):
    method __init__ (line 1034) | def __init__(
    method encode (line 1148) | def encode(self, x: torch.FloatTensor, return_dict: bool = True) -> Au...
    method decode (line 1159) | def decode(
    method _encode (line 1170) | def _encode(
    method _decode (line 1183) | def _decode(
    method slicing_encode (line 1194) | def slicing_encode(self, x: torch.Tensor) -> torch.Tensor:
    method slicing_decode (line 1212) | def slicing_decode(self, z: torch.Tensor) -> torch.Tensor:
    method blend_v (line 1230) | def blend_v(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method blend_h (line 1236) | def blend_h(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method tiled_encode (line 1242) | def tiled_encode(self, x: torch.Tensor) -> torch.Tensor:
    method tiled_decode (line 1267) | def tiled_decode(self, z: torch.Tensor) -> torch.Tensor:
    method forward (line 1292) | def forward(
    method load_state_dict (line 1307) | def load_state_dict(self, state_dict, strict=False):
  class VideoAutoencoderKLWrapper (line 1320) | class VideoAutoencoderKLWrapper(VideoAutoencoderKL):
    method __init__ (line 1321) | def __init__(
    method forward (line 1334) | def forward(self, x: torch.FloatTensor) -> CausalAutoencoderOutput:
    method encode (line 1340) | def encode(self, x: torch.FloatTensor) -> CausalEncoderOutput:
    method decode (line 1347) | def decode(self, z: torch.FloatTensor) -> CausalDecoderOutput:
    method preprocess (line 1353) | def preprocess(self, x: torch.Tensor):
    method postprocess (line 1358) | def postprocess(self, x: torch.Tensor):
    method set_causal_slicing (line 1362) | def set_causal_slicing(
    method set_memory_limit (line 1381) | def set_memory_limit(self, conv_max_mem: Optional[float], norm_max_mem...

FILE: modules/seedvr/src/models/video_vae_v3/modules/causal_inflation_lib.py
  function ignore_padding (line 31) | def ignore_padding(model):
  class InflatedCausalConv3d (line 40) | class InflatedCausalConv3d(Conv3d):
    method __init__ (line 41) | def __init__(
    method set_memory_limit (line 56) | def set_memory_limit(self, value: float):
    method set_memory_device (line 59) | def set_memory_device(self, memory_device: _memory_device_t):
    method memory_limit_conv (line 62) | def memory_limit_conv(
    method forward (line 145) | def forward(
    method basic_forward (line 160) | def basic_forward(self, input: Tensor, memory_state: MemoryState = Mem...
    method slicing_forward (line 181) | def slicing_forward(
    method tflops (line 238) | def tflops(self, args, kwargs, output) -> float:
    method _load_from_state_dict (line 247) | def _load_from_state_dict(
  function init_causal_conv3d (line 269) | def init_causal_conv3d(
  function causal_norm_wrapper (line 285) | def causal_norm_wrapper(norm_layer: nn.Module, x: torch.Tensor) -> torch...
  function remove_head (line 326) | def remove_head(tensor: Tensor, times: int = 1) -> Tensor:
  function extend_head (line 336) | def extend_head(tensor: Tensor, times: int = 2, memory: Optional[Tensor]...
  function inflate_weight (line 354) | def inflate_weight(weight_2d: torch.Tensor, weight_3d: torch.Tensor, inf...
  function inflate_bias (line 374) | def inflate_bias(bias_2d: torch.Tensor, bias_3d: torch.Tensor, inflation...
  function modify_state_dict (line 388) | def modify_state_dict(layer, state_dict, prefix, inflate_weight_fn, infl...

FILE: modules/seedvr/src/models/video_vae_v3/modules/context_parallel_lib.py
  function causal_conv_slice_inputs (line 22) | def causal_conv_slice_inputs(x, split_size, memory_state):
  function causal_conv_gather_outputs (line 27) | def causal_conv_gather_outputs(x):
  function get_output_len (line 32) | def get_output_len(conv_module, input_len, pad_len, dim=0):
  function get_cache_size (line 38) | def get_cache_size(conv_module, input_len, pad_len, dim=0):
  function cache_send_recv (line 51) | def cache_send_recv(tensor: List[Tensor], cache_size, times, memory=None):

FILE: modules/seedvr/src/models/video_vae_v3/modules/global_config.py
  function get_norm_limit (line 20) | def get_norm_limit():
  function set_norm_limit (line 24) | def set_norm_limit(value: Optional[float] = None):

FILE: modules/seedvr/src/models/video_vae_v3/modules/inflated_layers.py
  class InflatedCausalConv3d (line 26) | class InflatedCausalConv3d(Conv3d):
    method __init__ (line 27) | def __init__(
    method set_memory_device (line 41) | def set_memory_device(self, memory_device: _memory_device_t):
    method forward (line 44) | def forward(self, input: Tensor, memory_state: MemoryState = MemorySta...
    method _load_from_state_dict (line 65) | def _load_from_state_dict(
  function init_causal_conv3d (line 87) | def init_causal_conv3d(

FILE: modules/seedvr/src/models/video_vae_v3/modules/inflated_lib.py
  class MemoryState (line 28) | class MemoryState(Enum):
  function causal_norm_wrapper (line 41) | def causal_norm_wrapper(norm_layer: nn.Module, x: torch.Tensor) -> torch...
  function remove_head (line 65) | def remove_head(tensor: Tensor, times: int = 1) -> Tensor:
  function extend_head (line 74) | def extend_head(
  function inflate_weight (line 93) | def inflate_weight(weight_2d: torch.Tensor, weight_3d: torch.Tensor, inf...
  function inflate_bias (line 113) | def inflate_bias(bias_2d: torch.Tensor, bias_3d: torch.Tensor, inflation...
  function modify_state_dict (line 127) | def modify_state_dict(layer, state_dict, prefix, inflate_weight_fn, infl...

FILE: modules/seedvr/src/models/video_vae_v3/modules/types.py
  class DiagonalGaussianDistribution (line 25) | class DiagonalGaussianDistribution:
    method __init__ (line 26) | def __init__(self, mean: torch.Tensor, logvar: torch.Tensor):
    method mode (line 32) | def mode(self) -> torch.Tensor:
    method sample (line 35) | def sample(self) -> torch.FloatTensor:
    method kl (line 38) | def kl(self) -> torch.Tensor:
  class MemoryState (line 44) | class MemoryState(Enum):
  class QuantizerOutput (line 58) | class QuantizerOutput(NamedTuple):
  class CausalAutoencoderOutput (line 64) | class CausalAutoencoderOutput(NamedTuple):
  class CausalEncoderOutput (line 70) | class CausalEncoderOutput(NamedTuple):
  class CausalDecoderOutput (line 75) | class CausalDecoderOutput(NamedTuple):

FILE: modules/seedvr/src/optimization/memory_manager.py
  function preinitialize_rope_cache (line 13) | def preinitialize_rope_cache(runner) -> None:
  function clear_rope_cache (line 80) | def clear_rope_cache(runner) -> None:

FILE: modules/seedvr/src/optimization/performance.py
  function optimized_video_rearrange (line 12) | def optimized_video_rearrange(video_tensors: List[torch.Tensor]) -> List...
  function optimized_single_video_rearrange (line 80) | def optimized_single_video_rearrange(video: torch.Tensor) -> torch.Tensor:
  function optimized_sample_to_image_format (line 105) | def optimized_sample_to_image_format(sample: torch.Tensor) -> torch.Tensor:
  function temporal_latent_blending (line 130) | def temporal_latent_blending(latents1: torch.Tensor, latents2: torch.Ten...

FILE: modules/seedvr/src/utils/color_fix.py
  function adain_color_fix (line 8) | def adain_color_fix(target: Image, source: Image):
  function wavelet_color_fix (line 23) | def wavelet_color_fix(target: Image, source: Image):
  function calc_mean_std (line 38) | def calc_mean_std(feat: Tensor, eps=1e-5):
  function adaptive_instance_normalization (line 53) | def adaptive_instance_normalization(content_feat:Tensor, style_feat:Tens...
  function wavelet_blur (line 67) | def wavelet_blur(image: Tensor, radius: int):
  function wavelet_decomposition (line 88) | def wavelet_decomposition(image: Tensor, levels=5):
  function wavelet_reconstruction (line 104) | def wavelet_reconstruction(content_feat:Tensor, style_feat:Tensor):

FILE: modules/seedvr/test.py
  function upscale_image (line 25) | def upscale_image(model_name:str, image_path:str):

FILE: modules/server.py
  class UvicornServer (line 7) | class UvicornServer(uvicorn.Server):
    method __init__ (line 8) | def __init__(self, app: fastapi.FastAPI, listen = None, port = None, k...
    method start (line 29) | def start(self):
    method stop (line 34) | def stop(self):
    method restart (line 38) | def restart(self):
  class HypercornServer (line 44) | class HypercornServer():
    method __init__ (line 45) | def __init__(self, app: fastapi.FastAPI, listen = None, port = None, k...
    method run (line 65) | def run(self):
    method start (line 70) | def start(self):

FILE: modules/shared.py
  class Backend (line 66) | class Backend(Enum):
  function list_checkpoint_titles (line 148) | def list_checkpoint_titles():
  function is_url (line 157) | def is_url(string):
  function refresh_checkpoints (line 163) | def refresh_checkpoints():
  function refresh_vaes (line 168) | def refresh_vaes():
  function refresh_upscalers (line 173) | def refresh_upscalers():
  function list_samplers (line 178) | def list_samplers():
  function restart_server (line 908) | def restart_server(restart=True):
  function restore_defaults (line 932) | def restore_defaults(restart=True):

FILE: modules/shared_defaults.py
  function get_default_modes (line 5) | def get_default_modes(cmd_opts, mem_stat):

FILE: modules/shared_helpers.py
  function listdir (line 11) | def listdir(path):
  function walk_files (line 23) | def walk_files(path, allowed_extensions=None):
  function html_path (line 37) | def html_path(filename):
  function html (line 41) | def html(filename):
  function req (line 49) | def req(url_addr, headers = None, **kwargs):
  class TotalTQDM (line 62) | class TotalTQDM: # compatibility with previous global-tqdm
    method __init__ (line 64) | def __init__(self):
    method reset (line 66) | def reset(self):
    method update (line 68) | def update(self):
    method updateTotal (line 70) | def updateTotal(self, new_total):
    method clear (line 72) | def clear(self):

FILE: modules/shared_items.py
  function postprocessing_scripts (line 86) | def postprocessing_scripts():
  function sd_vae_items (line 91) | def sd_vae_items():
  function sd_taesd_items (line 96) | def sd_taesd_items():
  function refresh_vae_list (line 100) | def refresh_vae_list():
  function sd_unet_items (line 105) | def sd_unet_items():
  function refresh_unet_list (line 110) | def refresh_unet_list():
  function sd_te_items (line 115) | def sd_te_items():
  function refresh_te_list (line 121) | def refresh_te_list():
  function list_crossattention (line 126) | def list_crossattention():
  function get_pipelines (line 135) | def get_pipelines():
  function get_repo (line 145) | def get_repo(model):

FILE: modules/shared_legacy.py
  class LegacyOption (line 7) | class LegacyOption(OptionInfo):
    method __init__ (line 8) | def __init__(self, *args, **kwargs):
  function get_legacy_options (line 77) | def get_legacy_options():

FILE: modules/shared_state.py
  class State (line 14) | class State:
    method __init__ (line 53) | def __init__(self):
    method __str__ (line 56) | def __str__(self) -> str:
    method sampling_step (line 68) | def sampling_step(self):
    method sampling_step (line 72) | def sampling_step(self, value):
    method skip (line 77) | def skip(self):
    method interrupt (line 81) | def interrupt(self):
    method pause (line 85) | def pause(self):
    method nextjob (line 89) | def nextjob(self):
    method dict (line 99) | def dict(self):
    method status (line 112) | def status(self):
    method find (line 145) | def find(self, task_id:str):
    method history (line 151) | def history(self, op:str, task_id:str=None, results:list=[]):
    method outputs (line 167) | def outputs(self, results):
    method get_id (line 175) | def get_id(self, task_id:str=None):
    method clear (line 183) | def clear(self):
    method begin (line 194) | def begin(self, title="", task_id=0, api=None):
    method end (line 226) | def end(self, task_id=None):
    method step (line 241) | def step(self, step:int=1):
    method update (line 244) | def update(self, job:str, steps:int=0, jobs:int=0):
    method set_current_image (line 259) | def set_current_image(self):
    method do_set_current_image (line 269) | def do_set_current_image(self):
    method assign_current_image (line 296) | def assign_current_image(self, image):

FILE: modules/styles.py
  class Style (line 15) | class Style():
    method __init__ (line 16) | def __init__(self, name: str, desc: str = "", prompt: str = "", negati...
  function merge_prompts (line 28) | def merge_prompts(style_prompt: str, prompt: str) -> str:
  function apply_styles_to_prompt (line 42) | def apply_styles_to_prompt(prompt, styles):
  function select_from_weighted_list (line 48) | def select_from_weighted_list(inner: str) -> str:
  function apply_curly_braces_to_prompt (line 109) | def apply_curly_braces_to_prompt(prompt, seed=-1):
  function apply_file_wildcards (line 133) | def apply_file_wildcards(prompt, replaced = [], not_found = [], recursio...
  function apply_wildcards_to_prompt (line 187) | def apply_wildcards_to_prompt(prompt, all_wildcards, seed=-1, silent=Fal...
  function get_reference_style (line 220) | def get_reference_style():
  function apply_styles_to_extra (line 232) | def apply_styles_to_extra(p, style: Style):
  class StyleDatabase (line 291) | class StyleDatabase:
    method __init__ (line 292) | def __init__(self, opts):
    method load_style (line 319) | def load_style(self, fn, prefix=None):
    method reload (line 351) | def reload(self):
    method find_style (line 378) | def find_style(self, name):
    method get_style_prompts (line 382) | def get_style_prompts(self, styles):
    method get_negative_style_prompts (line 390) | def get_negative_style_prompts(self, styles):
    method apply_styles_to_prompts (line 398) | def apply_styles_to_prompts(self, prompts, negatives, styles, seeds):
    method apply_styles_to_prompt (line 436) | def apply_styles_to_prompt(self, prompt, styles, wildcards:bool=True):
    method apply_negative_styles_to_prompt (line 447) | def apply_negative_styles_to_prompt(self, prompt, styles, wildcards:bo...
    method apply_styles_to_extra (line 458) | def apply_styles_to_extra(self, p):
    method extract_comments (line 476) | def extract_comments(self, p):
    method save_styles (line 485) | def save_styles(self, path, verbose=False):
    method load_csv (line 508) | def load_csv(self, legacy_file):

FILE: modules/sub_quadratic_attention.py
  function narrow_trunc (line 21) | def narrow_trunc(
  class AttnChunk (line 30) | class AttnChunk(NamedTuple):
  class SummarizeChunk (line 36) | class SummarizeChunk:
    method __call__ (line 38) | def __call__(
  class ComputeQueryChunkAttn (line 45) | class ComputeQueryChunkAttn:
    method __call__ (line 47) | def __call__(
  function _summarize_chunk (line 54) | def _summarize_chunk(
  function _query_chunk_attention (line 75) | def _query_chunk_attention(
  function _get_attention_scores_no_kv_chunking (line 116) | def _get_attention_scores_no_kv_chunking(
  class ScannedChunk (line 135) | class ScannedChunk(NamedTuple):
  function efficient_dot_product_attention (line 140) | def efficient_dot_product_attention(

FILE: modules/taesd/hybrid_small.py
  class AutoencoderSmall (line 38) | class AutoencoderSmall(ModelMixin, ConfigMixin, FromOriginalModelMixin):
    method __init__ (line 73) | def __init__(
    method _set_gradient_checkpointing (line 145) | def _set_gradient_checkpointing(self, module, value=False):
    method enable_tiling (line 149) | def enable_tiling(self, use_tiling: bool = True):
    method disable_tiling (line 157) | def disable_tiling(self):
    method enable_slicing (line 164) | def enable_slicing(self):
    method disable_slicing (line 171) | def disable_slicing(self):
    method attn_processors (line 180) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 204) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method set_default_attn_processor (line 239) | def set_default_attn_processor(self):
    method encode (line 255) | def encode(
    method _decode (line 287) | def _decode(self, z: torch.FloatTensor, return_dict: bool = True) -> U...
    method decode (line 300) | def decode(
    method blend_v (line 328) | def blend_v(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method blend_h (line 334) | def blend_h(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method tiled_encode (line 340) | def tiled_encode(self, x: torch.FloatTensor, return_dict: bool = True)...
    method tiled_decode (line 394) | def tiled_decode(self, z: torch.FloatTensor, return_dict: bool = True)...
    method forward (line 442) | def forward(
    method fuse_qkv_projections (line 471) | def fuse_qkv_projections(self):
    method unfuse_qkv_projections (line 495) | def unfuse_qkv_projections(self):

FILE: modules/taesd/taehv.py
  function conv (line 15) | def conv(n_in, n_out, **kwargs):
  class Clamp (line 18) | class Clamp(nn.Module):
    method forward (line 19) | def forward(self, x):
  class MemBlock (line 22) | class MemBlock(nn.Module):
    method __init__ (line 23) | def __init__(self, n_in, n_out):
    method forward (line 28) | def forward(self, x, past):
  class TPool (line 31) | class TPool(nn.Module):
    method __init__ (line 32) | def __init__(self, n_f, stride):
    method forward (line 36) | def forward(self, x):
  class TGrow (line 40) | class TGrow(nn.Module):
    method __init__ (line 41) | def __init__(self, n_f, stride):
    method forward (line 45) | def forward(self, x):
  function apply_model_with_memblocks (line 50) | def apply_model_with_memblocks(model, x, parallel, show_progress_bar):
  class TAEHV (line 150) | class TAEHV(nn.Module):
    method __init__ (line 153) | def __init__(self, checkpoint_path="taehv.pth", decoder_time_upscale=(...
    method patch_tgrow_layers (line 201) | def patch_tgrow_layers(self, sd):
    method encode_video (line 216) | def encode_video(self, x, parallel=True, show_progress_bar=True):
    method decode_video (line 228) | def decode_video(self, x, parallel=True, show_progress_bar=True):
    method forward (line 241) | def forward(self, x):
    method decode (line 244) | def decode(self, x, parallel=True, show_progress_bar=False, return_dic...
    method encode (line 248) | def encode(self, x, parallel=True, show_progress_bar=False, return_dic...

FILE: modules/taesd/taem1.py
  function conv (line 15) | def conv(n_in, n_out, **kwargs):
  class Clamp (line 18) | class Clamp(nn.Module):
    method forward (line 19) | def forward(self, x):
  class MemBlock (line 22) | class MemBlock(nn.Module):
    method __init__ (line 23) | def __init__(self, n_in, n_out):
    method forward (line 28) | def forward(self, x, past):
  class TPool (line 31) | class TPool(nn.Module):
    method __init__ (line 32) | def __init__(self, n_f, stride):
    method forward (line 36) | def forward(self, x):
  class TGrow (line 40) | class TGrow(nn.Module):
    method __init__ (line 41) | def __init__(self, n_f, stride):
    method forward (line 45) | def forward(self, x):
  function apply_model_with_memblocks (line 50) | def apply_model_with_memblocks(model, x, parallel, show_progress_bar):
  class TAEM1 (line 146) | class TAEM1(nn.Module):
    method __init__ (line 149) | def __init__(self, checkpoint_path="taem1.pth"):
    method encode_video (line 170) | def encode_video(self, x, parallel=True, show_progress_bar=True):
    method decode_video (line 182) | def decode_video(self, x, parallel=True, show_progress_bar=True):
    method forward (line 205) | def forward(self, x):

FILE: modules/taesd/taesd.py
  function conv (line 6) | def conv(n_in, n_out, **kwargs):
  class Clamp (line 9) | class Clamp(nn.Module):
    method forward (line 10) | def forward(self, x):
  class Block (line 13) | class Block(nn.Module):
    method __init__ (line 14) | def __init__(self, n_in, n_out):
    method forward (line 19) | def forward(self, x):
  function Encoder (line 22) | def Encoder(latent_channels=4):
  function Decoder (line 31) | def Decoder(latent_channels=4):
  class TAESD (line 59) | class TAESD(nn.Module): # pylint: disable=abstract-method
    method __init__ (line 63) | def __init__(self, encoder_path=None, decoder_path=None, latent_channe...
    method guess_latent_channels (line 79) | def guess_latent_channels(self, decoder_path, encoder_path):
    method scale_latents (line 87) | def scale_latents(x):
    method unscale_latents (line 91) | def unscale_latents(x):

FILE: modules/teacache/__init__.py
  function apply_teacache (line 13) | def apply_teacache(p):

FILE: modules/teacache/teacache_chroma.py
  function teacache_chroma_forward (line 11) | def teacache_chroma_forward(

FILE: modules/teacache/teacache_cogvideox.py
  function teacache_cog_forward (line 11) | def teacache_cog_forward(

FILE: modules/teacache/teacache_flux.py
  function teacache_flux_forward (line 11) | def teacache_flux_forward(

FILE: modules/teacache/teacache_hidream.py
  function teacache_hidream_forward (line 12) | def teacache_hidream_forward(

FILE: modules/teacache/teacache_ltx.py
  function teacache_ltx_forward (line 11) | def teacache_ltx_forward(

FILE: modules/teacache/teacache_lumina2.py
  function teacache_lumina2_forward (line 11) | def teacache_lumina2_forward(

FILE: modules/teacache/teacache_mochi.py
  function teacache_mochi_forward (line 11) | def teacache_mochi_forward(

FILE: modules/textual_inversion.py
  function list_embeddings (line 16) | def list_embeddings(*dirs):
  function open_embeddings (line 22) | def open_embeddings(filename):
  function convert_bundled (line 61) | def convert_bundled(data):
  function get_text_encoders (line 75) | def get_text_encoders():
  function deref_tokenizers (line 99) | def deref_tokenizers(tokens, tokenizers):
  function insert_tokens (line 118) | def insert_tokens(embeddings: list, tokenizers: list):
  function insert_vectors (line 130) | def insert_vectors(embedding, tokenizers, text_encoders, hiddensizes):
  class Embedding (line 151) | class Embedding:
    method __init__ (line 152) | def __init__(self, vec, name, filename=None, step=None):
    method save (line 167) | def save(self, filename):
    method checksum (line 184) | def checksum(self):
  class DirWithTextualInversionEmbeddings (line 196) | class DirWithTextualInversionEmbeddings:
    method __init__ (line 197) | def __init__(self, path):
    method has_changed (line 201) | def has_changed(self):
    method update (line 206) | def update(self):
  function convert_embedding (line 212) | def convert_embedding(tensor, text_encoder, text_encoder_2):
  class EmbeddingDatabase (line 231) | class EmbeddingDatabase:
    method __init__ (line 232) | def __init__(self):
    method add_embedding_dir (line 240) | def add_embedding_dir(self, path):
    method register_embedding (line 243) | def register_embedding(self, embedding, model):
    method load_diffusers_embedding (line 257) | def load_diffusers_embedding(self, filename: Union[str, List[str]] = N...
    method load_from_dir (line 308) | def load_from_dir(self, embdir):
    method load_textual_inversion_embeddings (line 317) | def load_textual_inversion_embeddings(self, force_reload=False):

FILE: modules/theme.py
  function list_builtin_themes (line 11) | def list_builtin_themes():
  function refresh_themes (line 16) | def refresh_themes(no_update=False):
  function list_locales (line 39) | def list_locales():
  function list_themes (line 43) | def list_themes():
  function reload_gradio_theme (line 87) | def reload_gradio_theme():

FILE: modules/timer.py
  class Timer (line 12) | class Timer:
    method __init__ (line 13) | def __init__(self):
    method elapsed (line 19) | def elapsed(self, reset=True):
    method add (line 26) | def add(self, name, t):
    method ts (line 31) | def ts(self, name, t):
    method record (line 35) | def record(self, category=None, extra_time=0, reset=True):
    method summary (line 44) | def summary(self, min_time=default_min_time, total=True):
    method get_total (line 56) | def get_total(self):
    method dct (line 59) | def dct(self, min_time=default_min_time):
    method reset (line 68) | def reset(self):

FILE: modules/todo/__init__.py
  function apply_todo (line 4) | def apply_todo(model, p, method='todo'):

FILE: modules/todo/todo_merge.py
  function init_generator (line 24) | def init_generator(device: torch.device, fallback: torch.Generator = None):
  function do_nothing (line 41) | def do_nothing(x: torch.Tensor, mode: str = None): # pylint: disable=unu...
  function mps_gather_workaround (line 45) | def mps_gather_workaround(input, dim, index): # pylint: disable=redefine...
  function up_or_downsample (line 56) | def up_or_downsample(item, cur_w, cur_h, new_w, new_h, method):
  function compute_merge (line 74) | def compute_merge(x: torch.Tensor, tome_info):
  function bipartite_soft_matching_random2d (line 132) | def bipartite_soft_matching_random2d(metric: torch.Tensor,
  class TokenMergeAttentionProcessor (line 246) | class TokenMergeAttentionProcessor:
    method __init__ (line 247) | def __init__(self):
    method torch2_attention (line 256) | def torch2_attention(self, attn, query, key, value, attention_mask, ba...
    method xformers_attention (line 272) | def xformers_attention(self, attn, query, key, value, attention_mask, ...
    method regular_attention (line 289) | def regular_attention(self, attn, query, key, value, attention_mask, b...
    method __call__ (line 304) | def __call__(

FILE: modules/todo/todo_utils.py
  function hook_tome_model (line 12) | def hook_tome_model(model: torch.nn.Module):
  function remove_tome_patch (line 22) | def remove_tome_patch(pipe: torch.nn.Module):
  function patch_attention_proc (line 32) | def patch_attention_proc(unet, token_merge_args={}):
  function remove_patch (line 62) | def remove_patch(pipe: torch.nn.Module):

FILE: modules/token_merge.py
  function apply_token_merging (line 4) | def apply_token_merging(sd_model):
  function remove_token_merging (line 61) | def remove_token_merging(sd_model):

FILE: modules/transformer_cache.py
  function set_cache (line 9) | def set_cache(faster_cache=None, pyramid_attention_broadcast=None):

FILE: modules/txt2img.py
  function txt2img (line 12) | def txt2img(id_task, state,

FILE: modules/ui.py
  function create_override_settings_dropdown (line 37) | def create_override_settings_dropdown(a, _b):
  function gr_show (line 41) | def gr_show(visible=True):
  function create_output_panel (line 45) | def create_output_panel(tabname, outdir): # pylint: disable=unused-argum...
  function send_gradio_gallery_to_image (line 50) | def send_gradio_gallery_to_image(x):
  function create_refresh_button (line 56) | def create_refresh_button(refresh_component, refresh_method, refreshed_a...
  function connect_clear_prompt (line 60) | def connect_clear_prompt(button): # pylint: disable=unused-argument
  function setup_progressbar (line 64) | def setup_progressbar(*args, **kwargs): # pylint: disable=unused-argument
  function create_ui (line 68) | def create_ui(startup_timer = None):

FILE: modules/ui_caption.py
  function vlm_caption_wrapper (line 8) | def vlm_caption_wrapper(question, system_prompt, prompt, image, model_na...
  function update_vlm_prompts_for_model (line 18) | def update_vlm_prompts_for_model(model_name):
  function update_vlm_prompt_placeholder (line 25) | def update_vlm_prompt_placeholder(question):
  function update_vlm_params (line 32) | def update_vlm_params(*args):
  function tagger_tag_wrapper (line 46) | def tagger_tag_wrapper(image, model_name, general_threshold, character_t...
  function tagger_batch_wrapper (line 63) | def tagger_batch_wrapper(model_name, batch_files, batch_folder, batch_st...
  function update_tagger_ui (line 85) | def update_tagger_ui(model_name):
  function update_tagger_params (line 99) | def update_tagger_params(model_name, general_threshold, character_thresh...
  function update_clip_params (line 114) | def update_clip_params(*args):
  function update_clip_model_params (line 127) | def update_clip_model_params(clip_model, blip_model, clip_mode):
  function update_vlm_model_params (line 135) | def update_vlm_model_params(vlm_model, vlm_system):
  function update_default_caption_type (line 142) | def update_default_caption_type(caption_type):
  function create_ui (line 148) | def create_ui():

FILE: modules/ui_common.py
  function gr_show (line 16) | def gr_show(visible=True):
  function update_generation_info (line 20) | def update_generation_info(generation_info, html_info, img_index):
  function plaintext_to_html (line 41) | def plaintext_to_html(text, elem_classes=[]):
  function infotext_to_html (line 46) | def infotext_to_html(text):
  function delete_files (line 64) | def delete_files(js_data, files, all_files, index):
  function save_files (line 107) | def save_files(js_data, files, html_info, index):
  function open_folder (line 233) | def open_folder(result_gallery, gallery_index = 0):
  function create_output_panel (line 257) | def create_output_panel(tabname, preview=True, prompt=None, height=None,...
  function create_refresh_button (line 346) | def create_refresh_button(refresh_component, refresh_method, refreshed_a...
  function create_override_inputs (line 364) | def create_override_inputs(tab): # pylint: disable=unused-argument
  function reuse_seed (line 372) | def reuse_seed(seed_component: gr.Number, reuse_button: gr.Button, subse...
  function connect_reuse_seed (line 392) | def connect_reuse_seed(seed: gr.Number, reuse_seed_btn: gr.Button, gener...
  function update_token_counter (line 425) | def update_token_counter(text):

FILE: modules/ui_components.py
  class FormComponent (line 4) | class FormComponent:
    method get_expected_parent (line 5) | def get_expected_parent(self):
  class ToolButton (line 12) | class ToolButton(FormComponent, gr.Button): # small button with single e...
    method __init__ (line 13) | def __init__(self, *args, **kwargs):
    method get_block_name (line 17) | def get_block_name(self):
  class FormRow (line 22) | class FormRow(FormComponent, gr.Row): # unused
    method get_block_name (line 23) | def get_block_name(self):
  class FormColumn (line 27) | class FormColumn(FormComponent, gr.Column): # unused
    method get_block_name (line 28) | def get_block_name(self):
  class FormGroup (line 32) | class FormGroup(FormComponent, gr.Group): # unused
    method get_block_name (line 33) | def get_block_name(self):
  class FormHTML (line 37) | class FormHTML(FormComponent, gr.HTML): # unused
    method get_block_name (line 38) | def get_block_name(self):
  class FormColorPicker (line 42) | class FormColorPicker(FormComponent, gr.ColorPicker): # unused
    method get_block_name (line 43) | def get_block_name(self):
  class DropdownMulti (line 47) | class DropdownMulti(FormComponent, gr.Dropdown): # unused
    method __init__ (line 48) | def __init__(self, **kwargs):
    method get_block_name (line 50) | def get_block_name(self):
  class DropdownEditable (line 54) | class DropdownEditable(FormComponent, gr.Dropdown): # unused
    method __init__ (line 55) | def __init__(self, **kwargs):
    method get_block_name (line 57) | def get_block_name(self):
  class InputAccordion (line 61) | class InputAccordion(gr.Checkbox): # unused
    method __init__ (line 63) | def __init__(self, value, **kwargs):
    method extra (line 80) | def extra(self):
    method __enter__ (line 83) | def __enter__(self):
    method __exit__ (line 87) | def __exit__(self, exc_type, exc_val, exc_tb):
    method get_block_name (line 90) | def get_block_name(self):
  class ResizeHandleRow (line 94) | class ResizeHandleRow(gr.Row): # unusued
    method __init__ (line 95) | def __init__(self, **kwargs):
    method get_block_name (line 98) | def get_block_name(self):

FILE: modules/ui_control.py
  function return_stats (line 19) | def return_stats(t: float = None):
  function return_controls (line 48) | def return_controls(res, t: float = None):
  function get_units (line 73) | def get_units(*values):
  function generate_click (line 90) | def generate_click(job_id: str, state: str, active_tab: str, *args):
  function generate_click_alt (line 118) | def generate_click_alt(job_id: str, state: str, active_tab: str, *args):
  function create_ui (line 146) | def create_ui(_blocks: gr.Blocks=None):

FILE: modules/ui_control_elements.py
  function create_ui_elements (line 14) | def create_ui_elements(units, result_txt, preview_process):

FILE: modules/ui_control_helpers.py
  function initialize (line 20) | def initialize():
  function interrogate (line 51) | def interrogate():
  function display_units (line 64) | def display_units(num_units):
  function get_video (line 69) | def get_video(filepath: str):
  function process_kanvas (line 83) | def process_kanvas(x): # only used when kanvas overrides gr.Image object
  function select_input (line 131) | def select_input(input_mode, input_image, init_image, init_type, input_v...
  function copy_input (line 209) | def copy_input(mode_from, mode_to, input_image, input_resize, input_inpa...
  function transfer_input (line 229) | def transfer_input(dst):

FILE: modules/ui_docs.py
  class Page (line 8) | class Page():
    method __init__ (line 9) | def __init__(self, fn, full: bool = True):
    method read (line 20) | def read(self, full: bool = True):
    method search (line 36) | def search(self, text):
    method get (line 78) | def get(self):
    method __str__ (line 90) | def __str__(self):
  class Pages (line 94) | class Pages():
    method __init__ (line 95) | def __init__(self):
    method build (line 101) | def build(self, full: bool = True):
    method search (line 111) | def search(self, text: str, topk: int = 10, full: bool = True) -> list...
    method get (line 127) | def get(self, title: str) -> Page:
  function get_docs_page (line 139) | def get_docs_page(page_title: str) -> str:
  function search_html (line 148) | def search_html(pages: list[Page]) -> str:
  function search_docs (line 165) | def search_docs(search_term):
  function get_github_page (line 178) | def get_github_page(page):
  function search_github (line 189) | def search_github(search_term):
  function create_ui_logs (line 231) | def create_ui_logs():
  function create_ui_github (line 248) | def create_ui_github():
  function create_ui_docs (line 262) | def create_ui_docs():
  function create_ui (line 277) | def create_ui():

FILE: modules/ui_extensions.py
  function get_installed (line 37) | def get_installed(ext):
  function list_extensions (line 42) | def list_extensions():
  function apply_changes (line 75) | def apply_changes(disable_list, update_list, disable_all):
  function check_updates (line 98) | def check_updates(_id_task, disable_list, search_text, sort_column):
  function normalize_git_url (line 128) | def normalize_git_url(url: str | None) -> str:
  function install_extension_from_url (line 132) | def install_extension_from_url(dirname, url, branch_name, search_text, s...
  function install_extension (line 189) | def install_extension(extension_to_install, search_text, sort_column):
  function uninstall_extension (line 195) | def uninstall_extension(extension_path, search_text, sort_column):
  function update_extension (line 225) | def update_extension(extension_path, search_text, sort_column):
  function refresh_extensions_list (line 252) | def refresh_extensions_list(search_text, sort_column):
  function search_extensions (line 273) | def search_extensions(search_text, sort_column):
  function make_wrappable_html (line 278) | def make_wrappable_html(text: str) -> str:
  function create_html (line 284) | def create_html(search_text, sort_column):
  function create_ui (line 436) | def create_ui():

FILE: modules/ui_extra_networks.py
  function init_api (line 54) | def init_api():
  class DateTimeEncoder (line 125) | class DateTimeEncoder(json.JSONEncoder):
    method default (line 126) | def default(self, o):
  class ExtraNetworksPage (line 133) | class ExtraNetworksPage:
    method __init__ (line 134) | def __init__(self, title):
    method __str__ (line 153) | def __str__(self):
    method switch_view (line 156) | def switch_view(self, tabname: str):
    method refresh (line 166) | def refresh(self):
    method patch (line 169) | def patch(self, text: str, tabname: str):
    method create_xyz_grid (line 172) | def create_xyz_grid(self):
    method find_version (line 175) | def find_version(self, item, info):
    method link_preview (line 198) | def link_preview(self, filename):
    method get_exif (line 204) | def get_exif(self, image: Image.Image):
    method create_thumb (line 221) | def create_thumb(self):
    method create_items (line 256) | def create_items(self, tabname):
    method create_page (line 276) | def create_page(self, tabname, skip = False):
    method list_items (line 379) | def list_items(self):
    method allowed_directories_for_previews (line 382) | def allowed_directories_for_previews(self):
    method create_html (line 385) | def create_html(self, item, tabname):
    method find_preview_file (line 426) | def find_preview_file(self, path):
    method find_preview (line 447) | def find_preview(self, filename):
    method update_all_previews (line 453) | def update_all_previews(self, items):
    method find_description (line 500) | def find_description(self, path, info=None):
    method find_info (line 532) | def find_info(self, path):
  function initialize (line 549) | def initialize():
  function register_page (line 553) | def register_page(page: ExtraNetworksPage):
  function register_pages (line 567) | def register_pages():
  function get_pages (line 590) | def get_pages(title=None):
  class ExtraNetworksUi (line 613) | class ExtraNetworksUi:
    method __init__ (line 614) | def __init__(self):
  function create_ui (line 642) | def create_ui(container, button_parent, tabname, skip_indexing = False):
  function setup_ui (line 1102) | def setup_ui(ui, gallery: gr.Gallery = None):

FILE: modules/ui_extra_networks_checkpoints.py
  class ExtraNetworksPageCheckpoints (line 26) | class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage):
    method __init__ (line 27) | def __init__(self):
    method refresh (line 30) | def refresh(self):
    method list_reference (line 33) | def list_reference(self): # pylint: disable=inconsistent-return-statem...
    method create_item (line 122) | def create_item(self, name):
    method list_items (line 153) | def list_items(self):
    method allowed_directories_for_previews (line 166) | def allowed_directories_for_previews(self):

FILE: modules/ui_extra_networks_history.py
  class ExtraNetworksPageHistory (line 7) | class ExtraNetworksPageHistory(ui_extra_networks.ExtraNetworksPage):
    method __init__ (line 8) | def __init__(self):
    method refresh (line 13) | def refresh(self):
    method list_items (line 20) | def list_items(self):
    method find_description (line 35) | def find_description(self, path, info=None):

FILE: modules/ui_extra_networks_lora.py
  class ExtraNetworksPageLora (line 11) | class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
    method __init__ (line 12) | def __init__(self):
    method refresh (line 16) | def refresh(self):
    method get_tags (line 20) | def get_tags(l, info, version):
    method cleanup_version (line 67) | def cleanup_version(self, dct, lora):
    method create_item (line 72) | def create_item(self, name):
    method list_items (line 106) | def list_items(self):
    method allowed_directories_for_previews (line 117) | def allowed_directories_for_previews(self):

FILE: modules/ui_extra_networks_styles.py
  class ExtraNetworksPageStyles (line 8) | class ExtraNetworksPageStyles(ui_extra_networks.ExtraNetworksPage):
    method __init__ (line 9) | def __init__(self):
    method refresh (line 12) | def refresh(self):
    method parse_desc (line 15) | def parse_desc(self, desc):
    method create_style (line 47) | def create_style(self, params):
    method create_item (line 69) | def create_item(self, k):
    method list_items (line 101) | def list_items(self):
    method allowed_directories_for_previews (line 107) | def allowed_directories_for_previews(self):
  class ExtraNetworkStyles (line 111) | class ExtraNetworkStyles(extra_networks.ExtraNetwork):
    method __init__ (line 112) | def __init__(self):
    method activate (line 116) | def activate(self, p, params_list):
    method deactivate (line 138) | def deactivate(self, p, force=False):

FILE: modules/ui_extra_networks_textual_inversion.py
  class ExtraNetworksPageTextualInversion (line 7) | class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksP...
    method __init__ (line 8) | def __init__(self):
    method refresh (line 13) | def refresh(self):
    method create_item (line 19) | def create_item(self, embedding: Embedding):
    method list_items (line 44) | def list_items(self):
    method allowed_directories_for_previews (line 62) | def allowed_directories_for_previews(self):

FILE: modules/ui_extra_networks_vae.py
  class ExtraNetworksPageVAEs (line 7) | class ExtraNetworksPageVAEs(ui_extra_networks.ExtraNetworksPage):
    method __init__ (line 8) | def __init__(self):
    method refresh (line 11) | def refresh(self):
    method list_items (line 14) | def list_items(self):
    method allowed_directories_for_previews (line 41) | def allowed_directories_for_previews(self):

FILE: modules/ui_extra_networks_wildcards.py
  class ExtraNetworksPageWildcards (line 9) | class ExtraNetworksPageWildcards(ui_extra_networks.ExtraNetworksPage):
    method __init__ (line 10) | def __init__(self):
    method parents (line 13) | def parents(self, file):
    method refresh (line 19) | def refresh(self):
    method list_items (line 26) | def list_items(self):
    method allowed_directories_for_previews (line 49) | def allowed_directories_for_previews(self):

FILE: modules/ui_gallery.py
  function read_media (line 9) | def read_media(fn):
  function create_ui (line 56) | def create_ui():

FILE: modules/ui_guidance.py
  function create_guidance_inputs (line 9) | def create_guidance_inputs(tab):

FILE: modules/ui_history.py
  function create_ui (line 4) | def create_ui():

FILE: modules/ui_img2img.py
  function process_interrogate (line 6) | def process_interrogate(mode, ii_input_files, ii_input_dir, ii_output_di...
  function create_ui (line 35) | def create_ui():

FILE: modules/ui_javascript.py
  function webpath (line 9) | def webpath(fn):
  function html_head (line 20) | def html_head():
  function html_body (line 47) | def html_body():
  function html_login (line 56) | def html_login():
  function html_css (line 64) | def html_css(css: list[str]):
  function reload_javascript (line 100) | def reload_javascript():

FILE: modules/ui_loadsave.py
  class UiLoadsave (line 11) | class UiLoadsave:
    method __init__ (line 14) | def __init__(self, filename):
    method add_component (line 26) | def add_component(self, path, x):
    method add_block (line 107) | def add_block(self, x, path=""):
    method read_from_file (line 121) | def read_from_file(self):
    method write_to_file (line 125) | def write_to_file(self, current_ui_settings):
    method dump_defaults (line 129) | def dump_defaults(self):
    method iter_all (line 134) | def iter_all(self, values):
    method iter_changes (line 159) | def iter_changes(self, values):
    method iter_menus (line 182) | def iter_menus(self):
    method ui_view (line 194) | def ui_view(self, *values):
    method ui_apply (line 225) | def ui_apply(self, *values):
    method ui_submenu_apply (line 246) | def ui_submenu_apply(self, items):
    method ui_restore (line 280) | def ui_restore(self):
    method create_ui (line 286) | def create_ui(self):
    method setup_ui (line 294) | def setup_ui(self):

FILE: modules/ui_models.py
  function create_ui (line 15) | def create_ui():

FILE: modules/ui_models_load.py
  function load_model (line 17) | def load_model(model: str, cls: str, repo: str, dataframes: list):
  function unload_model (line 78) | def unload_model():
  function process_huggingface_url (line 83) | def process_huggingface_url(url):
  class Component (line 104) | class Component():
    method __init__ (line 105) | def __init__(self, signature, name=None, cls=None, val=None, local=Non...
    method __str__ (line 148) | def __str__(self):
    method save (line 151) | def save(self):
    method dataframe (line 154) | def dataframe(self):
    method load (line 157) | def load(self):
  function create_ui (line 215) | def create_ui(gr_status, gr_file):

FILE: modules/ui_postprocessing.py
  function submit_info (line 5) | def submit_info(image):
  function submit_process (line 14) | def submit_process(tab_index, extras_image, image_batch, extras_batch_in...
  function create_ui (line 20) | def create_ui():

FILE: modules/ui_prompt_styles.py
  function select_style (line 10) | def select_style(name):
  function save_style (line 19) | def save_style(name, prompt, negative_prompt):
  function delete_style (line 28) | def delete_style(name):
  function materialize_styles (line 36) | def materialize_styles(prompt, negative_prompt, styles): # pylint: disab...
  function refresh_styles (line 42) | def refresh_styles():
  class UiPromptStyles (line 46) | class UiPromptStyles:
    method __init__ (line 47) | def __init__(self, tabname, main_ui_prompt, main_ui_negative_prompt): ...

FILE: modules/ui_sections.py
  function create_toprow (line 7) | def create_toprow(is_img2img: bool = False, id_part: str = None, generat...
  function ar_change (line 66) | def ar_change(ar, width, height):
  function create_resolution_inputs (line 82) | def create_resolution_inputs(tab, default_width=1024, default_height=1024):
  function create_interrogate_button (line 94) | def create_interrogate_button(tab: str, inputs: list = None, outputs: st...
  function create_batch_inputs (line 101) | def create_batch_inputs(tab, accordion=True):
  function create_seed_inputs (line 109) | def create_seed_inputs(tab, reuse_visible=True, accordion=True, subseed_...
  function create_video_inputs (line 128) | def create_video_inputs(tab:str, show_always:bool=False):
  function create_advanced_inputs (line 149) | def create_advanced_inputs(tab):
  function create_correction_inputs (line 162) | def create_correction_inputs(tab):
  function create_sampler_and_steps_selection (line 186) | def create_sampler_and_steps_selection(choices, tabname, default_steps:i...
  function create_sampler_options (line 196) | def create_sampler_options(tabname):
  function create_hires_inputs (line 299) | def create_hires_inputs(tab):
  function create_resize_inputs (line 319) | def create_resize_inputs(tab, images, accordion=True, latent=False, non_...

FILE: modules/ui_settings.py
  function apply_setting (line 17) | def apply_setting(key, value):
  function get_value_for_setting (line 44) | def get_value_for_setting(key):
  function create_setting_component (line 52) | def create_setting_component(key, is_quicksettings=False):
  function create_dirty_indicator (line 108) | def create_dirty_indicator(key, keys_to_reset, **kwargs):
  function run_settings (line 120) | def run_settings(*args):
  function run_settings_single (line 159) | def run_settings_single(value, key, progress=False):
  function create_ui (line 176) | def create_ui(disabled_tabs=[]):
  function reset_quicksettings (line 313) | def reset_quicksettings(quick_components):
  function create_quicksettings (line 322) | def create_quicksettings(interfaces):

FILE: modules/ui_symbols.py
  class SVGSymbol (line 54) | class SVGSymbol:
    method __stylize (line 60) | def __stylize(cls, svg: str, color: str | None = None, display: str | ...
    method __init__ (line 67) | def __init__(self, svg: str):
    method style (line 81) | def style(self, color: str | None = None, display: str | None = None) ...
    method __str__ (line 88) | def __str__(self):

FILE: modules/ui_txt2img.py
  function create_ui (line 6) | def create_ui():

FILE: modules/ui_video.py
  function create_ui (line 9) | def create_ui():

FILE: modules/ui_video_vlm.py
  function enhance_prompt (line 24) | def enhance_prompt(enable:bool, model:str=None, image=None, prompt:str='...
  function create_ui (line 54) | def create_ui(prompt_element:gr.Textbox, image_element:gr.Image):

FILE: modules/update.py
  function get_version (line 16) | def get_version():
  function apply_update (line 47) | def apply_update(update_rebase, update_submodules, update_extensions):
  function create_ui (line 87) | def create_ui():

FILE: modules/upscaler.py
  class Upscaler (line 10) | class Upscaler:
    method __init__ (line 23) | def __init__(self, create_dirs=True):
    method find_folder (line 54) | def find_folder(self, folder, scalers, loaded):
    method find_scalers (line 70) | def find_scalers(self):
    method do_upscale (line 89) | def do_upscale(self, img: Image, selected_model: str):
    method upscale (line 92) | def upscale(self, img: Image, scale, selected_model: str = None):
    method load_model (line 117) | def load_model(self, path: str):
    method find_models (line 120) | def find_models(self, ext_filter=None) -> list: # pylint: disable=unus...
    method update_status (line 123) | def update_status(self, prompt):
    method find_model (line 126) | def find_model(self, path):
  class UpscalerData (line 144) | class UpscalerData:
    method __init__ (line 152) | def __init__(self, name: str, path: str = None, upscaler: Upscaler = N...
  function compile_upscaler (line 161) | def compile_upscaler(model):

FILE: modules/upscaler_algo.py
  class UpscalerDCC (line 7) | class UpscalerDCC(Upscaler):
    method __init__ (line 8) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 16) | def do_upscale(self, img: Image, selected_model=None):
  class UpscalerVIPS (line 32) | class UpscalerVIPS(Upscaler):
    method __init__ (line 33) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 44) | def do_upscale(self, img: Image, selected_model=None):
  class UpscalerHQX (line 79) | class UpscalerHQX(Upscaler):
    method __init__ (line 80) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 87) | def do_upscale(self, img: Image, selected_model=None):
  class UpscalerICBI (line 99) | class UpscalerICBI(Upscaler):
    method __init__ (line 100) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 107) | def do_upscale(self, img: Image, selected_model=None):

FILE: modules/upscaler_simple.py
  class UpscalerNone (line 6) | class UpscalerNone(Upscaler):
    method __init__ (line 7) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method load_model (line 12) | def load_model(self, path):
    method do_upscale (line 15) | def do_upscale(self, img, selected_model=None):
  class UpscalerResize (line 19) | class UpscalerResize(Upscaler):
    method __init__ (line 20) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 32) | def do_upscale(self, img: Image, selected_model=None):
    method load_model (line 51) | def load_model(self, _):
  class UpscalerLatent (line 55) | class UpscalerLatent(Upscaler):
    method __init__ (line 56) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 69) | def do_upscale(self, img: Image, selected_model=None):

FILE: modules/upscaler_spandrel.py
  class UpscalerSpandrel (line 14) | class UpscalerSpandrel(Upscaler):
    method __init__ (line 15) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method process (line 27) | def process(self, img: Image.Image) -> Image.Image:
    method do_upscale (line 40) | def do_upscale(self, img: Image, selected_model=None):

FILE: modules/upscaler_vae.py
  class UpscalerAsymmetricVAE (line 6) | class UpscalerAsymmetricVAE(Upscaler):
    method __init__ (line 7) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 17) | def do_upscale(self, img: Image, selected_model=None):
  class UpscalerWanUpscale (line 46) | class UpscalerWanUpscale(Upscaler):
    method __init__ (line 47) | def __init__(self, dirname=None): # pylint: disable=unused-argument
    method do_upscale (line 57) | def do_upscale(self, img: Image, selected_model=None):

FILE: modules/vae/sd_vae_approx.py
  class VAEApprox (line 10) | class VAEApprox(nn.Module):
    method __init__ (line 11) | def __init__(self):
    method forward (line 22) | def forward(self, x):
  function nn_approximation (line 35) | def nn_approximation(sample): # Approximate NN
  function cheap_approximation (line 61) | def cheap_approximation(sample): # Approximate simple

FILE: modules/vae/sd_vae_fal.py
  function is_compatile (line 16) | def is_compatile():
  function load_fal_vae (line 20) | def load_fal_vae():
  function unload_fal_vae (line 35) | def unload_fal_vae():
  class Flux2TinyAutoEncoder (line 45) | class Flux2TinyAutoEncoder(ModelMixin, ConfigMixin):
    method __init__ (line 47) | def __init__(
    method encode (line 100) | def encode(self, x: torch.Tensor, return_dict: bool = True) -> Encoder...
    method decode (line 108) | def decode(self, z: torch.Tensor, return_dict: bool = True) -> Decoder...
    method forward (line 116) | def forward(self, sample: torch.Tensor, return_dict: bool = True) -> D...

FILE: modules/vae/sd_vae_natten.py
  function init (line 12) | def init():
  function fuse_qkv (line 23) | def fuse_qkv(attn: Attention) -> None:
  function fuse_vae_qkv (line 33) | def fuse_vae_qkv(vae) -> None:
  class NattenAttnProcessor (line 38) | class NattenAttnProcessor:
    method __init__ (line 41) | def __init__(self, kernel_size: int):
    method __call__ (line 44) | def __call__(
  function enable_natten (line 82) | def enable_natten(pipe):

FILE: modules/vae/sd_vae_ostris.py
  function load_vae (line 13) | def load_vae(pipe):

FILE: modules/vae/sd_vae_remote.py
  function remote_decode (line 49) | def remote_decode(latents: torch.Tensor, width: int = 0, height: int = 0...
  function remote_encode (line 130) | def remote_encode(images: list[Image.Image], model_type: str | None = No...

FILE: modules/vae/sd_vae_repa.py
  function repa_load (line 16) | def repa_load(latents):

FILE: modules/vae/sd_vae_stablecascade.py
  class Previewer (line 11) | class Previewer(nn.Module):
    method __init__ (line 12) | def __init__(self, c_in=16, c_hidden=512, c_out=3):
    method forward (line 50) | def forward(self, x):
  function download_model (line 54) | def download_model(model_path):
  function load_model (line 63) | def load_model(model_path):
  function decode (line 70) | def decode(latents):

FILE: modules/vae/sd_vae_taesd.py
  function warn_once (line 50) | def warn_once(msg, variant=None):
  function get_model (line 59) | def get_model(model_type = 'decoder', variant = None):
  function decode (line 152) | def decode(latents):
  function encode (line 187) | def encode(image):

FILE: modules/video.py
  function interpolate_frames (line 9) | def interpolate_frames(images, count: int = 0, scale: float = 1.0, pad: ...
  function save_video_atomic (line 26) | def save_video_atomic(images, filename, video_type: str = 'none', durati...
  function save_video (line 63) | def save_video(p, images, filename = None, video_type: str = 'none', dur...
  function get_video_params (line 92) | def get_video_params(filepath: str, capture: bool = False):

FILE: modules/video_models/google_veo.py
  function google_requirements (line 31) | def google_requirements():
  function get_size_buckets (line 37) | def get_size_buckets(width: int, height: int) -> str:
  class GoogleVeoVideoPipeline (line 46) | class GoogleVeoVideoPipeline():
    method __init__ (line 47) | def __init__(self, model_name: str):
    method txt2vid (line 54) | def txt2vid(self, prompt):
    method img2vid (line 61) | def img2vid(self, prompt, image):
    method get_args (line 72) | def get_args(self):
    method __call__ (line 112) | def __call__(self, prompt: list[str], width: int, height: int, image: ...
  function load_veo (line 171) | def load_veo(model_name): # pylint: disable=unused-argument

FILE: modules/video_models/models_def.py
  class Model (line 9) | class Model():
    method __str__ (line 29) | def __str__(self):

FILE: modules/video_models/video_cache.py
  function apply_teacache_patch (line 5) | def apply_teacache_patch(cls):

FILE: modules/video_models/video_load.py
  function _loader (line 11) | def _loader(component):
  function load_custom (line 23) | def load_custom(model_name: str):
  function load_model (line 32) | def load_model(selected: models_def.Model):
  function load_upscale_vae (line 195) | def load_upscale_vae():

FILE: modules/video_models/video_overrides.py
  function load_override (line 11) | def load_override(selected: Model, **load_args):
  function set_overrides (line 35) | def set_overrides(p: processing.StableDiffusionProcessingVideo, selected...

FILE: modules/video_models/video_prompt.py
  function prepare_prompt (line 4) | def prepare_prompt(p, init_image, prompt:str, vlm_enhance:bool, vlm_mode...

FILE: modules/video_models/video_run.py
  function generate (line 12) | def generate(*args, **kwargs):

FILE: modules/video_models/video_save.py
  function get_video_filename (line 13) | def get_video_filename(p:processing.StableDiffusionProcessingVideo):
  function save_params (line 31) | def save_params(p, filename: str = None):
  function images_to_tensor (line 55) | def images_to_tensor(images):
  function numpy_to_tensor (line 67) | def numpy_to_tensor(images):
  function write_audio (line 80) | def write_audio(
  function atomic_save_video (line 131) | def atomic_save_video(filename: str,
  function save_video (line 193) | def save_video(

FILE: modules/video_models/video_ui.py
  function engine_change (line 12) | def engine_change(engine):
  function get_selected (line 18) | def get_selected(engine, model):
  function model_change (line 26) | def model_change(engine, model):
  function model_load (line 34) | def model_load(engine, model):
  function run_video (line 52) | def run_video(*args):
  function create_ui_inputs (line 80) | def create_ui_inputs():
  function create_ui_outputs (line 91) | def create_ui_outputs():
  function create_ui_size (line 109) | def create_ui_size():
  function create_ui (line 123) | def create_ui(prompt, negative, styles, overrides, init_image, init_stre...

FILE: modules/video_models/video_utils.py
  function queue_err (line 12) | def queue_err(msg):
  function get_url (line 17) | def get_url(url):
  function check_av (line 21) | def check_av():
  function set_prompt (line 32) | def set_prompt(p):
  function hijack_encode_image (line 41) | def hijack_encode_image(*args, **kwargs):
  function get_codecs (line 57) | def get_codecs():
  function decode_fourcc (line 80) | def decode_fourcc(cc):
  function get_video_frames (line 86) | def get_video_frames(fn: str, num_frames: int = -1, skip_frames: int = 0):

FILE: modules/video_models/video_vae.py
  function set_vae_params (line 9) | def set_vae_params(p, slicing:bool=True, tiling:bool=True, framewise:boo...
  function vae_decode_tiny (line 32) | def vae_decode_tiny(latents):

FILE: modules/zluda.py
  function test (line 10) | def test(device) -> Union[Exception, None]:
  function zluda_init (line 23) | def zluda_init():

FILE: modules/zluda_installer.py
  class ZLUDAResult (line 30) | class ZLUDAResult(ctypes.Structure):
  class ZLUDALibrary (line 37) | class ZLUDALibrary:
    method __init__ (line 40) | def __init__(self, internal: ctypes.CDLL):
  class Core (line 44) | class Core(ZLUDALibrary):
    method __init__ (line 45) | def __init__(self, internal: ctypes.CDLL):
    method to_hip_stream (line 57) | def to_hip_stream(self, zluda_object: ctypes.c_void_p):
    method get_nightly_flag (line 60) | def get_nightly_flag(self) -> int:
  function set_default_agent (line 68) | def set_default_agent(agent: rocm.Agent):
  function is_reinstall_needed (line 73) | def is_reinstall_needed() -> bool: # ZLUDA<3.9.4
  function install (line 77) | def install():
  function uninstall (line 107) | def uninstall():
  function set_blaslt_enabled (line 112) | def set_blaslt_enabled(enabled: bool):
  function get_blaslt_enabled (line 117) | def get_blaslt_enabled() -> bool:
  function link_or_copy (line 121) | def link_or_copy(src: os.PathLike, dst: os.PathLike):
  function load (line 131) | def load():

FILE: pipelines/bria/bria_pipeline.py
  class BriaPipeline (line 63) | class BriaPipeline(FluxPipeline):
    method __init__ (line 81) | def __init__(
    method encode_prompt (line 112) | def encode_prompt(
    method guidance_scale (line 213) | def guidance_scale(self):
    method do_classifier_free_guidance (line 221) | def do_classifier_free_guidance(self):
    method joint_attention_kwargs (line 225) | def joint_attention_kwargs(self):
    method num_timesteps (line 229) | def num_timesteps(self):
    method interrupt (line 233) | def interrupt(self):
    method __call__ (line 238) | def __call__(
    method check_inputs (line 516) | def check_inputs(
    method to (line 567) | def to(self, *args, **kwargs):
    method prepare_latents (line 580) | def prepare_latents(
    method _pack_latents (line 616) | def _pack_latents(latents, batch_size, num_channels_latents, height, w...
    method _unpack_latents (line 624) | def _unpack_latents(latents, height, width, vae_scale_factor):
    method _prepare_latent_image_ids (line 638) | def _prepare_latent_image_ids(batch_size, height, width, device, dtype):

FILE: pipelines/bria/bria_utils.py
  function get_text (line 23) | def get_text(caption):
  function get_by_t5_prompt_embeds (line 55) | def get_by_t5_prompt_embeds(
  function get_t5_prompt_embeds (line 99) | def get_t5_prompt_embeds(
  function get_original_sigmas (line 149) | def get_original_sigmas(num_train_timesteps=1000,num_inference_steps=1000):
  function is_ng_none (line 157) | def is_ng_none(negative_prompt):
  class CudaTimerContext (line 160) | class CudaTimerContext:
    method __init__ (line 161) | def __init__(self, times_arr):
    method __enter__ (line 164) | def __enter__(self):
    method __exit__ (line 169) | def __exit__(self, type, value, traceback):
  function get_env_prefix (line 176) | def get_env_prefix():
  function compute_density_for_timestep_sampling (line 186) | def compute_density_for_timestep_sampling(
  function compute_loss_weighting_for_sd3 (line 206) | def compute_loss_weighting_for_sd3(weighting_scheme: str, sigmas=None):
  function initialize_distributed (line 223) | def initialize_distributed():
  function get_clip_prompt_embeds (line 234) | def get_clip_prompt_embeds(
  function get_1d_rotary_pos_embed (line 287) | def get_1d_rotary_pos_embed(
  class FluxPosEmbed (line 353) | class FluxPosEmbed(torch.nn.Module):
    method __init__ (line 355) | def __init__(self, theta: int, axes_dim: List[int]):
    method forward (line 360) | def forward(self, ids: torch.Tensor) -> torch.Tensor:
  function get_cosine_schedule_with_warmup_and_decay (line 387) | def get_cosine_schedule_with_warmup_and_decay(
  function get_lr_scheduler (line 429) | def get_lr_scheduler(

FILE: pipelines/bria/transformer_block.py
  class FluxSingleTransformerBlock (line 46) | class FluxSingleTransformerBlock(nn.Module):
    method __init__ (line 47) | def __init__(self, dim: int, num_attention_heads: int, attention_head_...
    method forward (line 79) | def forward(
  class FluxTransformerBlock (line 107) | class FluxTransformerBlock(nn.Module):
    method __init__ (line 108) | def __init__(
    method forward (line 136) | def forward(
  class FluxTransformer2DModel (line 193) | class FluxTransformer2DModel(
    method __init__ (line 232) | def __init__(
    method attn_processors (line 291) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 315) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method fuse_qkv_projections (line 350) | def fuse_qkv_projections(self):
    method unfuse_qkv_projections (line 376) | def unfuse_qkv_projections(self):
    method forward (line 389) | def forward(

FILE: pipelines/bria/transformer_bria.py
  class Timesteps (line 17) | class Timesteps(nn.Module):
    method __init__ (line 18) | def __init__(self, num_channels: int, flip_sin_to_cos: bool, downscale...
    method forward (line 26) | def forward(self, timesteps):
  class TimestepProjEmbeddings (line 37) | class TimestepProjEmbeddings(nn.Module):
    method __init__ (line 38) | def __init__(self, embedding_dim, time_theta):
    method forward (line 44) | def forward(self, timestep, dtype):
  class BriaTransformer2DModel (line 55) | class BriaTransformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, ...
    method __init__ (line 76) | def __init__(
    method _set_gradient_checkpointing (line 138) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 142) | def forward(

FILE: pipelines/f_lite/f_lite.model.py
  function timestep_embedding (line 17) | def timestep_embedding(t, dim, max_period=10000):
  class RMSNorm (line 28) | class RMSNorm(nn.Module):
    method __init__ (line 29) | def __init__(self, dim, eps=1e-6, trainable=False):
    method forward (line 37) | def forward(self, x):
  class QKNorm (line 47) | class QKNorm(nn.Module):
    method __init__ (line 50) | def __init__(self, dim, trainable=False):
    method forward (line 55) | def forward(self, q, k):
  class Attention (line 61) | class Attention(nn.Module):
    method __init__ (line 62) | def __init__(
    method forward (line 94) | def forward(self, x, context=None, v_0=None, rope=None):
  class DiTBlock (line 136) | class DiTBlock(nn.Module):
    method __init__ (line 137) | def __init__(
    method forward (line 187) | def forward(self, x, context, c, v_0=None, rope=None):
  class PatchEmbed (line 229) | class PatchEmbed(nn.Module):
    method __init__ (line 230) | def __init__(self, patch_size=16, in_channels=3, embed_dim=768):
    method forward (line 235) | def forward(self, x):
  class TwoDimRotary (line 242) | class TwoDimRotary(torch.nn.Module):
    method __init__ (line 243) | def __init__(self, dim, base=10000, h=256, w=256):
    method forward (line 261) | def forward(self, x, height_width=None, extend_with_register_tokens=0):
  function apply_rotary_emb (line 294) | def apply_rotary_emb(x, cos, sin):
  class DiT (line 306) | class DiT(ModelMixin, ConfigMixin, FromOriginalModelMixin, PeftAdapterMi...
    method __init__ (line 308) | def __init__(
    method save_lora_weights (line 371) | def save_lora_weights(self, save_directory):
    method load_lora_weights (line 376) | def load_lora_weights(self, load_directory):
    method forward (line 382) | def forward(self, x, context, timesteps):

FILE: pipelines/f_lite/model.py
  function timestep_embedding (line 17) | def timestep_embedding(t, dim, max_period=10000):
  class RMSNorm (line 28) | class RMSNorm(nn.Module):
    method __init__ (line 29) | def __init__(self, dim, eps=1e-6, trainable=False):
    method forward (line 37) | def forward(self, x):
  class QKNorm (line 47) | class QKNorm(nn.Module):
    method __init__ (line 50) | def __init__(self, dim, trainable=False):
    method forward (line 55) | def forward(self, q, k):
  class Attention (line 61) | class Attention(nn.Module):
    method __init__ (line 62) | def __init__(
    method forward (line 94) | def forward(self, x, context=None, v_0=None, rope=None):
  class DiTBlock (line 136) | class DiTBlock(nn.Module):
    method __init__ (line 137) | def __init__(
    method forward (line 187) | def forward(self, x, context, c, v_0=None, rope=None):
  class PatchEmbed (line 229) | class PatchEmbed(nn.Module):
    method __init__ (line 230) | def __init__(self, patch_size=16, in_channels=3, embed_dim=768):
    method forward (line 235) | def forward(self, x):
  class TwoDimRotary (line 242) | class TwoDimRotary(torch.nn.Module):
    method __init__ (line 243) | def __init__(self, dim, base=10000, h=256, w=256):
    method forward (line 261) | def forward(self, x, height_width=None, extend_with_register_tokens=0):
  function apply_rotary_emb (line 294) | def apply_rotary_emb(x, cos, sin):
  class DiT (line 306) | class DiT(ModelMixin, ConfigMixin, FromOriginalModelMixin, PeftAdapterMi...
    method __init__ (line 308) | def __init__(
    method save_lora_weights (line 371) | def save_lora_weights(self, save_directory):
    method load_lora_weights (line 376) | def load_lora_weights(self, load_directory):
    method forward (line 382) | def forward(self, x, context, timesteps):

FILE: pipelines/f_lite/pipeline.py
  class APGConfig (line 22) | class APGConfig:
  class FLitePipelineOutput (line 30) | class FLitePipelineOutput(BaseOutput):
  class FLitePipeline (line 42) | class FLitePipeline(DiffusionPipeline):
    method __init__ (line 56) | def __init__(
    method enable_vae_slicing (line 79) | def enable_vae_slicing(self):
    method enable_vae_tiling (line 84) | def enable_vae_tiling(self):
    method set_progress_bar_config (line 89) | def set_progress_bar_config(self, **kwargs):
    method progress_bar (line 93) | def progress_bar(self, iterable=None, **kwargs):
    method encode_prompt (line 99) | def encode_prompt(
    method to (line 148) | def to(self, torch_device=None, torch_dtype=None, silence_dtype_warnin...
    method __call__ (line 159) | def __call__(

FILE: pipelines/flex2/__init__.py
  class Flex2Pipeline (line 12) | class Flex2Pipeline(FluxControlPipeline):
    method __init__ (line 13) | def __init__(
    method check_inputs (line 25) | def check_inputs(
    method __call__ (line 61) | def __call__(

FILE: pipelines/flux/flux_bnb.py
  function load_flux_bnb (line 6) | def load_flux_bnb(checkpoint_info, diffusers_load_config): # pylint: dis...

FILE: pipelines/flux/flux_legacy_loader.py
  function load_flux_quanto (line 14) | def load_flux_quanto(checkpoint_info):
  function load_flux_bnb (line 76) | def load_flux_bnb(checkpoint_info, diffusers_load_config): # pylint: dis...
  function load_quants (line 107) | def load_quants(kwargs, repo_id, cache_dir, allow_quant): # pylint: disa...
  function load_transformer (line 156) | def load_transformer(file_path): # triggered by opts.sd_unet change
  function load_flux (line 206) | def load_flux(checkpoint_info, diffusers_load_config): # triggered by op...

FILE: pipelines/flux/flux_lora.py
  function calculate_module_shape (line 1) | def calculate_module_shape(model, base_module=None, base_weight_param_na...
  function apply_patch (line 29) | def apply_patch():

FILE: pipelines/flux/flux_nf4.py
  function _replace_with_bnb_linear (line 20) | def _replace_with_bnb_linear(
  function check_quantized_param (line 69) | def check_quantized_param(
  function create_quantized_param (line 86) | def create_quantized_param(
  function load_flux_nf4 (line 145) | def load_flux_nf4(checkpoint_info, prequantized: bool = True):

FILE: pipelines/flux/flux_nunchaku.py
  function load_flux_nunchaku (line 4) | def load_flux_nunchaku(repo_id):

FILE: pipelines/flux/flux_quanto.py
  function load_flux_quanto (line 14) | def load_flux_quanto(checkpoint_info):

FILE: pipelines/generic.py
  function _loader (line 12) | def _loader(component):
  function load_transformer (line 21) | def load_transformer(repo_id, cls_name, load_config=None, subfolder="tra...
  function load_text_encoder (line 102) | def load_text_encoder(repo_id, cls_name, load_config=None, subfolder="te...

FILE: pipelines/hdm/hdm/data/base.py
  class BaseDataset (line 10) | class BaseDataset(Data.Dataset):
    method collate (line 11) | def collate(self, batch):
  class DummyDataset (line 31) | class DummyDataset(BaseDataset):
    method __init__ (line 32) | def __init__(
    method __len__ (line 48) | def __len__(self):
    method __getitem__ (line 51) | def __getitem__(self, index):
  class CombineDataset (line 71) | class CombineDataset(Data.Dataset):
    method __init__ (line 72) | def __init__(
    method collate (line 109) | def collate(self, batch):
    method __len__ (line 148) | def __len__(self):
    method __getitem__ (line 152) | def __getitem__(self, index):

FILE: pipelines/hdm/hdm/data/kohya.py
  function get_files (line 21) | def get_files(folder):
  function load_npy (line 32) | def load_npy(path):
  function load_pickle (line 45) | def load_pickle(path):
  function conver_rgb (line 52) | def conver_rgb(x):
  class KohyaDataset (line 56) | class KohyaDataset(Data.Dataset):
    method __init__ (line 57) | def __init__(
    method __len__ (line 117) | def __len__(self):
    method get_caption (line 120) | def get_caption(self, txt_file):
    method get_data_from_files (line 152) | def get_data_from_files(self, img_file, txt_file, resize=None):
    method make_cropped_pos (line 163) | def make_cropped_pos(self, img_t, target_h, target_w):
    method _getitem (line 180) | def _getitem(self, img_file, txt_file):
    method __getitem__ (line 188) | def __getitem__(self, index):

FILE: pipelines/hdm/hdm/loader.py
  function model_loader (line 13) | def model_loader(
  function load_trainer (line 79) | def load_trainer(conf: dict, unet=None, te=None, vae=None, scheduler=Non...
  function load_model (line 100) | def load_model(conf: dict):
  function load_dataset (line 109) | def load_dataset(conf: dict):
  function load_all (line 114) | def load_all(conf: dict):

FILE: pipelines/hdm/hdm/modules/base.py
  class BasicUNet (line 12) | class BasicUNet(ModelMixin, ConfigMixin):
    method enable_gradient_checkpointing (line 13) | def enable_gradient_checkpointing(self):
    method disable_gradient_checkpointing (line 16) | def disable_gradient_checkpointing(self):
    method forward (line 19) | def forward(
  class UNetWithPos (line 38) | class UNetWithPos(UNet2DConditionModel):
    method __init__ (line 40) | def __init__(
    method forward (line 159) | def forward(

FILE: pipelines/hdm/hdm/modules/rope.py
  function bounding_box (line 10) | def bounding_box(h, w, pixel_aspect_ratio=1.0):
  function make_grid (line 29) | def make_grid(h_pos, w_pos):
  function centers (line 36) | def centers(start, stop, num, dtype=None, device=None):
  function make_axial_pos (line 42) | def make_axial_pos(
  function rotate_half (line 55) | def rotate_half(x):
  function apply_rotary_emb (line 60) | def apply_rotary_emb(freqs, t, start_index=0, scale=1.0):
  function freqs_pixel_log (line 73) | def freqs_pixel_log(max_freq=10.0):
  class AxialRoPE (line 82) | class AxialRoPE(nn.Module):
    method __init__ (line 83) | def __init__(
    method extra_repr (line 93) | def extra_repr(self):
    method get_freqs (line 97) | def get_freqs(self, pos):
    method forward (line 105) | def forward(self, x, pos):

FILE: pipelines/hdm/hdm/modules/text_encoders.py
  class BaseTextEncoder (line 11) | class BaseTextEncoder(nn.Module):
    method __init__ (line 12) | def __init__(self):
    method tokenize (line 17) | def tokenize(self, text: str) -> list[int] | list[list[int]] | torch.L...
    method encode (line 20) | def encode(self, text: str) -> torch.Tensor:
    method forward (line 23) | def forward(self, tokenizer_outputs: list[dict[str, torch.Tensor]]):
  class SimpleTextEncoder (line 27) | class SimpleTextEncoder(BaseTextEncoder):
    method __init__ (line 28) | def __init__(
    method tokenize (line 49) | def tokenize(self, text, **kwargs):
    method encode (line 52) | def encode(self, text, **kwargs):
    method forward (line 55) | def forward(self, tokenizers_outputs):
  class ConcatTextEncoders (line 83) | class ConcatTextEncoders(BaseTextEncoder):
    method __init__ (line 92) | def __init__(
    method trainable_modules (line 154) | def trainable_modules(self):
    method trainable_params (line 162) | def trainable_params(self):
    method device (line 171) | def device(self):
    method tokenize (line 174) | def tokenize(self, text, **kwargs):
    method encode (line 180) | def encode(self, text, **kwargs):
    method forward (line 183) | def forward(

FILE: pipelines/hdm/hdm/modules/unet_patch.py
  class RoPEAttention (line 33) | class RoPEAttention(Attention):
    method __init__ (line 34) | def __init__(self, *args, **kwargs):
    method apply_to (line 42) | def apply_to(cls, original: Attention):
    method forward (line 52) | def forward(
  class RoPEAttnProcessor2_0 (line 70) | class RoPEAttnProcessor2_0(AttnProcessor2_0):
    method __call__ (line 71) | def __call__(
  class RoPEXFormersAttnProcessor (line 171) | class RoPEXFormersAttnProcessor(XFormersAttnProcessor):
    method __call__ (line 172) | def __call__(
  class RoPEBasicTransformerBlock (line 273) | class RoPEBasicTransformerBlock(BasicTransformerBlock):
    method apply_to (line 275) | def apply_to(cls, original: BasicTransformerBlock):
    method forward (line 283) | def forward(
  class RoPETransformer2DModel (line 413) | class RoPETransformer2DModel(Transformer2DModel):
    method __init__ (line 416) | def __init__(self, *args, **kwargs):
    method forward (line 422) | def forward(
  function apply_patch (line 550) | def apply_patch():
  function restore (line 557) | def restore():
  class HDUNet2DConditionModel (line 564) | class HDUNet2DConditionModel(UNet2DConditionModel):
    method __init__ (line 565) | def __init__(self, *args, **kwargs):
    method from_config (line 584) | def from_config(cls, arch: dict):
  class RoPEUNet2DConditionModel (line 591) | class RoPEUNet2DConditionModel(HDUNet2DConditionModel):
    method __init__ (line 592) | def __init__(self, *args, **kwargs):
    method from_config (line 600) | def from_config(cls, arch: dict):
    method forward (line 606) | def forward(self, *args, **kwargs):

FILE: pipelines/hdm/hdm/modules/xut.py
  class XUDiTConditionModel (line 11) | class XUDiTConditionModel(ModelMixin, ConfigMixin):
    method __init__ (line 15) | def __init__(
    method from_config (line 61) | def from_config(cls, config: Dict[str, Any] | str) -> "XUDiTConditionM...
    method enable_gradient_checkpointing (line 67) | def enable_gradient_checkpointing(self):
    method disable_gradient_checkpointing (line 70) | def disable_gradient_checkpointing(self):
    method forward (line 73) | def forward(

FILE: pipelines/hdm/hdm/pipeline.py
  class HDMXUTPipeline (line 13) | class HDMXUTPipeline(DiffusionPipeline):
    method __init__ (line 19) | def __init__(
    method apply_compile (line 38) | def apply_compile(self, *args, **kwargs):
    method __call__ (line 52) | def __call__(

FILE: pipelines/hdm/hdm/trainer/callbacks.py
  class ImageGenCallback (line 11) | class ImageGenCallback(Callback):
    method __init__ (line 12) | def __init__(self, config, img_gen_func):
    method on_train_batch_start (line 24) | def on_train_batch_start(

FILE: pipelines/hdm/hdm/trainer/diffusion.py
  function get_noise_noisy_latents_and_timesteps (line 10) | def get_noise_noisy_latents_and_timesteps(
  function apply_snr_weight (line 36) | def apply_snr_weight(loss, timesteps, noise_scheduler, gamma, v_predicti...
  function apply_debiased_estimation (line 47) | def apply_debiased_estimation(loss, timesteps, noise_scheduler):
  function prepare_scheduler_for_custom_training (line 57) | def prepare_scheduler_for_custom_training(noise_scheduler, device):

FILE: pipelines/hdm/hdm/trainer/trainer.py
  class BaseTrainer (line 25) | class BaseTrainer(pl.LightningModule):
    method __init__ (line 26) | def __init__(
    method configure_optimizers (line 57) | def configure_optimizers(self):
  class DMTrainer (line 92) | class DMTrainer(BaseTrainer):
    method __init__ (line 93) | def __init__(
    method on_train_epoch_end (line 173) | def on_train_epoch_end(self) -> None:
    method training_step (line 202) | def training_step(self, batch, idx):
  class FlowTrainer (line 268) | class FlowTrainer(BaseTrainer):
    method __init__ (line 269) | def __init__(
    method on_train_epoch_end (line 362) | def on_train_epoch_end(self) -> None:
    method training_step (line 391) | def training_step(self, batch, idx):

FILE: pipelines/hdm/hdm/utils/__init__.py
  function get_obj_from_str (line 10) | def get_obj_from_str(string, reload=False):
  function instantiate (line 18) | def instantiate(obj):
  function exists (line 31) | def exists(val):
  function uniq (line 35) | def uniq(arr):
  function default (line 39) | def default(val, d):
  function zero_module (line 45) | def zero_module(module: nn.Module):
  function random_choice (line 54) | def random_choice(
  function count_params (line 64) | def count_params(model, verbose=False):
  function remove_none (line 71) | def remove_none(list_x):

FILE: pipelines/hdm/hdm/utils/config.py
  function load_train_config (line 6) | def load_train_config(file):

FILE: pipelines/hdm/xut/modules/adaln.py
  class AdaLN (line 9) | class AdaLN(nn.Module):
    method __init__ (line 10) | def __init__(self, dim, y_dim, gate=True, norm_layer=RMSNorm, shared=F...
    method forward (line 21) | def forward(self, x, y, shared_adaln=None):

FILE: pipelines/hdm/xut/modules/attention.py
  function memory_efficient_attention (line 29) | def memory_efficient_attention(query, key, value, attn_bias=None, p=0.0):
  class SelfAttention (line 44) | class SelfAttention(nn.Module):
    method __init__ (line 45) | def __init__(self, dim, n_heads=8, head_dim=-1, pos_dim=2):
    method forward (line 61) | def forward(self, x, pos_map=None, mask=None):
  class CrossAttention (line 104) | class CrossAttention(nn.Module):
    method __init__ (line 105) | def __init__(self, dim, ctx_dim, n_heads=8, head_dim=-1, pos_dim=2):
    method forward (line 122) | def forward(self, x, ctx, pos_map=None, ctx_pos_map=None, mask=None):
  class AttentionPooling (line 166) | class AttentionPooling(CrossAttention):
    method __init__ (line 167) | def __init__(self, dim, n_heads=8, head_dim=-1, pos_dim=2):
    method forward (line 171) | def forward(self, x, pos_map=None, mask=None):
  class AttentiveProbe (line 176) | class AttentiveProbe(CrossAttention):
    method __init__ (line 177) | def __init__(self, dim, out_dim, n_heads=8, head_dim=-1, pos_dim=2, n_...
    method forward (line 182) | def forward(self, x, pos_map=None, mask=None):
  function prefix_causal_attention_mask (line 190) | def prefix_causal_attention_mask(

FILE: pipelines/hdm/xut/modules/axial_rope.py
  function rotate_half (line 11) | def rotate_half(x):
  function apply_rotary_emb (line 19) | def apply_rotary_emb(freqs, t, start_index=0, scale=1.0):
  function centers (line 35) | def centers(start, stop, num, dtype=None, device=None):
  function make_grid (line 40) | def make_grid(h_pos, w_pos):
  function bounding_box (line 45) | def bounding_box(h, w, pixel_aspect_ratio=1.0):
  function make_axial_pos (line 64) | def make_axial_pos(
  function make_axial_pos_no_cache (line 77) | def make_axial_pos_no_cache(
  function make_cropped_pos (line 90) | def make_cropped_pos(crop_h, crop_w, target_h, target_w):
  function freqs_pixel (line 101) | def freqs_pixel(max_freq=10.0):
  function freqs_pixel_log (line 109) | def freqs_pixel_log(max_freq=10.0):
  class AxialRoPE (line 118) | class AxialRoPE(nn.Module):
    method __init__ (line 119) | def __init__(
    method extra_repr (line 133) | def extra_repr(self):
    method get_freqs (line 137) | def get_freqs(self, pos):
    method forward (line 145) | def forward(self, x, pos):
  class AdditiveAxialRoPE (line 150) | class AdditiveAxialRoPE(AxialRoPE):
    method __init__ (line 155) | def __init__(
    method forward (line 166) | def forward(self, x, pos):

FILE: pipelines/hdm/xut/modules/layers.py
  class SwiGLUTorch (line 16) | class SwiGLUTorch(nn.Module):
    method __init__ (line 17) | def __init__(
    method forward (line 32) | def forward(self, x):

FILE: pipelines/hdm/xut/modules/norm.py
  class DyT (line 14) | class DyT(nn.Module):
    method __init__ (line 20) | def __init__(self, hidden_size, init_alpha=1.0):
    method forward (line 26) | def forward(self, hidden_states):
  class RMSNormTorch (line 31) | class RMSNormTorch(nn.RMSNorm):
    method __init__ (line 32) | def __init__(self, hidden_size, *args, eps=1e-6, offset=0.0, **kwargs):
    method forward (line 37) | def forward(self, hidden_states):
  class RMSNorm (line 54) | class RMSNorm(LigerRMSNorm):
    method __init__ (line 55) | def __init__(
    method forward (line 73) | def forward(self, hidden_states):
  function Norm (line 77) | def Norm(module: nn.Module):

FILE: pipelines/hdm/xut/modules/patch.py
  class PatchEmbed (line 6) | class PatchEmbed(nn.Module):
    method __init__ (line 7) | def __init__(
    method forward (line 23) | def forward(self, x, pos_map=None):
  class UnPatch (line 44) | class UnPatch(nn.Module):
    method __init__ (line 45) | def __init__(self, patch_size=4, input_dim=512, out_channel=3, proj=Tr...
    method forward (line 55) | def forward(self, x: torch.Tensor, axis1=None, axis2=None, loss_mask=N...

FILE: pipelines/hdm/xut/modules/time_emb.py
  class TimestepEmbedding (line 9) | class TimestepEmbedding(nn.Module):
    method __init__ (line 10) | def __init__(self, dim, max_period=10000, time_factor: float = 1000.0):
    method forward (line 26) | def forward(self, t):

FILE: pipelines/hdm/xut/modules/transformer.py
  class TransformerBlock (line 9) | class TransformerBlock(nn.Module):
    method __init__ (line 10) | def __init__(
    method forward (line 51) | def forward(

FILE: pipelines/hdm/xut/utils/__init__.py
  function isiterable (line 5) | def isiterable(obj):
  function compile_wrapper (line 13) | def compile_wrapper(func, **kwargs):

FILE: pipelines/hdm/xut/xut.py
  class TBackBone (line 15) | class TBackBone(nn.Module):
    method __init__ (line 20) | def __init__(
    method init_weight (line 52) | def init_weight(self):
    method forward (line 67) | def forward(
  class XUTBackBone (line 100) | class XUTBackBone(nn.Module):
    method __init__ (line 105) | def __init__(
    method init_weight (line 173) | def init_weight(self):
    method forward (line 188) | def forward(
  class XUDiT (line 274) | class XUDiT(nn.Module):
    method __init__ (line 279) | def __init__(
    method init_weight (line 401) | def init_weight(self):
    method set_grad_ckpt (line 409) | def set_grad_ckpt(self, grad_ckpt):
    method forward (line 416) | def forward(

FILE: pipelines/hidream/pipeline_hidream_image_editing.py
  function retrieve_latents (line 81) | def retrieve_latents(
  function calculate_shift (line 95) | def calculate_shift(
  function retrieve_timesteps (line 109) | def retrieve_timesteps(
  class HiDreamImageEditingPipeline (line 168) | class HiDreamImageEditingPipeline(DiffusionPipeline, HiDreamImageLoraLoa...
    method __init__ (line 172) | def __init__(
    method _get_t5_prompt_embeds (line 211) | def _get_t5_prompt_embeds(
    method _get_clip_prompt_embeds (line 248) | def _get_clip_prompt_embeds(
    method _get_llama3_prompt_embeds (line 285) | def _get_llama3_prompt_embeds(
    method encode_prompt (line 329) | def encode_prompt(
    method enable_vae_slicing (line 528) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 535) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 542) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 550) | def disable_vae_tiling(self):
    method check_inputs (line 557) | def check_inputs(
    method prepare_latents (line 666) | def prepare_latents(
    method prepare_image_latents (line 693) | def prepare_image_latents(
    method guidance_scale (line 736) | def guidance_scale(self):
    method image_guidance_scale (line 740) | def image_guidance_scale(self):
    method do_classifier_free_guidance (line 744) | def do_classifier_free_guidance(self):
    method attention_kwargs (line 748) | def attention_kwargs(self):
    method num_timesteps (line 752) | def num_timesteps(self):
    method interrupt (line 756) | def interrupt(self):
    method __call__ (line 761) | def __call__(

FILE: pipelines/meissonic/pipeline.py
  function _prepare_latent_image_ids (line 37) | def _prepare_latent_image_ids(batch_size, height, width, device, dtype):
  class MeissonicPipeline (line 51) | class MeissonicPipeline(DiffusionPipeline):
    method __init__ (line 63) | def __init__(
    method __call__ (line 89) | def __call__(

FILE: pipelines/meissonic/pipeline_img2img.py
  function _prepare_latent_image_ids (line 34) | def _prepare_latent_image_ids(batch_size, height, width, device, dtype):
  class MeissonicImg2ImgPipeline (line 49) | class MeissonicImg2ImgPipeline(DiffusionPipeline):
    method __init__ (line 61) | def __init__(
    method __call__ (line 83) | def __call__(

FILE: pipelines/meissonic/pipeline_inpaint.py
  function _prepare_latent_image_ids (line 31) | def _prepare_latent_image_ids(batch_size, height, width, device, dtype):
  class MeissonicInpaintPipeline (line 46) | class MeissonicInpaintPipeline(DiffusionPipeline):
    method __init__ (line 58) | def __init__(
    method __call__ (line 88) | def __call__(

FILE: pipelines/meissonic/scheduler.py
  function gumbel_noise (line 25) | def gumbel_noise(t, generator=None):
  function mask_by_random_topk (line 35) | def mask_by_random_topk(mask_len, probs, temperature=1.0, generator=None):
  class SchedulerOutput (line 44) | class SchedulerOutput(BaseOutput):
  class Scheduler (line 61) | class Scheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 67) | def __init__(
    method set_timesteps (line 75) | def set_timesteps(
    method step (line 88) | def step(
    method add_noise (line 163) | def add_noise(self, sample, timesteps, generator=None):

FILE: pipelines/meissonic/transformer.py
  function get_3d_rotary_pos_embed (line 46) | def get_3d_rotary_pos_embed(
  function get_2d_rotary_pos_embed (line 130) | def get_2d_rotary_pos_embed(embed_dim, crops_coords, grid_size, use_real...
  function get_2d_rotary_pos_embed_from_grid (line 158) | def get_2d_rotary_pos_embed_from_grid(embed_dim, grid, use_real=False):
  function get_2d_rotary_pos_embed_lumina (line 178) | def get_2d_rotary_pos_embed_lumina(embed_dim, len_h, len_w, linear_facto...
  function get_1d_rotary_pos_embed (line 194) | def get_1d_rotary_pos_embed(
  class FluxPosEmbed (line 251) | class FluxPosEmbed(nn.Module):
    method __init__ (line 253) | def __init__(self, theta: int, axes_dim: List[int]):
    method forward (line 258) | def forward(self, ids: torch.Tensor) -> torch.Tensor:
  class FusedFluxAttnProcessor2_0 (line 277) | class FusedFluxAttnProcessor2_0:
    method __init__ (line 280) | def __init__(self):
    method __call__ (line 286) | def __call__(
  class SingleTransformerBlock (line 367) | class   SingleTransformerBlock(nn.Module):
    method __init__ (line 381) | def __init__(self, dim, num_attention_heads, attention_head_dim, mlp_r...
    method forward (line 404) | def forward(
  class TransformerBlock (line 429) | class TransformerBlock(nn.Module):
    method __init__ (line 443) | def __init__(self, dim, num_attention_heads, attention_head_dim, qk_no...
    method forward (line 482) | def forward(
  class UVit2DConvEmbed (line 529) | class UVit2DConvEmbed(nn.Module):
    method __init__ (line 530) | def __init__(self, in_channels, block_out_channels, vocab_size, elemen...
    method forward (line 536) | def forward(self, input_ids):
  class ConvMlmLayer (line 543) | class ConvMlmLayer(nn.Module):
    method __init__ (line 544) | def __init__(
    method forward (line 558) | def forward(self, hidden_states):
  class SwiGLU (line 564) | class SwiGLU(nn.Module):
    method __init__ (line 575) | def __init__(self, dim_in: int, dim_out: int, bias: bool = True):
    method forward (line 580) | def forward(self, hidden_states):
  class ConvNextBlock (line 585) | class ConvNextBlock(nn.Module):
    method __init__ (line 586) | def __init__(
    method forward (line 606) | def forward(self, x, cond_embeds):
  class Simple_UVitBlock (line 629) | class Simple_UVitBlock(nn.Module):
    method __init__ (line 630) | def __init__(
    method forward (line 672) | def forward(self, x):
  class UVitBlock (line 681) | class UVitBlock(nn.Module):
    method __init__ (line 682) | def __init__(
    method forward (line 760) | def forward(self, x, pooled_text_emb, encoder_hidden_states, cross_att...
  class Transformer2DModel (line 779) | class Transformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMixin, From...
    method __init__ (line 803) | def __init__(
    method attn_processors (line 900) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 924) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method fuse_qkv_projections (line 959) | def fuse_qkv_projections(self):
    method unfuse_qkv_projections (line 985) | def unfuse_qkv_projections(self):
    method _set_gradient_checkpointing (line 998) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 1002) | def forward(

FILE: pipelines/model_anima.py
  function _import_from_file (line 10) | def _import_from_file(module_name, file_path):
  function load_anima (line 17) | def load_anima(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_auraflow.py
  function load_auraflow (line 7) | def load_auraflow(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_bria.py
  function load_bria (line 9) | def load_bria(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_chroma.py
  function load_chroma (line 7) | def load_chroma(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_chrono.py
  function postprocess (line 7) | def postprocess(p, result): # pylint: disable=unused-argument
  function load_chrono (line 14) | def load_chrono(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_cogview.py
  function load_cogview3 (line 7) | def load_cogview3(checkpoint_info, diffusers_load_config=None):
  function load_cogview4 (line 33) | def load_cogview4(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_cosmos.py
  function load_cosmos_t2i (line 7) | def load_cosmos_t2i(checkpoint_info, diffusers_load_config=None):
  class Fake_safety_checker (line 40) | class Fake_safety_checker:
    method __init__ (line 41) | def __init__(self):
    method __call__ (line 45) | def __call__(self, *args, **kwargs): # pylint: disable=unused-argument
    method to (line 48) | def to(self, _device):
    method check_text_safety (line 51) | def check_text_safety(self, _prompt):
    method check_video_safety (line 54) | def check_video_safety(self, vid):

FILE: pipelines/model_flex.py
  function load_flex (line 7) | def load_flex(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_flite.py
  function load_flite (line 8) | def load_flite(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_flux.py
  function load_flux (line 8) | def load_flux(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_flux2.py
  function load_flux2 (line 7) | def load_flux2(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_flux2_klein.py
  function load_flux2_klein (line 7) | def load_flux2_klein(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_glm.py
  class GLMTokenProgressProcessor (line 9) | class GLMTokenProgressProcessor(transformers.LogitsProcessor):
    method __init__ (line 12) | def __init__(self):
    method set_total (line 20) | def set_total(self, total_tokens: int):
    method __call__ (line 24) | def __call__(self, input_ids, scores):
  function hijack_vision_language_generate (line 57) | def hijack_vision_language_generate(pipe):
  function load_glm_image (line 83) | def load_glm_image(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_google.py
  function google_requirements (line 28) | def google_requirements():
  function get_size_buckets (line 34) | def get_size_buckets(width: int, height: int) -> str:
  class GoogleNanoBananaPipeline (line 43) | class GoogleNanoBananaPipeline():
    method __init__ (line 44) | def __init__(self, model_name: str):
    method txt2img (line 51) | def txt2img(self, prompt):
    method img2img (line 58) | def img2img(self, prompt, image):
    method get_args (line 71) | def get_args(self):
    method __call__ (line 111) | def __call__(self, prompt: list[str], width: int, height: int, image: ...
  function load_nanobanana (line 165) | def load_nanobanana(checkpoint_info, diffusers_load_config): # pylint: d...

FILE: pipelines/model_hdm.py
  function load_hdm (line 7) | def load_hdm(checkpoint_info, diffusers_load_config=None): # pylint: dis...

FILE: pipelines/model_hidream.py
  function load_llama (line 7) | def load_llama(diffusers_load_config=None):
  function load_hidream (line 33) | def load_hidream(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_hunyuandit.py
  function load_hunyuandit (line 7) | def load_hunyuandit(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_hyimage.py
  function load_hyimage (line 9) | def load_hyimage(checkpoint_info, diffusers_load_config=None): # pylint:...
  function load_hyimage3 (line 44) | def load_hyimage3(checkpoint_info, diffusers_load_config=None): # pylint...
  class HunyuanImage3Wrapper (line 75) | class HunyuanImage3Wrapper(torch.nn.Module):
    method __init__ (line 76) | def __init__(self, model):
    method __call__ (line 80) | def __call__(

FILE: pipelines/model_kandinsky.py
  function load_kandinsky21 (line 7) | def load_kandinsky21(checkpoint_info, diffusers_load_config=None):
  function load_kandinsky22 (line 25) | def load_kandinsky22(checkpoint_info, diffusers_load_config=None):
  function load_kandinsky3 (line 43) | def load_kandinsky3(checkpoint_info, diffusers_load_config=None):
  function load_kandinsky5 (line 76) | def load_kandinsky5(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_kolors.py
  function load_kolors (line 6) | def load_kolors(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_longcat.py
  function load_longcat (line 7) | def load_longcat(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_lumina.py
  function load_lumina (line 7) | def load_lumina(checkpoint_info, diffusers_load_config=None):
  function load_lumina2 (line 25) | def load_lumina2(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_meissonic.py
  function load_meissonic (line 6) | def load_meissonic(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_nextstep.py
  function load_nextstep (line 6) | def load_nextstep(checkpoint_info, diffusers_load_config=None): # pylint...

FILE: pipelines/model_omnigen.py
  function load_omnigen (line 5) | def load_omnigen(checkpoint_info, diffusers_load_config=None): # pylint:...
  function load_omnigen2 (line 35) | def load_omnigen2(checkpoint_info, diffusers_load_config=None): # pylint...

FILE: pipelines/model_ovis.py
  function load_ovis (line 7) | def load_ovis(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_pixart.py
  function load_pixart (line 8) | def load_pixart(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_prx.py
  function load_prx (line 6) | def load_prx(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_qwen.py
  function load_qwen (line 6) | def load_qwen(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_sana.py
  function load_quants (line 7) | def load_quants(kwargs, repo_id, cache_dir):
  function load_sana (line 24) | def load_sana(checkpoint_info, kwargs=None):

FILE: pipelines/model_sd3.py
  function load_sd3 (line 7) | def load_sd3(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_stablecascade.py
  function get_timestep_ratio_conditioning (line 7) | def get_timestep_ratio_conditioning(t, alphas_cumprod):
  function load_text_encoder (line 18) | def load_text_encoder(path):
  function load_prior (line 64) | def load_prior(path, config_file="default"):
  function load_cascade_combined (line 87) | def load_cascade_combined(checkpoint_info, diffusers_load_config=None):
  class StableCascadeDecoderPipelineFixed (line 167) | class StableCascadeDecoderPipelineFixed(diffusers.StableCascadeDecoderPi...
    method guidance_scale (line 168) | def guidance_scale(self): # pylint: disable=invalid-overridden-method
    method do_classifier_free_guidance (line 171) | def do_classifier_free_guidance(self): # pylint: disable=invalid-overr...
    method __call__ (line 175) | def __call__(

FILE: pipelines/model_wanai.py
  function load_transformer (line 7) | def load_transformer(repo_id, diffusers_load_config=None, subfolder='tra...
  function load_text_encoder (line 50) | def load_text_encoder(repo_id, diffusers_load_config=None):
  function load_wan (line 68) | def load_wan(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_xomni.py
  class XOmniPipeline (line 7) | class XOmniPipeline(diffusers.DiffusionPipeline):
    method __init__ (line 8) | def __init__(
    method load (line 21) | def load(
    method __call__ (line 50) | def __call__(
  function load_xomni (line 107) | def load_xomni(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/model_z_image.py
  function load_nunchaku (line 7) | def load_nunchaku():
  function load_z_image (line 21) | def load_z_image(checkpoint_info, diffusers_load_config=None):

FILE: pipelines/omnigen2/image_processor.py
  class OmniGen2ImageProcessor (line 25) | class OmniGen2ImageProcessor(VaeImageProcessor):
    method __init__ (line 48) | def __init__(
    method get_new_height_width (line 71) | def get_new_height_width(
    method preprocess (line 134) | def preprocess(

FILE: pipelines/omnigen2/models/attention_processor.py
  class OmniGen2AttnProcessor (line 31) | class OmniGen2AttnProcessor:
    method __init__ (line 48) | def __init__(self) -> None:
    method __call__ (line 56) | def __call__(

FILE: pipelines/omnigen2/models/embeddings.py
  function apply_rotary_emb (line 24) | def apply_rotary_emb(
  function apply_rotary_emb (line 73) | def apply_rotary_emb(x, freqs_cis, use_real: bool = True, use_real_unbin...

FILE: pipelines/omnigen2/models/transformers/block_lumina2.py
  class Lumina2CombinedTimestepCaptionEmbedding (line 28) | class Lumina2CombinedTimestepCaptionEmbedding(nn.Module):
    method __init__ (line 29) | def __init__(
    method _initialize_weights (line 54) | def _initialize_weights(self):
    method forward (line 58) | def forward(

FILE: pipelines/omnigen2/models/transformers/repo.py
  class OmniGen2RotaryPosEmbed (line 9) | class OmniGen2RotaryPosEmbed(nn.Module):
    method __init__ (line 10) | def __init__(self, theta: int,
    method get_freqs_cis (line 21) | def get_freqs_cis(axes_dim: Tuple[int, int, int],
    method _get_freqs_cis (line 31) | def _get_freqs_cis(self, freqs_cis, ids: torch.Tensor) -> torch.Tensor:
    method forward (line 43) | def forward(

FILE: pipelines/omnigen2/models/transformers/transformer_omnigen2.py
  class OmniGen2TransformerBlock (line 27) | class OmniGen2TransformerBlock(nn.Module):
    method __init__ (line 49) | def __init__(
    method initialize_weights (line 103) | def initialize_weights(self) -> None:
    method forward (line 122) | def forward(
  class OmniGen2Transformer2DModel (line 171) | class OmniGen2Transformer2DModel(ModelMixin, ConfigMixin, PeftAdapterMix...
    method __init__ (line 206) | def __init__(
    method initialize_weights (line 336) | def initialize_weights(self) -> None:
    method img_patch_embed_and_refine (line 355) | def img_patch_embed_and_refine(
    method flat_and_pad_to_seq (line 423) | def flat_and_pad_to_seq(self, hidden_states, ref_image_hidden_states):
    method forward (line 489) | def forward(

FILE: pipelines/omnigen2/pipeline_omnigen2.py
  class FMPipelineOutput (line 52) | class FMPipelineOutput(BaseOutput):
  function retrieve_timesteps (line 65) | def retrieve_timesteps(
  class OmniGen2Pipeline (line 111) | class OmniGen2Pipeline(DiffusionPipeline):
    method __init__ (line 131) | def __init__(
    method prepare_latents (line 164) | def prepare_latents(
    method encode_vae (line 202) | def encode_vae(self, img: torch.FloatTensor) -> torch.FloatTensor:
    method prepare_image (line 220) | def prepare_image(
    method _get_qwen2_prompt_embeds (line 259) | def _get_qwen2_prompt_embeds(
    method _apply_chat_template (line 326) | def _apply_chat_template(self, prompt: str):
    method encode_prompt (line 337) | def encode_prompt(
    method num_timesteps (line 436) | def num_timesteps(self):
    method text_guidance_scale (line 440) | def text_guidance_scale(self):
    method image_guidance_scale (line 444) | def image_guidance_scale(self):
    method cfg_range (line 448) | def cfg_range(self):
    method __call__ (line 452) | def __call__(
    method processing (line 597) | def processing(
    method predict (line 692) | def predict(

FILE: pipelines/qwen/qwen_nunchaku.py
  function load_qwen_nunchaku (line 4) | def load_qwen_nunchaku(repo_id):

FILE: pipelines/qwen/qwen_pruning.py
  function check_qwen_pruning (line 1) | def check_qwen_pruning(repo_id, subfolder):

FILE: pipelines/segmoe/segmoe_model.py
  function remove_all_forward_hooks (line 23) | def remove_all_forward_hooks(model: torch.nn.Module) -> None:
  class SparseMoeBlock (line 32) | class SparseMoeBlock(nn.Module):
    method __init__ (line 33) | def __init__(self, config, experts):
    method forward (line 44) | def forward(self, hidden_states: torch.Tensor, scale=None) -> torch.Te...
  function getActivation (line 82) | def getActivation(activation, name):
  class SegMoEPipeline (line 89) | class SegMoEPipeline:
    method __init__ (line 90) | def __init__(self, config_or_path, **kwargs) -> Any:
    method to (line 139) | def to(self, *args, **kwargs):
    method load_from_scratch (line 142) | def load_from_scratch(self, config: str, **kwargs) -> None:
    method __call__ (line 860) | def __call__(self, *args: Any, **kwds: Any) -> Any:
    method create_empty (line 868) | def create_empty(self, path):
    method save_pretrained (line 1154) | def save_pretrained(self, path):
    method cast_hook (line 1173) | def cast_hook(self, pipe, dicts):
    method get_hidden_states (line 1261) | def get_hidden_states(self, model, positive, negative, average: bool =...
    method get_gate_params (line 1282) | def get_gate_params(

FILE: pipelines/wan/wan_image.py
  class WanImagePipeline (line 10) | class WanImagePipeline(diffusers.WanPipeline):
    method __call__ (line 11) | def __call__(
    method get_timesteps (line 80) | def get_timesteps(self, num_inference_steps, strength):
    method img2img_prepare_latents (line 89) | def img2img_prepare_latents(

FILE: pipelines/xomni/configuration_xomni.py
  class XOmniConfig (line 5) | class XOmniConfig(Qwen2Config):
    method __init__ (line 8) | def __init__(

FILE: pipelines/xomni/modeling_siglip_flux.py
  function drop_token (line 16) | def drop_token(x, drop_prob: float = 0., training: bool = False, scale_b...
  class FluxTransformer2DModelWithSigLIP (line 27) | class FluxTransformer2DModelWithSigLIP(FluxTransformer2DModel):
    method __init__ (line 29) | def __init__(
    method init_siglip_embed (line 62) | def init_siglip_embed(self, siglip_channels):
    method forward (line 66) | def forward(
  function teacache_forward (line 237) | def teacache_forward(
  class FluxPipelineWithSigLIP (line 499) | class FluxPipelineWithSigLIP(FluxPipeline):
    method __call__ (line 502) | def __call__(

FILE: pipelines/xomni/modeling_siglip_tokenizer.py
  function create_anyres_preprocess (line 15) | def create_anyres_preprocess(
  class IBQ (line 63) | class IBQ(nn.Module):
    method __init__ (line 64) | def __init__(self, n_e, e_dim, skip_quantization_prob=0.0, quantizatio...
    method forward (line 79) | def forward(self, z, temp=None, rescale_logits=False, return_logits=Fa...
    method get_codebook_entry (line 132) | def get_codebook_entry(self, indices, bhwc):
  class ResidualBlock (line 145) | class ResidualBlock(nn.Module):
    method __init__ (line 146) | def __init__(self, channels, num_groups=32):
    method forward (line 154) | def forward(self, x):
  class VQConvProjector (line 165) | class VQConvProjector(nn.Module):
    method __init__ (line 166) | def __init__(
    method forward (line 182) | def forward(self, x, h, w):
    method encode (line 191) | def encode(self, x, h, w):
    method decode (line 197) | def decode(self, tokens, bhwc):
  class SiglipTokenizer (line 204) | class SiglipTokenizer(nn.Module):
    method __init__ (line 205) | def __init__(
    method encode (line 225) | def encode(self, x):
    method decode (line 230) | def decode(self, tokens, bhwc):

FILE: pipelines/xomni/modeling_vit.py
  function _no_grad_trunc_normal_ (line 24) | def _no_grad_trunc_normal_(tensor, mean, std, a, b):
  function trunc_normal_ (line 62) | def trunc_normal_(tensor, mean=0.0, std=1.0, a=-2.0, b=2.0):
  function init_weights (line 90) | def init_weights(self):
  function init_weights_vit_timm (line 96) | def init_weights_vit_timm(module: nn.Module, name: str = "") -> None:
  class Attention (line 106) | class Attention(nn.Module):
    method __init__ (line 109) | def __init__(
    method forward (line 134) | def forward(self, x: torch.Tensor, cu_slens=None) -> torch.Tensor:
  class LayerScale (line 177) | class LayerScale(nn.Module):
    method __init__ (line 178) | def __init__(
    method forward (line 188) | def forward(self, x: torch.Tensor) -> torch.Tensor:
  class Block (line 192) | class Block(nn.Module):
    method __init__ (line 193) | def __init__(
    method forward (line 236) | def forward(self, x: torch.Tensor, cu_slens=None) -> torch.Tensor:
  class VisionTransformer (line 242) | class VisionTransformer(nn.Module):
    method __init__ (line 251) | def __init__(
    method init_weights (line 398) | def init_weights(self, mode: Literal["jax", "jax_nlhb", "moco", ""] = ...
    method no_weight_decay (line 407) | def no_weight_decay(self) -> Set:
    method group_matcher (line 411) | def group_matcher(self, coarse: bool = False) -> Dict:
    method set_grad_checkpointing (line 418) | def set_grad_checkpointing(self, enable: bool = True) -> None:
    method get_classifier (line 422) | def get_classifier(self) -> nn.Module:
    method reset_classifier (line 425) | def reset_classifier(self, num_classes: int, global_pool=None) -> None:
    method rescale_positional_embedding (line 440) | def rescale_positional_embedding(self, out_size):
    method _pos_embed (line 452) | def _pos_embed(self, x: torch.Tensor) -> torch.Tensor:
    method _intermediate_layers (line 485) | def _intermediate_layers(
    method get_intermediate_layers (line 507) | def get_intermediate_layers(
    method forward_features_list (line 538) | def forward_features_list(self, x_list):
    method forward_features (line 577) | def forward_features(self, x: torch.Tensor) -> torch.Tensor:
    method forward_head (line 593) | def forward_head(self, x: torch.Tensor, pre_logits: bool = False) -> t...
    method forward (line 605) | def forward(self, x, cal_attn_pool=False):
  class SigLIPVisionCfg (line 614) | class SigLIPVisionCfg:
  function resize_evaclip_pos_embed (line 651) | def resize_evaclip_pos_embed(model: VisionTransformer, interpolation: st...
  function create_siglip_vit (line 664) | def create_siglip_vit(

FILE: pipelines/xomni/modeling_xomni.py
  class XOmniDecoderLayer (line 19) | class XOmniDecoderLayer(Qwen2DecoderLayer):
    method __init__ (line 20) | def __init__(self, config: XOmniConfig, layer_idx: int):
    method forward (line 25) | def forward(
  class XOmniModel (line 43) | class XOmniModel(Qwen2Model, Qwen2PreTrainedModel):
    method __init__ (line 47) | def __init__(self, config: XOmniConfig):
    method get_input_embeddings (line 67) | def get_input_embeddings(self):
    method set_input_embeddings (line 70) | def set_input_embeddings(self, value):
    method embed_tokens (line 73) | def embed_tokens(self, input_ids):
    method norm (line 89) | def norm(self, hidden_states):
  class XOmniForCausalLM (line 94) | class XOmniForCausalLM(Qwen2ForCausalLM):
    method __init__ (line 100) | def __init__(self, config):
    method device (line 111) | def device(self):
    method init_vision (line 114) | def init_vision(self, flux_pipe_path, **kwargs):
    method set_generation_mode (line 150) | def set_generation_mode(self, mode):
    method mmencode (line 154) | def mmencode(self, tokenizer, texts=None, images=None, **kwargs):
    method mmdecode (line 165) | def mmdecode(self, tokenizer, token_ids, force_text=None, **kwargs):
    method tokenize_image (line 202) | def tokenize_image(self, image):
    method detokenize_image (line 218) | def detokenize_image(self, texts, images, token_ids, shape):
    method forward (line 240) | def forward(

FILE: scripts/animatediff.py
  function set_adapter (line 43) | def set_adapter(adapter_name: str = 'None'):
  function set_scheduler (line 138) | def set_scheduler(p, model, override: bool = False):
  function set_prompt (line 148) | def set_prompt(p):
  function set_lora (line 166) | def set_lora(p, lora, strength):
  function set_free_init (line 179) | def set_free_init(method, iters, order, spatial, temporal):
  function set_free_noise (line 192) | def set_free_noise(frames):
  class Script (line 200) | class Script(scripts_manager.Script):
    method title (line 201) | def title(self):
    method show (line 204) | def show(self, is_img2img):
    method ui (line 208) | def ui(self, is_img2img):
    method run (line 236) | def run(self, p: processing.StableDiffusionProcessing, adapter_index, ...
    method after (line 264) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/apg.py
  class Script (line 8) | class Script(scripts_manager.Script):
    method __init__ (line 9) | def __init__(self):
    method title (line 14) | def title(self):
    method show (line 17) | def show(self, is_img2img):
    method ui (line 20) | def ui(self, _is_img2img): # ui elements
    method register (line 29) | def register(self): # register xyz grid elements
    method run (line 53) | def run(self, p: processing.StableDiffusionProcessing, eta = 0.0, mome...
    method after (line 78) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/automatic_color_inpaint.py
  class Script (line 31) | class Script(scripts_manager.Script):
    method title (line 32) | def title(self):
    method show (line 35) | def show(self, is_img2img):
    method ui (line 39) | def ui(self, _is_img2img):
    method run (line 90) | def run(self, p: processing.StableDiffusionProcessing, *args):  # pyli...

FILE: scripts/blipdiffusion.py
  class Script (line 5) | class Script(scripts_manager.Script):
    method title (line 6) | def title(self):
    method show (line 9) | def show(self, is_img2img):
    method ui (line 12) | def ui(self, _is_img2img):
    method run (line 23) | def run(self, p: processing.StableDiffusionProcessing, source_subject,...

FILE: scripts/consistory/attention_processor.py
  class ConsistoryAttnStoreProcessor (line 28) | class ConsistoryAttnStoreProcessor:
    method __init__ (line 29) | def __init__(self, attnstore, place_in_unet):
    method __call__ (line 34) | def __call__(self, attn: Attention, hidden_states, encoder_hidden_stat...
  class ConsistoryExtendedAttnXFormersAttnProcessor (line 67) | class ConsistoryExtendedAttnXFormersAttnProcessor:
    method __init__ (line 79) | def __init__(self, place_in_unet, attnstore, extended_attn_kwargs, att...
    method __call__ (line 88) | def __call__(
  function register_extended_self_attn (line 256) | def register_extended_self_attn(unet, attnstore, extended_attn_kwargs):

FILE: scripts/consistory/consistory_pipeline.py
  class ConsistoryExtendAttnSDXLPipeline (line 46) | class ConsistoryExtendAttnSDXLPipeline(
    method __call__ (line 53) | def __call__(

FILE: scripts/consistory/consistory_run.py
  function load_pipeline (line 19) | def load_pipeline(gpu_id=0):
  function create_anchor_mapping (line 30) | def create_anchor_mapping(bsz, anchor_indices=[0]):
  function create_token_indices (line 37) | def create_token_indices(prompts, batch_size, concept_token, tokenizer):
  function create_latents (line 49) | def create_latents(story_pipeline, seed, batch_size, same_latent, device...
  function run_batch_generation (line 68) | def run_batch_generation(story_pipeline, prompts, concept_token,
  function run_anchor_generation (line 128) | def run_anchor_generation(story_pipeline, prompts, concept_token,
  function run_extra_generation (line 194) | def run_extra_generation(story_pipeline, prompts, concept_token,

FILE: scripts/consistory/consistory_unet_sdxl.py
  class UNet2DConditionOutput (line 65) | class UNet2DConditionOutput(BaseOutput):
  class ConsistorySDXLUNet2DConditionModel (line 77) | class ConsistorySDXLUNet2DConditionModel(ModelMixin, ConfigMixin, UNet2D...
    method __init__ (line 174) | def __init__(
    method attn_processors (line 630) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 653) | def set_attn_processor(
    method set_default_attn_processor (line 689) | def set_default_attn_processor(self):
    method set_attention_slice (line 704) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 769) | def _set_gradient_checkpointing(self, module, value=False):
    method enable_freeu (line 773) | def enable_freeu(self, s1, s2, b1, b2):
    method disable_freeu (line 797) | def disable_freeu(self):
    method forward (line 805) | def forward(

FILE: scripts/consistory/consistory_utils.py
  class FeatureInjector (line 13) | class FeatureInjector:
    method __init__ (line 14) | def __init__(self, nn_map, nn_distances, attn_masks, inject_range_alph...
    method inject_outputs (line 24) | def inject_outputs(self, output, curr_iter, output_res, extended_mappi...
    method inject_anchors (line 70) | def inject_anchors(self, output, curr_iter, output_res, extended_mappi...
  class AnchorCache (line 108) | class AnchorCache:
    method __init__ (line 109) | def __init__(self):
    method set_mode (line 117) | def set_mode(self, mode):
    method set_mode_inject (line 120) | def set_mode_inject(self):
    method set_mode_cache (line 123) | def set_mode_cache(self):
    method is_inject_mode (line 126) | def is_inject_mode(self):
    method is_cache_mode (line 129) | def is_cache_mode(self):
    method to_device (line 133) | def to_device(self, device):
  class QueryStore (line 147) | class QueryStore:
    method __init__ (line 148) | def __init__(self, mode='store', t_range=[0, 1000], strength_start=1, ...
    method set_mode (line 157) | def set_mode(self, mode): # mode can be 'cache' or 'inject'
    method cache_query (line 160) | def cache_query(self, query, place_in_unet: str):
    method inject_query (line 163) | def inject_query(self, query, place_in_unet, t):
  class DIFTLatentStore (line 173) | class DIFTLatentStore:
    method __init__ (line 174) | def __init__(self, steps: List[int], up_ft_indices: List[int]):
    method __call__ (line 179) | def __call__(self, features: torch.Tensor, t: int, layer_index: int):
    method copy (line 183) | def copy(self):
    method reset (line 191) | def reset(self):

FILE: scripts/consistory/utils/general_utils.py
  function get_dynamic_threshold (line 12) | def get_dynamic_threshold(tensor):
  function attn_map_to_binary (line 17) | def attn_map_to_binary(attention_map, scaler=1.):
  function gaussian_smooth (line 28) | def gaussian_smooth(input_tensor, kernel_size=3, sigma=1):
  function cos_dist (line 53) | def cos_dist(a, b):
  function gen_nn_map (line 60) | def gen_nn_map(src_features, src_mask,  tgt_features, tgt_mask, device, ...
  function cyclic_nn_map (line 78) | def cyclic_nn_map(features, masks, latent_resolutions, device):
  function anchor_nn_map (line 100) | def anchor_nn_map(features, anchor_features, masks, anchor_masks, latent...

FILE: scripts/consistory/utils/ptp_utils.py
  class AttentionStore (line 65) | class AttentionStore:
    method __init__ (line 66) | def __init__(self, attention_store_kwargs):
    method __call__ (line 87) | def __call__(self, attn, is_cross: bool, place_in_unet: str, attn_head...
    method reset (line 94) | def reset(self):
    method aggregate_last_steps_attention (line 102) | def aggregate_last_steps_attention(self) -> torch.Tensor:
    method get_attn_mask_bias (line 160) | def get_attn_mask_bias(self, tgt_size, bsz=None):
    method get_extended_attn_mask_instance (line 174) | def get_extended_attn_mask_instance(self, width, i):

FILE: scripts/consistory_ext.py
  class Script (line 18) | class Script(scripts_manager.Script):
    method __init__ (line 19) | def __init__(self):
    method title (line 24) | def title(self):
    method show (line 27) | def show(self, is_img2img):
    method reset (line 30) | def reset(self):
    method ui (line 35) | def ui(self, _is_img2img): # ui elements
    method create_model (line 67) | def create_model(self):
    method set_args (line 86) | def set_args(self, p: processing.StableDiffusionProcessing, *args):
    method create_anchors (line 130) | def create_anchors(self, anchors, concepts, seed, steps, dropout, same...
    method create_extra (line 161) | def create_extra(self, prompt, concepts, seed, steps, dropout, same, q...
    method run (line 192) | def run(self, p: processing.StableDiffusionProcessing, *args): # pylin...
    method after (line 216) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/ctrlx/__init__.py
  function get_last_control_i (line 22) | def get_last_control_i(control_schedule, num_inference_steps):
  class CtrlXStableDiffusionXLPipelineOutput (line 46) | class CtrlXStableDiffusionXLPipelineOutput(BaseOutput):
  class CtrlXStableDiffusionXLPipeline (line 52) | class CtrlXStableDiffusionXLPipeline(StableDiffusionXLPipeline):  # diff...
    method prepare_latents (line 54) | def prepare_latents(
    method structure_guidance_scale (line 129) | def structure_guidance_scale(self):
    method appearance_guidance_scale (line 133) | def appearance_guidance_scale(self):
    method __call__ (line 137) | def __call__(

FILE: scripts/ctrlx/features.py
  function get_schedule (line 5) | def get_schedule(timesteps, schedule):
  function get_elem (line 11) | def get_elem(l, i, default=0.0):
  function pad_list (line 17) | def pad_list(l_1, l_2, pad=0.0):
  function normalize (line 24) | def normalize(x, dim):
  function appearance_mean_std (line 32) | def appearance_mean_std(q_c_normed, k_s_normed, v_s):  # c: content, s: ...
  function feature_injection (line 41) | def feature_injection(features, batch_order):
  function appearance_transfer (line 49) | def appearance_transfer(features, q_normed, k_normed, batch_order, v=Non...

FILE: scripts/ctrlx/media.py
  function preprocess (line 10) | def preprocess(image, processor, **kwargs):

FILE: scripts/ctrlx/sdxl.py
  function get_control_config (line 9) | def get_control_config(structure_schedule, appearance_schedule):
  function convolution_forward (line 37) | def convolution_forward(  # From <class 'diffusers.models.resnet.ResnetB...
  class AttnProcessor2_0 (line 105) | class AttnProcessor2_0:  # From <class 'diffusers.models.attention_proce...
    method __init__ (line 107) | def __init__(self):
    method __call__ (line 111) | def __call__( # pylint: disable=keyword-arg-before-vararg
  function register_control (line 237) | def register_control(
  function register_attr (line 282) | def register_attr(model, t, do_control, batch_order):

FILE: scripts/ctrlx/utils.py
  function seed_everything (line 10) | def seed_everything(seed):
  function exists (line 19) | def exists(x):
  function get (line 23) | def get(x, default):
  function get_self_recurrence_schedule (line 29) | def get_self_recurrence_schedule(schedule, num_inference_steps):
  function batch_dict_to_tensor (line 42) | def batch_dict_to_tensor(batch_dict, batch_order):
  function batch_tensor_to_dict (line 50) | def batch_tensor_to_dict(batch_tensor, batch_order):
  function noise_prev (line 58) | def noise_prev(scheduler, timestep, x_0, noise=None):
  function noise_t2t (line 77) | def noise_t2t(scheduler, timestep, timestep_target, x_t, noise=None):

FILE: scripts/ctrlx_ext.py
  class Script (line 8) | class Script(scripts_manager.Script):
    method title (line 9) | def title(self):
    method show (line 12) | def show(self, is_img2img):
    method ui (line 15) | def ui(self, _is_img2img):
    method restore (line 36) | def restore(self):
    method run (line 40) | def run(self, p: processing.StableDiffusionProcessing, struct_prompt, ...

FILE: scripts/custom_code.py
  function convertExpr2Expression (line 9) | def convertExpr2Expression(expr):
  function exec_with_return (line 17) | def exec_with_return(code, module):
  class Script (line 38) | class Script(scripts_manager.Script):
    method title (line 40) | def title(self):
    method show (line 43) | def show(self, is_img2img):
    method ui (line 46) | def ui(self, is_img2img):
    method run (line 63) | def run(self, p, code, indent_level): # pylint: disable=arguments-differ

FILE: scripts/daam/evaluate.py
  function compute_iou (line 14) | def compute_iou(a: torch.Tensor, b: torch.Tensor) -> float:
  function compute_ioa (line 26) | def compute_ioa(a: torch.Tensor, b: torch.Tensor) -> float:
  function load_mask (line 38) | def load_mask(path: str) -> torch.Tensor:
  class UnsupervisedEvaluator (line 46) | class UnsupervisedEvaluator:
    method __init__ (line 47) | def __init__(self, name: str = 'UnsupervisedEvaluator'):
    method log_iou (line 52) | def log_iou(self, preds: Union[torch.Tensor, List[torch.Tensor]], trut...
    method mean_iou (line 60) | def mean_iou(self) -> float:
    method increment (line 73) | def increment(self):
    method __len__ (line 76) | def __len__(self) -> int:
    method __str__ (line 79) | def __str__(self):
  class MeanEvaluator (line 83) | class MeanEvaluator:
    method __init__ (line 84) | def __init__(self, name: str = 'MeanEvaluator'):
    method log_iou (line 89) | def log_iou(self, preds: Union[torch.Tensor, List[torch.Tensor]], trut...
    method log_intensity (line 96) | def log_intensity(self, pred: torch.Tensor):
    method mean_iou (line 101) | def mean_iou(self) -> float:
    method mean_intensity (line 105) | def mean_intensity(self) -> float:
    method ci95_miou (line 109) | def ci95_miou(self) -> float:
    method __len__ (line 112) | def __len__(self) -> int:
    method __str__ (line 115) | def __str__(self):

FILE: scripts/daam/experiment.py
  function build_word_list_coco80 (line 82) | def build_word_list_coco80() -> Dict[str, List[str]]:
  function _add_mask (line 89) | def _add_mask(masks: Dict[str, torch.Tensor], word: str, mask: torch.Ten...
  class GenerationExperiment (line 103) | class GenerationExperiment:
    method __post_init__ (line 119) | def __post_init__(self):
    method nsfw (line 125) | def nsfw(self) -> bool:
    method heat_map (line 128) | def heat_map(self, tokenizer: AutoTokenizer = None):
    method clear_checkpoint (line 135) | def clear_checkpoint(self):
    method save (line 140) | def save(self, path: str = None, heat_maps: bool = True, tokenizer: Au...
    method save_annotations (line 169) | def save_annotations(self, path: Path = None):
    method _load_truth_masks (line 177) | def _load_truth_masks(self, simplify80: bool = False) -> Dict[str, tor...
    method _load_pred_masks (line 187) | def _load_pred_masks(self, pred_prefix, composite=False, simplify80=Fa...
    method clear_prediction_masks (line 212) | def clear_prediction_masks(self, name: str):
    method save_prediction_mask (line 219) | def save_prediction_mask(self, mask: torch.Tensor, word: str, name: str):
    method save_heat_map (line 224) | def save_heat_map(
    method save_all_heat_maps (line 244) | def save_all_heat_maps(self, tokenizer: PreTrainedTokenizer = None, cr...
    method contains_truth_mask (line 260) | def contains_truth_mask(path: Union[str, Path], prompt_id: str = None)...
    method read_seed (line 267) | def read_seed(path: Union[str, Path], prompt_id: str = None) -> int:
    method has_annotations (line 274) | def has_annotations(path: Union[str, Path]) -> bool:
    method has_experiment (line 278) | def has_experiment(path: Union[str, Path], prompt_id: str) -> bool:
    method read_prompt (line 282) | def read_prompt(path: Union[str, Path], prompt_id: str = None) -> str:
    method _try_load_annotations (line 289) | def _try_load_annotations(self):
    method annotate (line 295) | def annotate(self, key: str, value: Any) -> 'GenerationExperiment':
    method load (line 304) | def load(

FILE: scripts/daam/heatmap.py
  function plot_overlay_heat_map (line 21) | def plot_overlay_heat_map(im, heat_map, word=None, out_file=None, crop=N...
  class WordHeatMap (line 68) | class WordHeatMap:
    method __init__ (line 69) | def __init__(self, heatmap: torch.Tensor, word: str = None, word_idx: ...
    method value (line 75) | def value(self):
    method plot_overlay (line 78) | def plot_overlay(self, image, out_file=None, color_normalize=True, ax=...
    method expand_as (line 90) | def expand_as(self, image, absolute=False, threshold=None, plot=False,...
    method compute_ioa (line 108) | def compute_ioa(self, other: 'WordHeatMap'):
  class SyntacticHeatMapPair (line 113) | class SyntacticHeatMapPair:
  class ParsedHeatMap (line 122) | class ParsedHeatMap:
  class GlobalHeatMap (line 127) | class GlobalHeatMap:
    method __init__ (line 128) | def __init__(self, tokenizer: Any, prompt: str, heat_maps: torch.Tensor):
    method compute_word_heat_map (line 134) | def compute_word_heat_map(self, word: str, word_idx: int = None, offse...
    method parsed_heat_maps (line 138) | def parsed_heat_maps(self) -> Iterable[ParsedHeatMap]:
    method dependency_relations (line 146) | def dependency_relations(self) -> Iterable[SyntacticHeatMapPair]:
  class RawHeatMapCollection (line 161) | class RawHeatMapCollection:
    method __init__ (line 162) | def __init__(self):
    method update (line 166) | def update(self, factor: int, layer_idx: int, head_idx: int, heatmap: ...
    method factors (line 171) | def factors(self) -> Set[int]:
    method layers (line 174) | def layers(self) -> Set[int]:
    method heads (line 177) | def heads(self) -> Set[int]:
    method __iter__ (line 180) | def __iter__(self):
    method clear (line 183) | def clear(self):

FILE: scripts/daam/hook.py
  class ModuleLocator (line 17) | class ModuleLocator(Generic[ModuleType]):
    method locate (line 18) | def locate(self, model: nn.Module) -> List[ModuleType]:
  class ObjectHooker (line 22) | class ObjectHooker(Generic[ModuleType]):
    method __init__ (line 23) | def __init__(self, module: ModuleType):
    method __enter__ (line 28) | def __enter__(self):
    method __exit__ (line 32) | def __exit__(self, exc_type, exc_val, exc_tb):
    method hook (line 35) | def hook(self):
    method unhook (line 45) | def unhook(self):
    method monkey_patch (line 58) | def monkey_patch(self, fn_name, fn, strict: bool = True):
    method monkey_super (line 66) | def monkey_super(self, fn_name, *args, **kwargs):
    method _hook_impl (line 69) | def _hook_impl(self):
    method _unhook_impl (line 72) | def _unhook_impl(self):
  class AggregateHooker (line 76) | class AggregateHooker(ObjectHooker[ModuleListType]):
    method _hook_impl (line 77) | def _hook_impl(self):
    method _unhook_impl (line 81) | def _unhook_impl(self):
    method register_hook (line 85) | def register_hook(self, hook: ObjectHooker):
  class UNetCrossAttentionLocator (line 89) | class UNetCrossAttentionLocator(ModuleLocator[Attention]):
    method __init__ (line 90) | def __init__(self, restrict: bool = None, locate_middle_block: bool = ...
    method locate (line 95) | def locate(self, model: UNet2DConditionModel) -> List[Attention]:

FILE: scripts/daam/trace.py
  class DiffusionHeatMapHooker (line 22) | class DiffusionHeatMapHooker(AggregateHooker):
    method __init__ (line 23) | def __init__(
    method time_callback (line 61) | def time_callback(self, *args, **kwargs):
    method layer_names (line 65) | def layer_names(self):
    method to_experiment (line 68) | def to_experiment(self, path, seed=None, id='.', subtype='.', **comput...
    method compute_global_heat_map (line 83) | def compute_global_heat_map(self, prompt=None, factors=None, head_idx=...
  class ImageProcessorHooker (line 135) | class ImageProcessorHooker(ObjectHooker[VaeImageProcessor]):
    method __init__ (line 136) | def __init__(self, processor: VaeImageProcessor, parent_trace: 'trace'):
    method _hooked_postprocess (line 140) | def _hooked_postprocess(hk_self, _: VaeImageProcessor, *args, **kwargs):
    method _hook_impl (line 146) | def _hook_impl(self):
  class PipelineHooker (line 150) | class PipelineHooker(ObjectHooker[StableDiffusionPipeline]):
    method __init__ (line 151) | def __init__(self, pipeline: StableDiffusionPipeline, parent_trace: 't...
    method _hooked_run_safety_checker (line 156) | def _hooked_run_safety_checker(hk_self, self: StableDiffusionPipeline,...
    method _hooked_check_inputs (line 171) | def _hooked_check_inputs(hk_self, _: StableDiffusionPipeline, prompt: ...
    method _hook_impl (line 184) | def _hook_impl(self):
  class UNetCrossAttentionHooker (line 189) | class UNetCrossAttentionHooker(ObjectHooker[Attention]):
    method __init__ (line 190) | def __init__(
    method _unravel_attn (line 220) | def _unravel_attn(self, x):
    method _save_attn (line 251) | def _save_attn(self, attn_slice: torch.Tensor):
    method _load_attn (line 254) | def _load_attn(self) -> torch.Tensor:
    method __call__ (line 257) | def __call__(
    method _hook_impl (line 311) | def _hook_impl(self):
    method _unhook_impl (line 315) | def _unhook_impl(self):
    method num_heat_maps (line 319) | def num_heat_maps(self):

FILE: scripts/daam/utils.py
  function auto_device (line 21) | def auto_device(obj: T = torch.device('cpu')) -> T:
  function auto_autocast (line 31) | def auto_autocast(*args, **kwargs):
  function plot_mask_heat_map (line 38) | def plot_mask_heat_map(im: PIL.Image.Image, heat_map: torch.Tensor, thre...
  function set_seed (line 45) | def set_seed(seed: int) -> torch.Generator:
  function cache_dir (line 57) | def cache_dir() -> Path:
  function compute_token_merge_indices (line 72) | def compute_token_merge_indices(tokenizer, prompt: str, word: str, word_...
  function cached_nlp (line 97) | def cached_nlp(prompt: str, type='en_core_web_md'):

FILE: scripts/daam_ext.py
  class Script (line 11) | class Script(scripts_manager.Script):
    method title (line 12) | def title(self):
    method show (line 15) | def show(self, is_img2img):
    method ui (line 18) | def ui(self, _is_img2img):
    method run (line 26) | def run(self, p: processing.StableDiffusionProcessing, append_images, ...

FILE: scripts/demofusion.py
  function gaussian_kernel (line 27) | def gaussian_kernel(kernel_size=3, sigma=1.0, channels=3):
  function gaussian_filter (line 36) | def gaussian_filter(latents, kernel_size=3, sigma=1.0):
  function rescale_noise_cfg (line 44) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class DemoFusionSDXLPipeline (line 58) | class DemoFusionSDXLPipeline(DiffusionPipeline, FromSingleFileMixin, Lor...
    method __init__ (line 61) | def __init__(
    method enable_vae_slicing (line 90) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 94) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 98) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 102) | def disable_vae_tiling(self):
    method encode_prompt (line 105) | def encode_prompt(
    method prepare_extra_step_kwargs (line 256) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 273) | def check_inputs(
    method prepare_latents (line 357) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 374) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method get_views (line 390) | def get_views(self, height, width, window_size=128, stride=64, random_...
    method tiled_decode (line 442) | def tiled_decode(self, latents, current_height, current_width):
    method upcast_vae (line 479) | def upcast_vae(self):
    method __call__ (line 498) | def __call__(
    method load_lora_weights (line 1160) | def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Uni...
    method _remove_text_encoder_monkey_patch (line 1215) | def _remove_text_encoder_monkey_patch(self):
  class Script (line 1222) | class Script(scripts_manager.Script):
    method title (line 1223) | def title(self):
    method show (line 1226) | def show(self, is_img2img):
    method ui (line 1230) | def ui(self, _is_img2img):
    method run (line 1245) | def run(self, p: processing.StableDiffusionProcessing, cosine_scale_1,...

FILE: scripts/differential_diffusion.py
  function rescale_noise_cfg (line 56) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class StableDiffusionXLDiffImg2ImgPipeline (line 70) | class StableDiffusionXLDiffImg2ImgPipeline(DiffusionPipeline, FromSingle...
    method __init__ (line 111) | def __init__(
    method enable_vae_slicing (line 142) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 150) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 158) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 167) | def disable_vae_tiling(self):
    method enable_model_cpu_offload (line 174) | def enable_model_cpu_offload(self, gpu_id=0): # pylint: disable=argume...
    method encode_prompt (line 205) | def encode_prompt(
    method prepare_extra_step_kwargs (line 398) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 415) | def check_inputs(
    method get_timesteps (line 482) | def get_timesteps(self, num_inference_steps, strength, device, denoisi...
    method prepare_latents (line 506) | def prepare_latents(
    method _get_add_time_ids (line 573) | def _get_add_time_ids(
    method upcast_vae (line 613) | def upcast_vae(self):
    method __call__ (line 633) | def __call__(
  class StableDiffusionDiffImg2ImgPipeline (line 1024) | class StableDiffusionDiffImg2ImgPipeline(DiffusionPipeline):
    method __init__ (line 1054) | def __init__(
    method enable_sequential_cpu_offload (line 1144) | def enable_sequential_cpu_offload(self, gpu_id=0): # pylint: disable=a...
    method enable_model_cpu_offload (line 1170) | def enable_model_cpu_offload(self, gpu_id=0): # pylint: disable=argume...
    method _execution_device (line 1200) | def _execution_device(self):
    method _encode_prompt (line 1218) | def _encode_prompt(
    method decode_latents (line 1357) | def decode_latents(self, latents):
    method prepare_extra_step_kwargs (line 1366) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 1383) | def check_inputs(
    method get_timesteps (line 1423) | def get_timesteps(self, num_inference_steps, strength, device): # pyli...
    method prepare_latents (line 1432) | def prepare_latents(self, image, timestep, batch_size, num_images_per_...
    method encode_prompt (line 1484) | def encode_prompt(
    method preprocess (line 1622) | def preprocess(self, image):
    method __call__ (line 1644) | def __call__(
  class Script (line 1848) | class Script(scripts_manager.Script):
    method title (line 1849) | def title(self):
    method show (line 1852) | def show(self, is_img2img):
    method ui (line 1855) | def ui(self, _is_img2img):
    method depthmap (line 1867) | def depthmap(self, image_init: Image.Image, image_map: Image.Image, mo...
    method run (line 1898) | def run(self, p: processing.StableDiffusionProcessingImg2Img, enabled,...

FILE: scripts/example.py
  class Script (line 65) | class Script(scripts_manager.Script):
    method title (line 66) | def title(self):
    method show (line 69) | def show(self, is_img2img):
    method ui (line 73) | def ui(self, _is_img2img):
    method run (line 87) | def run(self, p: processing.StableDiffusionProcessing, *args): # pylin...

FILE: scripts/flux_enhance.py
  class Script (line 16) | class Script(scripts_manager.Script):
    method title (line 29) | def title(self):
    method show (line 32) | def show(self, is_img2img):
    method load (line 35) | def load(self):
    method enhance (line 43) | def enhance(self, prompt, auto_apply: bool = False, temperature: float...
    method select (line 68) | def select(self, cell: gr.SelectData, _table):
    method ui (line 73) | def ui(self, _is_img2img):
    method run (line 89) | def run(self, p: processing.StableDiffusionProcessing, auto_apply, tem...
    method after_component (line 100) | def after_component(self, component, **kwargs): # searching for actual...

FILE: scripts/flux_tools.py
  class Script (line 17) | class Script(scripts_manager.Script):
    method title (line 18) | def title(self):
    method show (line 21) | def show(self, is_img2img):
    method ui (line 24) | def ui(self, _is_img2img): # ui elements
    method run (line 44) | def run(self, p: processing.StableDiffusionProcessing, tool: str = 'No...

FILE: scripts/freescale/free_lunch_utils.py
  function isinstance_str (line 10) | def isinstance_str(x: object, cls_name: str):
  function Fourier_filter (line 25) | def Fourier_filter(x, threshold, scale):
  function register_upblock2d (line 47) | def register_upblock2d(model):
  function register_free_upblock2d (line 89) | def register_free_upblock2d(model, b1=1.2, b2=1.4, s1=0.9, s2=0.2):
  function register_crossattn_upblock2d (line 146) | def register_crossattn_upblock2d(model):
  function register_free_crossattn_upblock2d (line 218) | def register_free_crossattn_upblock2d(model, b1=1.2, b2=1.4, s1=0.9, s2=...

FILE: scripts/freescale/freescale_pipeline.py
  function default (line 46) | def default(val, d):
  function exists (line 51) | def exists(val):
  function extract_into_tensor (line 54) | def extract_into_tensor(a, t, x_shape):
  function make_beta_schedule (line 59) | def make_beta_schedule(schedule, n_timestep, linear_start=1e-4, linear_e...
  function q_sample (line 88) | def q_sample(x_start, t, init_noise_sigma = 1.0, noise=None, device=None):
  function get_views (line 93) | def get_views(height, width, h_window_size=128, w_window_size=128, h_win...
  function gaussian_kernel (line 146) | def gaussian_kernel(kernel_size=3, sigma=1.0, channels=3):
  function gaussian_filter (line 155) | def gaussian_filter(latents, kernel_size=3, sigma=1.0):
  function rescale_noise_cfg (line 169) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class StableDiffusionXLFreeScale (line 183) | class StableDiffusionXLFreeScale(DiffusionPipeline, FromSingleFileMixin,...
    method __init__ (line 222) | def __init__(
    method enable_vae_slicing (line 251) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 259) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 267) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 276) | def disable_vae_tiling(self):
    method enable_model_cpu_offload (line 283) | def enable_model_cpu_offload(self, gpu_id=0):
    method encode_prompt (line 313) | def encode_prompt(
    method prepare_extra_step_kwargs (line 505) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 522) | def check_inputs(
    method prepare_latents (line 596) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 613) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method upcast_vae (line 630) | def upcast_vae(self):
    method __call__ (line 651) | def __call__(
    method load_lora_weights (line 1122) | def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Uni...
    method save_lora_weights (line 1154) | def save_lora_weights(
    method _remove_text_encoder_monkey_patch (line 1187) | def _remove_text_encoder_monkey_patch(self):

FILE: scripts/freescale/freescale_pipeline_img2img.py
  function process_image_to_tensor (line 48) | def process_image_to_tensor(image):
  function process_image_to_bitensor (line 61) | def process_image_to_bitensor(image):
  function default (line 69) | def default(val, d):
  function exists (line 74) | def exists(val):
  function extract_into_tensor (line 77) | def extract_into_tensor(a, t, x_shape):
  function make_beta_schedule (line 82) | def make_beta_schedule(schedule, n_timestep, linear_start=1e-4, linear_e...
  function q_sample (line 111) | def q_sample(x_start, t, init_noise_sigma = 1.0, noise=None, device=None):
  function get_views (line 116) | def get_views(height, width, h_window_size=128, w_window_size=128, h_win...
  function gaussian_kernel (line 169) | def gaussian_kernel(kernel_size=3, sigma=1.0, channels=3):
  function gaussian_filter (line 178) | def gaussian_filter(latents, kernel_size=3, sigma=1.0):
  function rescale_noise_cfg (line 192) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class StableDiffusionXLFreeScaleImg2Img (line 206) | class StableDiffusionXLFreeScaleImg2Img(DiffusionPipeline, FromSingleFil...
    method __init__ (line 245) | def __init__(
    method enable_vae_slicing (line 276) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 284) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 292) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 301) | def disable_vae_tiling(self):
    method enable_model_cpu_offload (line 308) | def enable_model_cpu_offload(self, gpu_id=0):
    method encode_prompt (line 338) | def encode_prompt(
    method prepare_extra_step_kwargs (line 530) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 547) | def check_inputs(
    method prepare_latents (line 621) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 638) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method upcast_vae (line 655) | def upcast_vae(self):
    method __call__ (line 676) | def __call__(
    method load_lora_weights (line 1178) | def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Uni...
    method save_lora_weights (line 1210) | def save_lora_weights(
    method _remove_text_encoder_monkey_patch (line 1243) | def _remove_text_encoder_monkey_patch(self):

FILE: scripts/freescale/scale_attention.py
  function gaussian_kernel (line 8) | def gaussian_kernel(kernel_size=3, sigma=1.0, channels=3):
  function gaussian_filter (line 17) | def gaussian_filter(latents, kernel_size=3, sigma=1.0):
  function get_views (line 24) | def get_views(height, width, h_window_size=128, w_window_size=128, scale...
  function scale_forward (line 83) | def scale_forward(
  function ori_forward (line 284) | def ori_forward(

FILE: scripts/freescale_ext.py
  class Script (line 8) | class Script(scripts_manager.Script):
    method __init__ (line 9) | def __init__(self):
    method title (line 16) | def title(self):
    method show (line 19) | def show(self, is_img2img):
    method ui (line 23) | def ui(self, _is_img2img): # ui elements
    method run (line 50) | def run(self, p: processing.StableDiffusionProcessing, cosine_scale, o...
    method after (line 119) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/hdr.py
  class Script (line 11) | class Script(scripts_manager.Script):
    method title (line 12) | def title(self):
    method show (line 15) | def show(self, is_img2img):
    method ui (line 18) | def ui(self, is_img2img):
    method change_tonemap (line 33) | def change_tonemap(self, is_tonemap):
    method merge (line 36) | def merge(self, imgs: list, is_tonemap: bool, gamma, scale, saturation):
    method run (line 59) | def run(self, p, hdr_range, save_hdr, is_tonemap, gamma, scale, satura...

FILE: scripts/image2video.py
  class Script (line 14) | class Script(scripts_manager.Script):
    method title (line 15) | def title(self):
    method show (line 18) | def show(self, is_img2img):
    method ui (line 23) | def ui(self, is_img2img):
    method run (line 54) | def run(self, p: processing.StableDiffusionProcessing, model_name, num...

FILE: scripts/infiniteyou/pipeline_flux_infusenet.py
  function calculate_shift (line 39) | def calculate_shift(
  function retrieve_timesteps (line 53) | def retrieve_timesteps(
  class FluxInfuseNetPipeline (line 112) | class FluxInfuseNetPipeline(FluxControlNetPipeline):
    method __call__ (line 114) | def __call__(

FILE: scripts/infiniteyou/pipeline_infu_flux.py
  function seed_everything (line 35) | def seed_everything(seed, deterministic=False):
  function retrieve_latents (line 56) | def retrieve_latents(
  function draw_kps (line 70) | def draw_kps(image_pil, kps, color_list=[(255,0,0), (0,255,0), (0,0,255)...
  function extract_arcface_bgr_embedding (line 99) | def extract_arcface_bgr_embedding(in_image, landmark, arcface_model=None...
  function resize_and_pad_image (line 111) | def resize_and_pad_image(source_img, target_img_size):
  class InfUFluxPipeline (line 138) | class InfUFluxPipeline:
    method __init__ (line 139) | def __init__(
    method load_loras (line 205) | def load_loras(self, loras):
    method _detect_face (line 217) | def _detect_face(self, id_image_cv2):
    method __call__ (line 229) | def __call__(

FILE: scripts/infiniteyou/resampler.py
  function FeedForward (line 10) | def FeedForward(dim, mult=4):
  function reshape_tensor (line 20) | def reshape_tensor(x, heads):
  class PerceiverAttention (line 31) | class PerceiverAttention(nn.Module):
    method __init__ (line 32) | def __init__(self, *, dim, dim_head=64, heads=8):
    method forward (line 46) | def forward(self, x, latents):
  class Resampler (line 78) | class Resampler(nn.Module):
    method __init__ (line 79) | def __init__(
    method forward (line 110) | def forward(self, x):

FILE: scripts/infiniteyou_ext.py
  function verify_insightface (line 15) | def verify_insightface():
  function load_infiniteyou (line 21) | def load_infiniteyou(model: str):
  class Script (line 32) | class Script(scripts_manager.Script):
    method title (line 33) | def title(self):
    method show (line 36) | def show(self, is_img2img):
    method ui (line 40) | def ui(self, _is_img2img):
    method run (line 61) | def run(self, p: processing.StableDiffusionProcessing,
    method after (line 111) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/init_latents.py
  class Script (line 4) | class Script(scripts_manager.Script):
    method title (line 7) | def title(self):
    method show (line 10) | def show(self, is_img2img):
    method get_latents (line 14) | def get_latents(p):
    method set_slerp (line 26) | def set_slerp(p, latents, var_latents, generator, var_generator):
    method process_batch (line 31) | def process_batch(self, p: processing.StableDiffusionProcessing, *args...

FILE: scripts/instantir/aggregator.py
  class ZeroConv (line 33) | class ZeroConv(nn.Module):
    method __init__ (line 34) | def __init__(self, label_nc, norm_nc, mask=False):
    method forward (line 39) | def forward(self, hidden_states, h_ori=None):
  class SFT (line 51) | class SFT(nn.Module):
    method __init__ (line 52) | def __init__(self, label_nc, norm_nc, mask=False):
    method forward (line 70) | def forward(self, hidden_states, mask=False):
  class AggregatorOutput (line 94) | class AggregatorOutput(BaseOutput):
  class ConditioningEmbedding (line 113) | class ConditioningEmbedding(nn.Module):
    method __init__ (line 123) | def __init__(
    method forward (line 145) | def forward(self, conditioning):
  class Aggregator (line 158) | class Aggregator(ModelMixin, ConfigMixin, FromOriginalModelMixin):
    method __init__ (line 230) | def __init__(
    method from_unet (line 504) | def from_unet(
    method attn_processors (line 582) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 606) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method set_default_attn_processor (line 641) | def set_default_attn_processor(self):
    method set_attention_slice (line 657) | def set_attention_slice(self, slice_size: Union[str, int, List[int]]) ...
    method process_encoder_hidden_states (line 722) | def process_encoder_hidden_states(
    method _set_gradient_checkpointing (line 754) | def _set_gradient_checkpointing(self, module, value: bool = False) -> ...
    method forward (line 758) | def forward(
  function zero_module (line 979) | def zero_module(module):

FILE: scripts/instantir/ip_adapter/attention_processor.py
  class AdaLayerNorm (line 6) | class AdaLayerNorm(nn.Module):
    method __init__ (line 7) | def __init__(self, embedding_dim: int, time_embedding_dim: int = None):
    method forward (line 20) | def forward(
  class AttnProcessor (line 29) | class AttnProcessor(nn.Module):
    method __init__ (line 34) | def __init__(
    method __call__ (line 41) | def __call__(
  class IPAttnProcessor (line 102) | class IPAttnProcessor(nn.Module):
    method __init__ (line 116) | def __init__(self, hidden_size, cross_attention_dim=None, scale=1.0, n...
    method __call__ (line 127) | def __call__(
  class TA_IPAttnProcessor (line 208) | class TA_IPAttnProcessor(nn.Module):
    method __init__ (line 222) | def __init__(self, hidden_size, cross_attention_dim=None, time_embeddi...
    method __call__ (line 236) | def __call__(
  class AttnProcessor2_0 (line 323) | class AttnProcessor2_0(torch.nn.Module):
    method __init__ (line 328) | def __init__(
    method __call__ (line 337) | def __call__(
  class split_AttnProcessor2_0 (line 416) | class split_AttnProcessor2_0(torch.nn.Module):
    method __init__ (line 421) | def __init__(
    method __call__ (line 431) | def __call__(
  class sep_split_AttnProcessor2_0 (line 539) | class sep_split_AttnProcessor2_0(torch.nn.Module):
    method __init__ (line 544) | def __init__(
    method __call__ (line 564) | def __call__(
  class AdditiveKV_AttnProcessor2_0 (line 699) | class AdditiveKV_AttnProcessor2_0(torch.nn.Module):
    method __init__ (line 704) | def __init__(
    method __call__ (line 716) | def __call__(
  class TA_AdditiveKV_AttnProcessor2_0 (line 808) | class TA_AdditiveKV_AttnProcessor2_0(torch.nn.Module):
    method __init__ (line 813) | def __init__(
    method __call__ (line 827) | def __call__(
  class IPAttnProcessor2_0 (line 923) | class IPAttnProcessor2_0(torch.nn.Module):
    method __init__ (line 937) | def __init__(self, hidden_size, cross_attention_dim=None, scale=1.0, n...
    method __call__ (line 951) | def __call__(
  class TA_IPAttnProcessor2_0 (line 1055) | class TA_IPAttnProcessor2_0(torch.nn.Module):
    method __init__ (line 1069) | def __init__(self, hidden_size, cross_attention_dim=None, time_embeddi...
    method __call__ (line 1085) | def __call__(
  class CNAttnProcessor (line 1201) | class CNAttnProcessor:
    method __init__ (line 1206) | def __init__(self, num_tokens=4):
    method __call__ (line 1209) | def __call__(self, attn, hidden_states, encoder_hidden_states=None, at...
  class CNAttnProcessor2_0 (line 1266) | class CNAttnProcessor2_0:
    method __init__ (line 1271) | def __init__(self, num_tokens=4):
    method __call__ (line 1276) | def __call__(
  function init_attn_proc (line 1353) | def init_attn_proc(unet, ip_adapter_tokens=16, use_lcm=False, use_adaln=...
  function init_aggregator_attn_proc (line 1407) | def init_aggregator_attn_proc(unet, use_adaln=False, split_attn=False):

FILE: scripts/instantir/ip_adapter/ip_adapter.py
  function is_torch2_available (line 6) | def is_torch2_available():
  class ImageProjModel (line 26) | class ImageProjModel(torch.nn.Module):
    method __init__ (line 29) | def __init__(self, cross_attention_dim=2048, clip_embeddings_dim=1280,...
    method forward (line 37) | def forward(self, image_embeds):
  class MLPProjModel (line 46) | class MLPProjModel(torch.nn.Module):
    method __init__ (line 48) | def __init__(self, cross_attention_dim=2048, clip_embeddings_dim=1280):
    method forward (line 58) | def forward(self, image_embeds):
  class MultiIPAdapterImageProjection (line 63) | class MultiIPAdapterImageProjection(torch.nn.Module):
    method __init__ (line 64) | def __init__(self, IPAdapterImageProjectionLayers):
    method forward (line 68) | def forward(self, image_embeds: List[torch.FloatTensor]):
  class IPAdapter (line 93) | class IPAdapter(torch.nn.Module):
    method __init__ (line 95) | def __init__(self, unet, image_proj_model, adapter_modules, ckpt_path=...
    method forward (line 104) | def forward(self, noisy_latents, timesteps, encoder_hidden_states, ima...
    method load_from_checkpoint (line 111) | def load_from_checkpoint(self, ckpt_path: str):
  class IPAdapterPlus (line 134) | class IPAdapterPlus(torch.nn.Module):
    method __init__ (line 136) | def __init__(self, unet, image_proj_model, adapter_modules, ckpt_path=...
    method forward (line 145) | def forward(self, noisy_latents, timesteps, encoder_hidden_states, ima...
    method load_from_checkpoint (line 152) | def load_from_checkpoint(self, ckpt_path: str):
  class IPAdapterXL (line 204) | class IPAdapterXL(IPAdapter):
    method forward (line 207) | def forward(self, noisy_latents, timesteps, encoder_hidden_states, une...
  class IPAdapterPlusXL (line 215) | class IPAdapterPlusXL(IPAdapterPlus):
    method forward (line 218) | def forward(self, noisy_latents, timesteps, encoder_hidden_states, une...
  class IPAdapterFull (line 226) | class IPAdapterFull(IPAdapterPlus):
    method init_proj (line 229) | def init_proj(self):

FILE: scripts/instantir/ip_adapter/resampler.py
  function FeedForward (line 13) | def FeedForward(dim, mult=4):
  function reshape_tensor (line 23) | def reshape_tensor(x, heads):
  class PerceiverAttention (line 34) | class PerceiverAttention(nn.Module):
    method __init__ (line 35) | def __init__(self, *, dim, dim_head=64, heads=8):
    method forward (line 49) | def forward(self, x, latents):
  class Resampler (line 81) | class Resampler(nn.Module):
    method __init__ (line 82) | def __init__(
    method forward (line 127) | def forward(self, x):
  function masked_mean (line 150) | def masked_mean(t, *, dim, mask=None):

FILE: scripts/instantir/ip_adapter/utils.py
  function init_adapter_in_unet (line 12) | def init_adapter_in_unet(
  function load_adapter_to_pipe (line 73) | def load_adapter_to_pipe(
  function revise_state_dict (line 164) | def revise_state_dict(old_state_dict_or_path, map_location="cpu"):
  function encode_image (line 181) | def encode_image(image_encoder, feature_extractor, image, device, num_im...
  function prepare_training_image_embeds (line 203) | def prepare_training_image_embeds(

FILE: scripts/instantir/lcm_single_step_scheduler.py
  class LCMSingleStepSchedulerOutput (line 35) | class LCMSingleStepSchedulerOutput(BaseOutput):
  function betas_for_alpha_bar (line 49) | def betas_for_alpha_bar(
  function rescale_zero_terminal_snr (line 94) | def rescale_zero_terminal_snr(betas: torch.FloatTensor) -> torch.FloatTe...
  class LCMSingleStepScheduler (line 130) | class LCMSingleStepScheduler(SchedulerMixin, ConfigMixin):
    method __init__ (line 194) | def __init__(
    method _init_step_index (line 252) | def _init_step_index(self, timestep):
    method step_index (line 270) | def step_index(self):
    method scale_model_input (line 273) | def scale_model_input(self, sample: torch.FloatTensor, timestep: Optio...
    method _threshold_sample (line 290) | def _threshold_sample(self, sample: torch.FloatTensor) -> torch.FloatT...
    method set_timesteps (line 323) | def set_timesteps(
    method get_scalings_for_boundary_condition_discrete (line 401) | def get_scalings_for_boundary_condition_discrete(self, timestep):
    method append_dims (line 409) | def append_dims(self, x, target_dims):
    method extract_into_tensor (line 416) | def extract_into_tensor(self, a, t, x_shape):
    method step (line 421) | def step(
    method add_noise (line 492) | def add_noise(
    method get_velocity (line 516) | def get_velocity(
    method __len__ (line 536) | def __len__(self):

FILE: scripts/instantir/sdxl_instantir.py
  function remove_attn2 (line 167) | def remove_attn2(model):
  function rescale_noise_cfg (line 183) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 198) | def retrieve_timesteps(
  class InstantIRPipeline (line 242) | class InstantIRPipeline(
    method __init__ (line 305) | def __init__(
    method prepare_previewers (line 352) | def prepare_previewers(self, previewer_lora_path: str, use_lcm=False):
    method encode_prompt (line 402) | def encode_prompt(
    method encode_image (line 637) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 674) | def prepare_ip_adapter_image_embeds(
    method prepare_extra_step_kwargs (line 734) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 751) | def check_inputs(
    method check_image (line 869) | def check_image(self, image, prompt, prompt_embeds):
    method prepare_image (line 907) | def prepare_image(
    method init_latents (line 931) | def init_latents(self, latents, generator, timestep):
    method prepare_latents (line 940) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 963) | def _get_add_time_ids(
    method upcast_vae (line 982) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 1002) | def get_guidance_scale_embedding(
    method guidance_scale (line 1033) | def guidance_scale(self):
    method guidance_rescale (line 1037) | def guidance_rescale(self):
    method clip_skip (line 1041) | def clip_skip(self):
    method do_classifier_free_guidance (line 1048) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 1052) | def cross_attention_kwargs(self):
    method denoising_end (line 1056) | def denoising_end(self):
    method num_timesteps (line 1060) | def num_timesteps(self):
    method __call__ (line 1065) | def __call__(

FILE: scripts/instantir_ext.py
  class Script (line 8) | class Script(scripts_manager.Script):
    method __init__ (line 9) | def __init__(self):
    method title (line 14) | def title(self):
    method show (line 17) | def show(self, is_img2img):
    method ui (line 20) | def ui(self, _is_img2img): # ui elements
    method run (line 36) | def run(self, p: processing.StableDiffusionProcessing, *args): # pylin...
    method dummy_unapply (line 86) | def dummy_unapply(self, pipe, unload): # pylint: disable=unused-argument
    method after (line 89) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/ipadapter.py
  class Script (line 10) | class Script(scripts_manager.Script):
    method title (line 13) | def title(self):
    method show (line 16) | def show(self, is_img2img):
    method load_images (line 19) | def load_images(self, files):
    method display_units (line 39) | def display_units(self, num_units):
    method display_advanced (line 43) | def display_advanced(self, advanced):
    method ui (line 46) | def ui(self, _is_img2img):
    method process (line 91) | def process(self, p: processing.StableDiffusionProcessing, *args): # p...

FILE: scripts/ipinstruct.py
  class Script (line 19) | class Script(scripts_manager.Script):
    method __init__ (line 20) | def __init__(self):
    method title (line 25) | def title(self):
    method show (line 28) | def show(self, is_img2img):
    method install (line 34) | def install(self):
    method ui (line 42) | def ui(self, _is_img2img): # ui elements
    method run (line 57) | def run(self, p: processing.StableDiffusionProcessing, query, image, s...
    method after (line 108) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/kohya_hires_fix.py
  class Script (line 6) | class Script(scripts_manager.Script):
    method title (line 7) | def title(self):
    method show (line 10) | def show(self, is_img2img):
    method ui (line 14) | def ui(self, _is_img2img):
    method run (line 25) | def run(self, p: processing.StableDiffusionProcessing, enabled, scale_...

FILE: scripts/layerdiffuse/__init__.py
  function apply_layerdiffuse_sd15 (line 10) | def apply_layerdiffuse_sd15(pipeline):
  function apply_layerdiffuse_sdxl_attn (line 21) | def apply_layerdiffuse_sdxl_attn(pipeline):
  function apply_layerdiffuse_sdxl_conv (line 31) | def apply_layerdiffuse_sdxl_conv(pipeline):
  function apply_layerdiffuse (line 43) | def apply_layerdiffuse():

FILE: scripts/layerdiffuse/layerdiffuse_loader.py
  function merge_delta_weights_into_unet (line 5) | def merge_delta_weights_into_unet(pipe, delta_weights):
  function get_attr (line 19) | def get_attr(obj, attr):
  function load_lora_to_unet (line 26) | def load_lora_to_unet(unet, model_path, frames, device, dtype):

FILE: scripts/layerdiffuse/layerdiffuse_model.py
  function zero_module (line 20) | def zero_module(module):
  class LatentTransparencyOffsetEncoder (line 29) | class LatentTransparencyOffsetEncoder(torch.nn.Module):
    method __init__ (line 30) | def __init__(self, *args, **kwargs):
    method __call__ (line 52) | def __call__(self, x):
  class UNet1024 (line 57) | class UNet1024(ModelMixin, ConfigMixin):
    method __init__ (line 59) | def __init__(
    method forward (line 161) | def forward(self, x, latent):
  function checkerboard (line 187) | def checkerboard(shape):
  class TransparentVAEDecoder (line 191) | class TransparentVAEDecoder(AutoencoderKL):
    method __init__ (line 193) | def __init__(
    method set_transparent_decoder (line 212) | def set_transparent_decoder(self, sd, mod_number=1):
    method estimate_single_pass (line 221) | def estimate_single_pass(self, pixel, latent):
    method estimate_augmented (line 225) | def estimate_augmented(self, pixel, latent):
    method decode (line 255) | def decode(self, z: torch.Tensor, return_dict: bool = True, generator=...
  class TransparentVAEEncoder (line 291) | class TransparentVAEEncoder:
    method __init__ (line 292) | def __init__(self, sd, device="cpu", torch_dtype=torch.float32):
  class HookerLayers (line 302) | class HookerLayers(torch.nn.Module):
    method __init__ (line 303) | def __init__(self, layer_list):
  class AdditionalAttentionCondsEncoder (line 308) | class AdditionalAttentionCondsEncoder(torch.nn.Module):
    method __init__ (line 309) | def __init__(self):
    method __call__ (line 354) | def __call__(self, h):
  class LoraLoader (line 362) | class LoraLoader(torch.nn.Module):
    method __init__ (line 363) | def __init__(self, layer_list, use_control=False):
  class LoRALinearLayer (line 373) | class LoRALinearLayer(torch.nn.Module):
    method __init__ (line 374) | def __init__(self, in_features: int, out_features: int, rank: int = 256):
    method forward (line 379) | def forward(self, h, org):
  class AttentionSharingProcessor (line 388) | class AttentionSharingProcessor(nn.Module):
    method __init__ (line 389) | def __init__(self, module, frames=2, use_control=True, rank=256):
    method __call__ (line 432) | def __call__(

FILE: scripts/layerdiffuse_ext.py
  class Script (line 5) | class Script(scripts_manager.Script):
    method title (line 7) | def title(self):
    method show (line 10) | def show(self, is_img2img):
    method apply (line 13) | def apply(self):
    method reload (line 27) | def reload(self):
    method is_active (line 31) | def is_active(self):
    method ui (line 40) | def ui(self, _is_img2img):

FILE: scripts/lbm/base/base_model.py
  class BaseModel (line 7) | class BaseModel(nn.Module):
    method __init__ (line 8) | def __init__(self, config: ModelConfig):
    method on_fit_start (line 15) | def on_fit_start(self, device: torch.device | None = None, *args, **kw...
    method forward (line 27) | def forward(self, batch: Dict[str, Any], *args, **kwargs):
    method freeze (line 30) | def freeze(self):
    method to (line 36) | def to(self, *args, **kwargs):
    method compute_metrics (line 50) | def compute_metrics(self, batch: Dict[str, Any], *args, **kwargs):
    method sample (line 54) | def sample(self, batch: Dict[str, Any], *args, **kwargs):
    method log_samples (line 58) | def log_samples(self, batch: Dict[str, Any], *args, **kwargs):
    method on_train_batch_end (line 62) | def on_train_batch_end(self, batch: Dict[str, Any], *args, **kwargs):

FILE: scripts/lbm/base/model_config.py
  class ModelConfig (line 6) | class ModelConfig(BaseConfig):

FILE: scripts/lbm/config.py
  class BaseConfig (line 13) | class BaseConfig:
    method __post_init__ (line 19) | def __post_init__(self):
    method from_dict (line 23) | def from_dict(cls, config_dict: Dict[str, Any]) -> "BaseConfig":
    method _dict_from_json (line 39) | def _dict_from_json(cls, json_path: Union[str, os.PathLike]) -> Dict[s...
    method from_json (line 58) | def from_json(cls, json_path: str) -> "BaseConfig":
    method to_dict (line 80) | def to_dict(self) -> dict:
    method to_json_string (line 87) | def to_json_string(self):
    method save_json (line 94) | def save_json(self, file_path: str):
    method save_yaml (line 103) | def save_yaml(self, file_path: str):
    method from_yaml (line 113) | def from_yaml(cls, yaml_path: str) -> "BaseConfig":

FILE: scripts/lbm/embedders/base/base_conditioner.py
  class BaseConditioner (line 13) | class BaseConditioner(BaseModel):
    method __init__ (line 39) | def __init__(self, config: BaseConditionerConfig):
    method forward (line 46) | def forward(

FILE: scripts/lbm/embedders/base/base_conditioner_config.py
  class BaseConditionerConfig (line 6) | class BaseConditionerConfig(BaseConfig):
    method __post_init__ (line 18) | def __post_init__(self):

FILE: scripts/lbm/embedders/conditioners_wrapper.py
  class ConditionerWrapper (line 15) | class ConditionerWrapper(nn.Module):
    method __init__ (line 24) | def __init__(
    method conditioner_sanity_check (line 33) | def conditioner_sanity_check(self):
    method on_fit_start (line 40) | def on_fit_start(self, device: torch.device = None, *args, **kwargs):
    method forward (line 44) | def forward(
    method to (line 98) | def to(self, *args, **kwargs):

FILE: scripts/lbm/embedders/latents_concat/latents_concat_embedder_config.py
  class LatentsConcatEmbedderConfig (line 8) | class LatentsConcatEmbedderConfig(BaseConditionerConfig):
    method __post_init__ (line 20) | def __post_init__(self):

FILE: scripts/lbm/embedders/latents_concat/latents_concat_embedder_model.py
  class LatentsConcatEmbedder (line 9) | class LatentsConcatEmbedder(BaseConditioner):
    method __init__ (line 18) | def __init__(self, config: LatentsConcatEmbedderConfig):
    method forward (line 21) | def forward(

FILE: scripts/lbm/extract.py
  function extract_object (line 7) | def extract_object(birefnet, img):
  function resize_and_center_crop (line 31) | def resize_and_center_crop(image, target_width, target_height):

FILE: scripts/lbm/inference.py
  function evaluate (line 28) | def evaluate(

FILE: scripts/lbm/lbm/lbm_config.py
  class LBMConfig (line 7) | class LBMConfig(ModelConfig):
    method __post_init__ (line 83) | def __post_init__(self):

FILE: scripts/lbm/lbm/lbm_model.py
  class LBMModel (line 15) | class LBMModel(BaseModel):
    method load_from_config (line 40) | def load_from_config(cls, config: LBMConfig):
    method __init__ (line 43) | def __init__(
    method on_fit_start (line 86) | def on_fit_start(self, device: torch.device | None = None, *args, **kw...
    method forward (line 94) | def forward(self, batch: Dict[str, Any], step=0, batch_idx=0, *args, *...
    method latent_loss (line 201) | def latent_loss(self, prediction, model_input, valid_latent_mask):
    method pixel_loss (line 222) | def pixel_loss(self, prediction, model_input, valid_mask):
    method _get_conditioning (line 304) | def _get_conditioning(
    method _timestep_sampling (line 327) | def _timestep_sampling(self, n_samples=1, device="cpu"):
    method _predicted_x_0 (line 357) | def _predicted_x_0(
    method _get_sigmas (line 369) | def _get_sigmas(
    method sample (line 383) | def sample(
    method log_samples (line 455) | def log_samples(

FILE: scripts/lbm/tiler.py
  class Tiler (line 12) | class Tiler:
    method get_tiles (line 13) | def get_tiles(
    method merge_tiles (line 84) | def merge_tiles(
    method _average_merge_tiles (line 105) | def _average_merge_tiles(self, tiles: List[List[torch.tensor]]) -> tor...
    method _gaussian_weights (line 156) | def _gaussian_weights(
    method _gaussian_merge_tiles (line 206) | def _gaussian_merge_tiles(self, tiles: List[List[torch.tensor]]) -> to...
    method _blend_v (line 260) | def _blend_v(
    method _blend_h (line 270) | def _blend_h(
    method _linear_merge_tiles (line 280) | def _linear_merge_tiles(self, tiles: List[List[torch.tensor]]) -> torc...
  function extract_into_tensor (line 316) | def extract_into_tensor(
  function pad (line 333) | def pad(x: torch.Tensor, base_h: int, base_w: int) -> torch.Tensor:
  function append_dims (line 352) | def append_dims(x: torch.Tensor, target_dims: int) -> torch.Tensor:
  function update_ema (line 363) | def update_ema(

FILE: scripts/lbm/unets/unet.py
  class DiffusersUNet2DWrapper (line 6) | class DiffusersUNet2DWrapper(UNet2DModel):
    method __init__ (line 13) | def __init__(self, *args, **kwargs):
    method forward (line 16) | def forward(
    method freeze (line 45) | def freeze(self):
  class DiffusersUNet2DCondWrapper (line 54) | class DiffusersUNet2DCondWrapper(UNet2DConditionModel):
    method __init__ (line 61) | def __init__(self, *args, **kwargs):
    method forward (line 65) | def forward(
    method freeze (line 141) | def freeze(self):

FILE: scripts/lbm/utils.py
  function get_model (line 19) | def get_model(
  function _get_model_from_config (line 86) | def _get_model_from_config(

FILE: scripts/lbm/vae/autoencoderKL.py
  class AutoencoderKLDiffusers (line 8) | class AutoencoderKLDiffusers(BaseModel):
    method __init__ (line 16) | def __init__(self, config: AutoencoderKLDiffusersConfig):
    method _get_properties (line 31) | def _get_properties(self):
    method encode (line 59) | def encode(self, x: torch.tensor, batch_size: int = 8):
    method decode (line 70) | def decode(self, z: torch.tensor):

FILE: scripts/lbm/vae/autoencoderKL_config.py
  class AutoencoderKLDiffusersConfig (line 7) | class AutoencoderKLDiffusersConfig(ModelConfig):

FILE: scripts/lbm_ext.py
  class Script (line 32) | class Script(scripts_manager.Script):
    method title (line 33) | def title(self):
    method show (line 36) | def show(self, is_img2img):
    method ui (line 40) | def ui(self, _is_img2img):
    method load (line 52) | def load(self, method: str):
    method run (line 76) | def run(self, p: processing.StableDiffusionProcessing, lbm_method, lbm...

FILE: scripts/ledits.py
  class Script (line 6) | class Script(scripts_manager.Script):
    method title (line 7) | def title(self):
    method show (line 10) | def show(self, is_img2img):
    method ui (line 14) | def ui(self, _is_img2img):
    method run (line 31) | def run(self, p: processing.StableDiffusionProcessing, edit_start, edi...

FILE: scripts/loopback.py
  class Script (line 10) | class Script(scripts_manager.Script):
    method title (line 11) | def title(self):
    method show (line 14) | def show(self, is_img2img):
    method ui (line 17) | def ui(self, is_img2img):
    method run (line 30) | def run(self, p, loops, final_denoising_strength, denoising_curve, ran...

FILE: scripts/lut.py
  class Script (line 11) | class Script(scripts_manager.Script):
    method title (line 12) | def title(self):
    method show (line 15) | def show(self, is_img2img): # pylint: disable=unused-argument
    method ui (line 18) | def ui(self, _is_img2img):
    method after (line 41) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/mixture_of_diffusers.py
  class Script (line 10) | class Script(scripts_manager.Script):
    method __init__ (line 11) | def __init__(self):
    method title (line 16) | def title(self):
    method show (line 19) | def show(self, is_img2img): # pylint: disable=unused-argument
    method update_ui (line 22) | def update_ui(self, x_tiles, y_tiles):
    method ui (line 29) | def ui(self, _is_img2img): # ui elements
    method calc_size (line 49) | def calc_size(self, size, tiles, overlap):
    method get_prompts (line 53) | def get_prompts(self, x_tiles, y_tiles, prompts, base_prompt, guidance):
    method check_dependencies (line 69) | def check_dependencies(self):
    method run (line 79) | def run(self, p: processing.StableDiffusionProcessing, *args): # pylin...
    method after (line 118) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/mixture_tiling.py
  function check_dependencies (line 9) | def check_dependencies():
  class Script (line 27) | class Script(scripts_manager.Script):
    method title (line 28) | def title(self):
    method show (line 31) | def show(self, is_img2img):
    method ui (line 34) | def ui(self, _is_img2img):
    method run (line 47) | def run(self, p: processing.StableDiffusionProcessing, x_size, y_size,...

FILE: scripts/mod/__init__.py
  function _tile2pixel_indices (line 86) | def _tile2pixel_indices(tile_row, tile_col, tile_width, tile_height, til...
  function _pixel2latent_indices (line 102) | def _pixel2latent_indices(px_row_init, px_row_end, px_col_init, px_col_e...
  function _tile2latent_indices (line 107) | def _tile2latent_indices(tile_row, tile_col, tile_width, tile_height, ti...
  function _tile2latent_exclusive_indices (line 122) | def _tile2latent_exclusive_indices(
  function _get_crops_coords_list (line 150) | def _get_crops_coords_list(num_rows, num_cols, output_width):
  function rescale_noise_cfg (line 195) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 222) | def retrieve_timesteps(
  class StableDiffusionXLTilingPipeline (line 282) | class StableDiffusionXLTilingPipeline(
    method __init__ (line 341) | def __init__(
    class SeedTilesMode (line 376) | class SeedTilesMode(Enum):
    method encode_prompt (line 382) | def encode_prompt(
    method prepare_extra_step_kwargs (line 621) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 638) | def check_inputs(self, prompt, height, width, grid_cols, seed_tiles_mo...
    method _get_add_time_ids (line 659) | def _get_add_time_ids(
    method _gaussian_weights (line 677) | def _gaussian_weights(self, tile_width, tile_height, nbatches, device,...
    method upcast_vae (line 702) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 721) | def get_guidance_scale_embedding(
    method guidance_scale (line 752) | def guidance_scale(self):
    method clip_skip (line 756) | def clip_skip(self):
    method do_classifier_free_guidance (line 763) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 767) | def cross_attention_kwargs(self):
    method num_timesteps (line 771) | def num_timesteps(self):
    method interrupt (line 775) | def interrupt(self):
    method __call__ (line 780) | def __call__(

FILE: scripts/mulan.py
  class Script (line 47) | class Script(scripts_manager.Script):
    method title (line 48) | def title(self):
    method show (line 51) | def show(self, is_img2img):
    method ui (line 54) | def ui(self, _is_img2img):
    method run (line 61) | def run(self, p: processing.StableDiffusionProcessing, selected_encode...

FILE: scripts/nudenet/bannedwords.py
  function check_banned (line 4) | def check_banned(words:str='', prompt:str='') -> list:

FILE: scripts/nudenet/imageguard.py
  function image_guard (line 95) | def image_guard(image, policy:str=None) -> str:

FILE: scripts/nudenet/langdetect.py
  function lang_detect (line 5) | def lang_detect(text:str, top:int=1, threshold:float=0.25) -> str:

FILE: scripts/nudenet/nudenet.py
  class NudeResult (line 46) | class NudeResult:
  class NudeDetector (line 53) | class NudeDetector:
    method __init__ (line 54) | def __init__(self, providers=None, model=None):
    method read_image (line 75) | def read_image(self, image, target_size=320):
    method postprocess (line 102) | def postprocess(self, output, resize_factor, pad_left, pad_top, min_sc...
    method pixelate (line 130) | def pixelate(self, image, blocks=3):
    method overlay (line 145) | def overlay(self, background, foreground, x_offset=None, y_offset=None):
    method detect (line 177) | def detect(self, image, min_score):
    method censor (line 187) | def censor(self, image, min_score=0.2, censor=None, method='pixelate',...
  function cli (line 224) | def cli():

FILE: scripts/nudenet_ext.py
  function create_ui (line 11) | def create_ui(accordion=True):
  function process (line 51) | def process(
  class Script (line 127) | class Script(scripts.Script):
    method title (line 131) | def title(self):
    method show (line 134) | def show(self, _is_img2img):
    method ui (line 138) | def ui(self, _is_img2img):
    method before_process (line 142) | def before_process(self, p: processing.StableDiffusionProcessing, enab...
    method postprocess_image (line 146) | def postprocess_image(self, p: processing.StableDiffusionProcessing, p...
  class ScriptPostprocessing (line 151) | class ScriptPostprocessing(scripts_postprocessing.ScriptPostprocessing):
    method ui (line 156) | def ui(self):
    method process (line 161) | def process(self, pp: scripts_postprocessing.PostprocessedImage, enabl...

FILE: scripts/outpainting_mk_2.py
  function get_matched_noise (line 11) | def get_matched_noise(_np_src_image, np_mask_rgb, noise_q=1, color_varia...
  class Script (line 102) | class Script(scripts_manager.Script):
    method title (line 103) | def title(self):
    method show (line 106) | def show(self, is_img2img):
    method ui (line 109) | def ui(self, is_img2img):
    method run (line 123) | def run(self, p, _, pixels, mask_blur, direction, noise_q, color_varia...

FILE: scripts/pixelsmith/autoencoder_kl.py
  class PixelSmithVAE (line 23) | class PixelSmithVAE(ModelMixin, ConfigMixin, FromOriginalModelMixin):
    method __init__ (line 58) | def __init__(
    method _set_gradient_checkpointing (line 114) | def _set_gradient_checkpointing(self, module, value=False):
    method enable_tiling (line 118) | def enable_tiling(self, use_tiling: bool = True):
    method disable_tiling (line 126) | def disable_tiling(self):
    method enable_slicing (line 133) | def enable_slicing(self):
    method disable_slicing (line 140) | def disable_slicing(self):
    method attn_processors (line 149) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 173) | def set_attn_processor(
    method set_default_attn_processor (line 210) | def set_default_attn_processor(self):
    method encode (line 226) | def encode(
    method _decode (line 258) | def _decode(self, z: torch.FloatTensor, return_dict: bool = True) -> U...
    method decode (line 271) | def decode(
    method blend_v (line 299) | def blend_v(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method blend_h (line 305) | def blend_h(self, a: torch.Tensor, b: torch.Tensor, blend_extent: int)...
    method tiled_encode (line 311) | def tiled_encode(self, x: torch.FloatTensor, return_dict: bool = True)...
    method tiled_decode (line 384) | def tiled_decode(self, z: torch.FloatTensor, return_dict: bool = True)...
    method forward (line 432) | def forward(
    method fuse_qkv_projections (line 461) | def fuse_qkv_projections(self):
    method unfuse_qkv_projections (line 485) | def unfuse_qkv_projections(self):

FILE: scripts/pixelsmith/pixelsmith_pipeline.py
  class PAGIdentitySelfAttnProcessor (line 76) | class PAGIdentitySelfAttnProcessor:
    method __init__ (line 81) | def __init__(self):
    method __call__ (line 85) | def __call__(
  class PAGCFGIdentitySelfAttnProcessor (line 189) | class PAGCFGIdentitySelfAttnProcessor:
    method __init__ (line 194) | def __init__(self):
    method __call__ (line 198) | def __call__(
  function rescale_noise_cfg (line 301) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_timesteps (line 316) | def retrieve_timesteps(
  class PixelSmithXLPipeline (line 361) | class PixelSmithXLPipeline(
    method __init__ (line 433) | def __init__(
    method encode_prompt (line 466) | def encode_prompt(
    method encode_image (line 701) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 726) | def prepare_ip_adapter_image_embeds(
    method prepare_extra_step_kwargs (line 778) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 795) | def check_inputs(
    method prepare_latents (line 892) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 909) | def _get_add_time_ids(
    method upcast_vae (line 927) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 948) | def get_guidance_scale_embedding(
    method pred_z0 (line 979) | def pred_z0(self, sample, model_output, timestep):
    method pred_x0 (line 999) | def pred_x0(self, latents, noise_pred, t, generator, device, prompt_em...
    method guidance_scale (line 1013) | def guidance_scale(self):
    method guidance_rescale (line 1017) | def guidance_rescale(self):
    method clip_skip (line 1021) | def clip_skip(self):
    method do_classifier_free_guidance (line 1028) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 1032) | def cross_attention_kwargs(self):
    method denoising_end (line 1036) | def denoising_end(self):
    method num_timesteps (line 1040) | def num_timesteps(self):
    method interrupt (line 1044) | def interrupt(self):
    method pag_scale (line 1050) | def pag_scale(self):
    method do_adversarial_guidance (line 1054) | def do_adversarial_guidance(self):
    method pag_adaptive_scaling (line 1058) | def pag_adaptive_scaling(self):
    method do_pag_adaptive_scaling (line 1062) | def do_pag_adaptive_scaling(self):
    method pag_drop_rate (line 1066) | def pag_drop_rate(self):
    method pag_applied_layers (line 1070) | def pag_applied_layers(self):
    method pag_applied_layers_index (line 1074) | def pag_applied_layers_index(self):
    method _random_crop (line 1078) | def _random_crop(self, z, i, j, patch_size):
    method get_value_coordinates (line 1082) | def get_value_coordinates(self, tensor):
    method __call__ (line 1089) | def __call__(

FILE: scripts/pixelsmith/vae.py
  class DecoderOutput (line 34) | class DecoderOutput(BaseOutput):
  class Encoder (line 46) | class Encoder(nn.Module):
    method __init__ (line 70) | def __init__(
    method forward (line 140) | def forward(self, sample: torch.FloatTensor) -> torch.FloatTensor:
  class Decoder (line 185) | class Decoder(nn.Module):
    method __init__ (line 208) | def __init__(
    method forward (line 285) | def forward(
  class UpSample (line 351) | class UpSample(nn.Module):
    method __init__ (line 362) | def __init__(
    method forward (line 372) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:
  class MaskConditionEncoder (line 379) | class MaskConditionEncoder(nn.Module):
    method __init__ (line 384) | def __init__(
    method forward (line 421) | def forward(self, x: torch.FloatTensor, mask=None) -> torch.FloatTensor:
  class MaskConditionDecoder (line 432) | class MaskConditionDecoder(nn.Module):
    method __init__ (line 455) | def __init__(
    method forward (line 537) | def forward(
  class VectorQuantizer (line 647) | class VectorQuantizer(nn.Module):
    method __init__ (line 656) | def __init__(
    method remap_to_used (line 689) | def remap_to_used(self, inds: torch.LongTensor) -> torch.LongTensor:
    method unmap_to_all (line 703) | def unmap_to_all(self, inds: torch.LongTensor) -> torch.LongTensor:
    method forward (line 713) | def forward(self, z: torch.FloatTensor) -> Tuple[torch.FloatTensor, to...
    method get_codebook_entry (line 747) | def get_codebook_entry(self, indices: torch.LongTensor, shape: Tuple[i...
  class DiagonalGaussianDistribution (line 765) | class DiagonalGaussianDistribution(object):
    method __init__ (line 766) | def __init__(self, parameters: torch.Tensor, deterministic: bool = Fal...
    method sample (line 778) | def sample(self, generator: Optional[torch.Generator] = None) -> torch...
    method kl (line 789) | def kl(self, other: "DiagonalGaussianDistribution" = None) -> torch.Te...
    method nll (line 808) | def nll(self, sample: torch.Tensor, dims: Tuple[int, ...] = [1, 2, 3])...
    method mode (line 817) | def mode(self) -> torch.Tensor:
  class EncoderTiny (line 821) | class EncoderTiny(nn.Module):
    method __init__ (line 839) | def __init__(
    method forward (line 875) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:
  class DecoderTiny (line 897) | class DecoderTiny(nn.Module):
    method __init__ (line 917) | def __init__(
    method forward (line 957) | def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:

FILE: scripts/pixelsmith_ext.py
  class Script (line 6) | class Script(scripts_manager.Script):
    method __init__ (line 7) | def __init__(self):
    method title (line 13) | def title(self):
    method show (line 16) | def show(self, is_img2img):
    method ui (line 19) | def ui(self, _is_img2img): # ui elements
    method encode (line 26) | def encode(self, p: processing.StableDiffusionProcessing, image: Image...
    method run (line 48) | def run(self, p: processing.StableDiffusionProcessing, slider: int = 2...
    method after (line 70) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/poor_mans_outpainting.py
  class Script (line 9) | class Script(scripts_manager.Script):
    method title (line 10) | def title(self):
    method show (line 13) | def show(self, is_img2img):
    method ui (line 16) | def ui(self, is_img2img):
    method run (line 28) | def run(self, p, pixels, mask_blur, direction): # pylint: disable=argu...

FILE: scripts/postprocessing_codeformer.py
  class ScriptPostprocessingCodeFormer (line 8) | class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostpr...
    method ui (line 12) | def ui(self):
    method process (line 19) | def process(self, pp: scripts_postprocessing.PostprocessedImage, codef...

FILE: scripts/postprocessing_gfpgan.py
  class ScriptPostprocessingGfpGan (line 7) | class ScriptPostprocessingGfpGan(scripts_postprocessing.ScriptPostproces...
    method ui (line 11) | def ui(self):
    method process (line 17) | def process(self, pp: scripts_postprocessing.PostprocessedImage, gfpga...

FILE: scripts/postprocessing_pixelart.py
  class ScriptPixelArt (line 4) | class ScriptPixelArt(scripts_postprocessing.ScriptPostprocessing):
    method ui (line 8) | def ui(self):
    method process (line 27) | def process(self, pp: scripts_postprocessing.PostprocessedImage, pixel...

FILE: scripts/postprocessing_upscale.py
  class ScriptPostprocessingUpscale (line 8) | class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostproce...
    method ui (line 12) | def ui(self):
    method upscale (line 51) | def upscale(self, image, info, upscaler, upscale_mode, upscale_by,  up...
    method process (line 65) | def process(self, pp: scripts_postprocessing.PostprocessedImage, upsca...
    method image_changed (line 89) | def image_changed(self):
  class ScriptPostprocessingUpscaleSimple (line 93) | class ScriptPostprocessingUpscaleSimple(ScriptPostprocessingUpscale):
    method ui (line 97) | def ui(self):
    method process (line 106) | def process(self, pp: scripts_postprocessing.PostprocessedImage, upsca...

FILE: scripts/postprocessing_video.py
  class ScriptPostprocessingUpscale (line 6) | class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostproce...
    method ui (line 9) | def ui(self):
    method postprocess (line 46) | def postprocess(self, images, filename, video_type, duration, loop, pa...

FILE: scripts/prompt_enhance.py
  function b64 (line 20) | def b64(image):
  function is_vision_model (line 32) | def is_vision_model(model_name: str) -> bool:
  function is_thinking_model (line 39) | def is_thinking_model(model_name: str) -> bool:
  function get_model_display_name (line 56) | def get_model_display_name(model_repo: str) -> str:
  function get_model_repo_from_display (line 66) | def get_model_repo_from_display(display_name: str) -> str:
  function keep_think_block_open (line 76) | def keep_think_block_open(text_prompt: str) -> str:
  class Options (line 93) | class Options:
    method get_model_choices (line 171) | def get_model_choices():
    method get_default_display (line 176) | def get_default_display():
  class Script (line 181) | class Script(scripts_manager.Script):
    method title (line 190) | def title(self):
    method show (line 193) | def show(self, _is_img2img):
    method compile (line 196) | def compile(self):
    method load (line 202) | def load(self, name:str=None, model_repo:str=None, model_gguf:str=None...
    method censored (line 292) | def censored(self, response):
    method unload (line 296) | def unload(self):
    method clean (line 309) | def clean(self, response, keep_thinking=False, prefill_text='', keep_p...
    method post (line 369) | def post(self, response, prefix, suffix, networks):
    method extract (line 381) | def extract(self, prompt):
    method enhance (line 387) | def enhance(self, model: str=None, prompt:str=None, system:str=None, p...
    method apply (line 629) | def apply(self, prompt, image, apply_prompt, llm_model, prompt_system,...
    method get_custom (line 654) | def get_custom(self, name):
    method update_vision_toggle (line 663) | def update_vision_toggle(self, model_name):
    method ui (line 670) | def ui(self, _is_img2img):
    method after_component (line 746) | def after_component(self, component, **kwargs): # searching for actual...
    method before_process (line 754) | def before_process(self, p: processing.StableDiffusionProcessing, *arg...

FILE: scripts/prompt_matrix.py
  class Script (line 9) | class Script(scripts_manager.Script):
    method title (line 10) | def title(self):
    method ui (line 13) | def ui(self, is_img2img):
    method run (line 27) | def run(self, p, put_at_start, different_seeds, prompt_type, variation...

FILE: scripts/prompts_from_file.py
  function process_string_tag (line 10) | def process_string_tag(tag):
  function process_int_tag (line 14) | def process_int_tag(tag):
  function process_float_tag (line 18) | def process_float_tag(tag):
  function process_boolean_tag (line 22) | def process_boolean_tag(tag):
  function cmdargs (line 54) | def cmdargs(line):
  function load_prompt_file (line 84) | def load_prompt_file(file):
  class Script (line 96) | class Script(scripts_manager.Script):
    method title (line 97) | def title(self):
    method ui (line 100) | def ui(self, is_img2img):
    method run (line 112) | def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt:...

FILE: scripts/pulid/attention_processor.py
  class AttnProcessor (line 12) | class AttnProcessor(nn.Module):
    method __init__ (line 13) | def __init__(self):
    method __call__ (line 16) | def __call__(
  class IDAttnProcessor (line 79) | class IDAttnProcessor(nn.Module):
    method __init__ (line 91) | def __init__(self, hidden_size, cross_attention_dim=None):
    method __call__ (line 96) | def __call__(
  class AttnProcessor2_0 (line 191) | class AttnProcessor2_0(nn.Module):
    method __init__ (line 196) | def __init__(self):
    method __call__ (line 201) | def __call__(
  class IDAttnProcessor2_0 (line 277) | class IDAttnProcessor2_0(torch.nn.Module):
    method __init__ (line 287) | def __init__(self, hidden_size, cross_attention_dim=None):
    method __call__ (line 295) | def __call__(

FILE: scripts/pulid/encoders_transformer.py
  function FeedForward (line 7) | def FeedForward(dim, mult=4):
  function reshape_tensor (line 17) | def reshape_tensor(x, heads):
  class PerceiverAttentionCA (line 28) | class PerceiverAttentionCA(nn.Module):
    method __init__ (line 29) | def __init__(self, *, dim=3072, dim_head=128, heads=16, kv_dim=2048):
    method forward (line 41) | def forward(self, x, latents):
  class PerceiverAttention (line 68) | class PerceiverAttention(nn.Module):
    method __init__ (line 69) | def __init__(self, *, dim, dim_head=64, heads=8, kv_dim=None):
    method forward (line 81) | def forward(self, x, latents):
  class IDFormer (line 109) | class IDFormer(nn.Module):
    method __init__ (line 117) | def __init__(
    method forward (line 175) | def forward(self, x, y):
  class IDEncoder (line 192) | class IDEncoder(nn.Module):
    method __init__ (line 193) | def __init__(self, width=1280, context_dim=2048, num_token=5):
    method forward (line 237) | def forward(self, x, y):

FILE: scripts/pulid/eva_clip/eva_vit_model.py
  class DropPath (line 33) | class DropPath(nn.Module):
    method __init__ (line 36) | def __init__(self, drop_prob=None):
    method forward (line 40) | def forward(self, x):
    method extra_repr (line 43) | def extra_repr(self) -> str:
  class Mlp (line 47) | class Mlp(nn.Module):
    method __init__ (line 48) | def __init__(
    method forward (line 70) | def forward(self, x):
  class SwiGLU (line 81) | class SwiGLU(nn.Module):
    method __init__ (line 82) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 97) | def forward(self, x):
  class Attention (line 106) | class Attention(nn.Module):
    method __init__ (line 107) | def __init__(
    method forward (line 173) | def forward(self, x, rel_pos_bias=None, attn_mask=None):
  class Block (line 246) | class Block(nn.Module):
    method __init__ (line 248) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
    method forward (line 287) | def forward(self, x, rel_pos_bias=None, attn_mask=None):
  class PatchEmbed (line 305) | class PatchEmbed(nn.Module):
    method __init__ (line 308) | def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=...
    method forward (line 320) | def forward(self, x, **kwargs):
  class RelativePositionBias (line 329) | class RelativePositionBias(nn.Module):
    method __init__ (line 331) | def __init__(self, window_size, num_heads):
    method forward (line 358) | def forward(self):
  class EVAVisionTransformer (line 366) | class EVAVisionTransformer(nn.Module):
    method __init__ (line 369) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
    method fix_init_weight (line 447) | def fix_init_weight(self):
    method get_cast_dtype (line 458) | def get_cast_dtype(self) -> torch.dtype:
    method _init_weights (line 461) | def _init_weights(self, m):
    method get_num_layers (line 470) | def get_num_layers(self):
    method lock (line 473) | def lock(self, unlocked_groups=0, freeze_bn_stats=False):
    method set_grad_checkpointing (line 479) | def set_grad_checkpointing(self, enable=True):
    method no_weight_decay (line 483) | def no_weight_decay(self):
    method get_classifier (line 486) | def get_classifier(self):
    method reset_classifier (line 489) | def reset_classifier(self, num_classes, global_pool=''):
    method forward_features (line 493) | def forward_features(self, x, return_all_features=False, return_hidden...
    method forward (line 541) | def forward(self, x, return_all_features=False, return_hidden=False, s...

FILE: scripts/pulid/eva_clip/factory.py
  function _natural_key (line 25) | def _natural_key(string_):
  function _rescan_model_configs (line 29) | def _rescan_model_configs():
  function list_models (line 53) | def list_models():
  function add_model_config (line 58) | def add_model_config(path):
  function get_model_config (line 66) | def get_model_config(model_name):
  function get_tokenizer (line 73) | def get_tokenizer(model_name):
  function load_state_dict (line 80) | def load_state_dict(checkpoint_path: str, map_location: str='cpu', model...
  function load_checkpoint (line 110) | def load_checkpoint(model, checkpoint_path, model_key="model|module|stat...
  function load_clip_visual_state_dict (line 131) | def load_clip_visual_state_dict(checkpoint_path: str, map_location: str=...
  function load_clip_text_state_dict (line 144) | def load_clip_text_state_dict(checkpoint_path: str, map_location: str='c...
  function get_pretrained_tag (line 152) | def get_pretrained_tag(pretrained_model):
  function load_pretrained_checkpoint (line 163) | def load_pretrained_checkpoint(
  function create_model (line 211) | def create_model(
  function create_model_and_transforms (line 358) | def create_model_and_transforms(
  function create_transforms (line 413) | def create_transforms(
  function create_model_from_pretrained (line 469) | def create_model_from_pretrained(

FILE: scripts/pulid/eva_clip/hf_model.py
  class BaseModelOutput (line 21) | class BaseModelOutput:
  class PretrainedConfig (line 25) | class PretrainedConfig:
  function _camel2snake (line 31) | def _camel2snake(s):
  function register_pooler (line 36) | def register_pooler(cls):
  class MeanPooler (line 43) | class MeanPooler(nn.Module):
    method forward (line 45) | def forward(self, x:BaseModelOutput, attention_mask:TensorType):
  class MaxPooler (line 50) | class MaxPooler(nn.Module):
    method forward (line 52) | def forward(self, x:BaseModelOutput, attention_mask:TensorType):
  class ClsPooler (line 57) | class ClsPooler(nn.Module):
    method __init__ (line 59) | def __init__(self, use_pooler_output=True):
    method forward (line 64) | def forward(self, x:BaseModelOutput, attention_mask:TensorType):
  class HFTextEncoder (line 74) | class HFTextEncoder(nn.Module):
    method __init__ (line 76) | def __init__(
    method mask (line 149) | def mask(self, input_ids, vocab_size, device, targets=None, masked_ind...
    method forward_mlm (line 174) | def forward_mlm(self, input_ids, image_embeds, mlm_probability=0.25):
    method forward (line 210) | def forward(self, x:TensorType) -> TensorType:
    method lock (line 217) | def lock(self, unlocked_layers:int=0, freeze_layer_norm:bool=True):
    method set_grad_checkpointing (line 235) | def set_grad_checkpointing(self, enable=True):
    method get_num_layers (line 238) | def get_num_layers(self):
    method init_parameters (line 243) | def init_parameters(self):

FILE: scripts/pulid/eva_clip/loss.py
  function gather_features (line 21) | def gather_features(
  class ClipLoss (line 70) | class ClipLoss(nn.Module):
    method __init__ (line 72) | def __init__(
    method forward (line 95) | def forward(self, image_features, text_features, logit_scale=1.):

FILE: scripts/pulid/eva_clip/model.py
  class CLIPVisionCfg (line 30) | class CLIPVisionCfg:
  class CLIPTextCfg (line 59) | class CLIPTextCfg:
  function get_cast_dtype (line 76) | def get_cast_dtype(precision: str):
  function _build_vision_tower (line 85) | def _build_vision_tower(
  function _build_text_tower (line 166) | def _build_text_tower(
  class CLIP (line 203) | class CLIP(nn.Module):
    method __init__ (line 204) | def __init__(
    method lock_image_tower (line 226) | def lock_image_tower(self, unlocked_groups=0, freeze_bn_stats=False):
    method set_grad_checkpointing (line 231) | def set_grad_checkpointing(self, enable=True):
    method no_weight_decay (line 236) | def no_weight_decay(self):
    method encode_image (line 239) | def encode_image(self, image, normalize: bool = False):
    method encode_text (line 243) | def encode_text(self, text, normalize: bool = False):
    method forward (line 257) | def forward(self, image, text):
  class CustomCLIP (line 263) | class CustomCLIP(nn.Module):
    method __init__ (line 264) | def __init__(
    method lock_image_tower (line 278) | def lock_image_tower(self, unlocked_groups=0, freeze_bn_stats=False):
    method lock_text_tower (line 282) | def lock_text_tower(self, unlocked_layers:int=0, freeze_layer_norm:boo...
    method set_grad_checkpointing (line 286) | def set_grad_checkpointing(self, enable=True):
    method no_weight_decay (line 291) | def no_weight_decay(self):
    method encode_image (line 294) | def encode_image(self, image, normalize: bool = False):
    method encode_text (line 298) | def encode_text(self, text, normalize: bool = False):
    method forward (line 302) | def forward(self, image, text):
  function convert_weights_to_lp (line 308) | def convert_weights_to_lp(model: nn.Module, dtype=torch.float16):
  function convert_to_custom_text_state_dict (line 340) | def convert_to_custom_text_state_dict(state_dict: dict):
  function build_model_from_openai_state_dict (line 359) | def build_model_from_openai_state_dict(
  function trace_model (line 419) | def trace_model(model, batch_size=256, device=torch.device('cpu')):

FILE: scripts/pulid/eva_clip/modified_resnet.py
  class Bottleneck (line 10) | class Bottleneck(nn.Module):
    method __init__ (line 13) | def __init__(self, inplanes, planes, stride=1):
    method forward (line 42) | def forward(self, x: torch.Tensor):
  class AttentionPool2d (line 58) | class AttentionPool2d(nn.Module):
    method __init__ (line 59) | def __init__(self, spacial_dim: int, embed_dim: int, num_heads: int, o...
    method forward (line 68) | def forward(self, x):
  class ModifiedResNet (line 95) | class ModifiedResNet(nn.Module):
    method __init__ (line 103) | def __init__(self, layers, output_dim, heads, image_size=224, width=64):
    method _make_layer (line 132) | def _make_layer(self, planes, blocks, stride=1):
    method init_parameters (line 141) | def init_parameters(self):
    method lock (line 154) | def lock(self, unlocked_groups=0, freeze_bn_stats=False):
    method set_grad_checkpointing (line 162) | def set_grad_checkpointing(self, enable=True):
    method stem (line 166) | def stem(self, x):
    method forward (line 173) | def forward(self, x):

FILE: scripts/pulid/eva_clip/openai.py
  function list_openai_models (line 18) | def list_openai_models() -> List[str]:
  function load_openai_model (line 23) | def load_openai_model(

FILE: scripts/pulid/eva_clip/pretrained.py
  function _pcfg (line 17) | def _pcfg(url='', hf_hub='', filename='', mean=None, std=None):
  function _clean_tag (line 190) | def _clean_tag(tag: str):
  function list_pretrained (line 195) | def list_pretrained(as_str: bool = False):
  function list_pretrained_models_by_tag (line 202) | def list_pretrained_models_by_tag(tag: str):
  function list_pretrained_tags_by_model (line 212) | def list_pretrained_tags_by_model(model: str):
  function is_pretrained_cfg (line 220) | def is_pretrained_cfg(model: str, tag: str):
  function get_pretrained_cfg (line 226) | def get_pretrained_cfg(model: str, tag: str):
  function get_pretrained_url (line 233) | def get_pretrained_url(model: str, tag: str):
  function download_pretrained_from_url (line 238) | def download_pretrained_from_url(
  function has_hf_hub (line 284) | def has_hf_hub(necessary=False):
  function download_pretrained_from_hf (line 292) | def download_pretrained_from_hf(
  function download_pretrained (line 303) | def download_pretrained(

FILE: scripts/pulid/eva_clip/rope.py
  function broadcat (line 7) | def broadcat(tensors, dim = -1):
  function rotate_half (line 23) | def rotate_half(x):
  class VisionRotaryEmbedding (line 30) | class VisionRotaryEmbedding(nn.Module):
    method __init__ (line 31) | def __init__(
    method forward (line 70) | def forward(self, t, start_index = 0):
  class VisionRotaryEmbeddingFast (line 79) | class VisionRotaryEmbeddingFast(nn.Module):
    method __init__ (line 80) | def __init__(
    method forward (line 121) | def forward(self, t, patch_indices_keep=None):

FILE: scripts/pulid/eva_clip/timm_model.py
  class TimmModel (line 28) | class TimmModel(nn.Module):
    method __init__ (line 33) | def __init__(
    method lock (line 78) | def lock(self, unlocked_groups=0, freeze_bn_stats=False):
    method set_grad_checkpointing (line 110) | def set_grad_checkpointing(self, enable=True):
    method forward (line 116) | def forward(self, x):

FILE: scripts/pulid/eva_clip/tokenizer.py
  function default_bpe (line 21) | def default_bpe():
  function bytes_to_unicode (line 26) | def bytes_to_unicode():
  function get_pairs (line 48) | def get_pairs(word):
  function basic_clean (line 60) | def basic_clean(text):
  function whitespace_clean (line 66) | def whitespace_clean(text):
  class SimpleTokenizer (line 72) | class SimpleTokenizer(object):
    method __init__ (line 73) | def __init__(self, bpe_path: str = default_bpe(), special_tokens=None):
    method bpe (line 98) | def bpe(self, token):
    method encode (line 139) | def encode(self, text):
    method decode (line 147) | def decode(self, tokens):
  function tokenize (line 156) | def tokenize(texts: Union[str, List[str]], context_length: int = 77) -> ...
  class HFTokenizer (line 188) | class HFTokenizer:
    method __init__ (line 190) | def __init__(self, tokenizer_name:str):
    method __call__ (line 194) | def __call__(self, texts:Union[str, List[str]], context_length:int=77)...

FILE: scripts/pulid/eva_clip/transform.py
  class ResizeMaxSize (line 13) | class ResizeMaxSize(nn.Module):
    method __init__ (line 15) | def __init__(self, max_size, interpolation=InterpolationMode.BICUBIC, ...
    method forward (line 24) | def forward(self, img):
  function _convert_to_rgb (line 39) | def _convert_to_rgb(image):
  function image_transform (line 60) | def image_transform(

FILE: scripts/pulid/eva_clip/transformer.py
  class LayerNormFp32 (line 20) | class LayerNormFp32(nn.LayerNorm):
    method __init__ (line 22) | def __init__(self, *args, **kwargs):
    method forward (line 25) | def forward(self, x: torch.Tensor):
  class LayerNorm (line 36) | class LayerNorm(nn.LayerNorm):
    method forward (line 39) | def forward(self, x: torch.Tensor):
  class QuickGELU (line 44) | class QuickGELU(nn.Module):
    method forward (line 46) | def forward(self, x: torch.Tensor):
  class LayerScale (line 50) | class LayerScale(nn.Module):
    method __init__ (line 51) | def __init__(self, dim, init_values=1e-5, inplace=False):
    method forward (line 56) | def forward(self, x):
  class PatchDropout (line 59) | class PatchDropout(nn.Module):
    method __init__ (line 64) | def __init__(self, prob, exclude_first_token=True):
    method forward (line 71) | def forward(self, x):
  function _in_projection_packed (line 103) | def _in_projection_packed(
  class Attention (line 134) | class Attention(nn.Module):
    method __init__ (line 135) | def __init__(
    method forward (line 179) | def forward(self, x, attn_mask: Optional[torch.Tensor] = None):
  class CustomAttention (line 227) | class CustomAttention(nn.Module):
    method __init__ (line 228) | def __init__(
    method forward (line 270) | def forward(self, query: torch.Tensor, key: torch.Tensor, value: torch...
  class CustomResidualAttentionBlock (line 323) | class CustomResidualAttentionBlock(nn.Module):
    method __init__ (line 324) | def __init__(
    method forward (line 368) | def forward(self, q: torch.Tensor, k: torch.Tensor, v: torch.Tensor, a...
  class CustomTransformer (line 373) | class CustomTransformer(nn.Module):
    method __init__ (line 374) | def __init__(
    method get_cast_dtype (line 413) | def get_cast_dtype(self) -> torch.dtype:
    method forward (line 416) | def forward(self, q: torch.Tensor, k: torch.Tensor = None, v: torch.Te...
  class ResidualAttentionBlock (line 427) | class ResidualAttentionBlock(nn.Module):
    method __init__ (line 428) | def __init__(
    method attention (line 458) | def attention(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor]...
    method forward (line 464) | def forward(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] =...
  class Transformer (line 469) | class Transformer(nn.Module):
    method __init__ (line 470) | def __init__(
    method get_cast_dtype (line 492) | def get_cast_dtype(self) -> torch.dtype:
    method forward (line 495) | def forward(self, x: torch.Tensor, attn_mask: Optional[torch.Tensor] =...
  class VisionTransformer (line 504) | class VisionTransformer(nn.Module):
    method __init__ (line 505) | def __init__(
    method lock (line 551) | def lock(self, unlocked_groups=0, freeze_bn_stats=False):
    method get_num_layers (line 584) | def get_num_layers(self):
    method set_grad_checkpointing (line 588) | def set_grad_checkpointing(self, enable=True):
    method no_weight_decay (line 592) | def no_weight_decay(self):
    method forward (line 595) | def forward(self, x: torch.Tensor, return_all_features: bool=False):
  class TextTransformer (line 626) | class TextTransformer(nn.Module):
    method __init__ (line 627) | def __init__(
    method init_parameters (line 670) | def init_parameters(self):
    method set_grad_checkpointing (line 687) | def set_grad_checkpointing(self, enable=True):
    method no_weight_decay (line 691) | def no_weight_decay(self):
    method get_num_layers (line 695) | def get_num_layers(self):
    method build_attention_mask (line 698) | def build_attention_mask(self):
    method forward (line 706) | def forward(self, text, return_all_features: bool=False):

FILE: scripts/pulid/eva_clip/utils.py
  function resize_clip_pos_embed (line 13) | def resize_clip_pos_embed(state_dict, model, interpolation: str = 'bicub...
  function resize_visual_pos_embed (line 46) | def resize_visual_pos_embed(state_dict, model, interpolation: str = 'bic...
  function resize_evaclip_pos_embed (line 78) | def resize_evaclip_pos_embed(state_dict, model, interpolation: str = 'bi...
  function resize_eva_pos_embed (line 109) | def resize_eva_pos_embed(state_dict, model, interpolation: str = 'bicubi...
  function resize_rel_pos_embed (line 140) | def resize_rel_pos_embed(state_dict, model, interpolation: str = 'bicubi...
  function freeze_batch_norm_2d (line 237) | def freeze_batch_norm_2d(module, module_match={}, name=''):
  function _ntuple (line 277) | def _ntuple(n):
  function is_logging (line 292) | def is_logging(args):
  class AllGather (line 304) | class AllGather(torch.autograd.Function):
    method forward (line 311) | def forward(ctx, tensor, rank, world_size):
    method backward (line 319) | def backward(ctx, grad_output):

FILE: scripts/pulid/pulid_flux.py
  function apply_flux (line 7) | def apply_flux(pipe: FluxPipeline):
  function unapply_flux (line 26) | def unapply_flux(pipe: FluxPipeline):

FILE: scripts/pulid/pulid_sampling.py
  function append_zero (line 10) | def append_zero(x):
  function get_sigmas_karras (line 14) | def get_sigmas_karras(n, sigma_min, sigma_max, rho=7., device='cpu'):
  function get_sigmas_exponential (line 23) | def get_sigmas_exponential(n, sigma_min, sigma_max, device='cpu'):
  function get_sigmas_polyexponential (line 29) | def get_sigmas_polyexponential(n, sigma_min, sigma_max, rho=1., device='...
  function get_sigmas_vp (line 36) | def get_sigmas_vp(n, beta_d=19.9, beta_min=0.1, eps_s=1e-3, device='cpu'):
  function append_dims (line 43) | def append_dims(x, target_dims):
  function to_d (line 51) | def to_d(x, sigma, denoised):
  function get_ancestral_step (line 56) | def get_ancestral_step(sigma_from, sigma_to, eta=1.):
  function default_noise_sampler (line 66) | def default_noise_sampler(x):
  function inpaint_mask (line 70) | def inpaint_mask(x, i, steps, mask_args):
  class BatchedBrownianTree (line 79) | class BatchedBrownianTree:
    method __init__ (line 82) | def __init__(self, x, t0, t1, seed=None, **kwargs):
    method sort (line 97) | def sort(a, b):
    method __call__ (line 100) | def __call__(self, t0, t1):
  class BrownianTreeNoiseSampler (line 106) | class BrownianTreeNoiseSampler:
    method __init__ (line 121) | def __init__(self, x, sigma_min, sigma_max, seed=None, transform=lambd...
    method __call__ (line 126) | def __call__(self, sigma, sigma_next):
  function sample_euler (line 132) | def sample_euler(model, x, sigmas, extra_args=None, callback=None, disab...
  function sample_euler_ancestral (line 155) | def sample_euler_ancestral(model, x, sigmas, extra_args=None, callback=N...
  function linear_multistep_coeff (line 176) | def linear_multistep_coeff(order, t, i, j):
  function log_likelihood (line 190) | def log_likelihood(model, x, sigma_min, sigma_max, extra_args=None, atol...
  class PIDStepSizeController (line 213) | class PIDStepSizeController:
    method __init__ (line 215) | def __init__(self, h, pcoeff, icoeff, dcoeff, order=1, accept_safety=0...
    method limiter (line 224) | def limiter(self, x):
    method propose_step (line 227) | def propose_step(self, error):
  class DPMSolver (line 242) | class DPMSolver(nn.Module):
    method __init__ (line 245) | def __init__(self, model, extra_args=None, eps_callback=None, info_cal...
    method t (line 252) | def t(self, sigma):
    method sigma (line 255) | def sigma(self, t):
    method eps (line 258) | def eps(self, eps_cache, key, x, t, *args, **kwargs):
    method dpm_solver_1_step (line 267) | def dpm_solver_1_step(self, x, t, t_next, eps_cache=None):
    method dpm_solver_2_step (line 274) | def dpm_solver_2_step(self, x, t, t_next, r1=1 / 2, eps_cache=None):
    method dpm_solver_3_step (line 284) | def dpm_solver_3_step(self, x, t, t_next, r1=1 / 3, r2=2 / 3, eps_cach...
    method dpm_solver_fast (line 297) | def dpm_solver_fast(self, x, t_start, t_end, nfe, eta=0., s_noise=1., ...
    method dpm_solver_adaptive (line 336) | def dpm_solver_adaptive(self, x, t_start, t_end, order=3, rtol=0.05, a...
  function sample_dpmpp_2s_ancestral (line 391) | def sample_dpmpp_2s_ancestral(model, x, sigmas, extra_args=None, callbac...
  function sample_dpmpp_sde (line 427) | def sample_dpmpp_sde(model, x, sigmas, extra_args=None, callback=None, d...
  function sample_dpmpp_2m (line 471) | def sample_dpmpp_2m(model, x, sigmas, extra_args=None, callback=None, di...
  function sample_dpmpp_2m_sde (line 499) | def sample_dpmpp_2m_sde(model, x, sigmas, extra_args=None, callback=None...
  function sample_dpmpp_3m_sde (line 546) | def sample_dpmpp_3m_sde(model, x, sigmas, extra_args=None, callback=None...

FILE: scripts/pulid/pulid_sdxl.py
  class StableDiffusionXLPuLIDPipeline (line 31) | class StableDiffusionXLPuLIDPipeline:
    method __init__ (line 32) | def __init__(self,
    method sigma_min (line 130) | def sigma_min(self):
    method sigma_max (line 134) | def sigma_max(self):
    method timestep (line 137) | def timestep(self, sigma):
    method get_sigmas_karras (line 142) | def get_sigmas_karras(self, n, rho=7.0):
    method hack_unet_attn_layers (line 149) | def hack_unet_attn_layers(self, unet):
    method load_pretrain (line 180) | def load_pretrain(self):
    method to_gray (line 198) | def to_gray(self, img):
    method get_id_embedding (line 203) | def get_id_embedding(self, image_list):
    method set_progress_bar_config (line 286) | def set_progress_bar_config(self, bar_format: str = None, ncols: int =...
    method sample (line 292) | def sample(self, x, sigma, **extra_args):
    method init_latent (line 307) | def init_latent(self, seed, size, image, mask_image, strength, width, ...
    method __call__ (line 347) | def __call__(
  class StableDiffusionXLPuLIDPipelineImage (line 441) | class StableDiffusionXLPuLIDPipelineImage(StableDiffusionXLPuLIDPipeline):
    method __init__ (line 442) | def __init__(self, pipe: StableDiffusionXLPipeline, device: torch.devi...
  class StableDiffusionXLPuLIDPipelineInpaint (line 447) | class StableDiffusionXLPuLIDPipelineInpaint(StableDiffusionXLPuLIDPipeli...
    method __init__ (line 448) | def __init__(self, pipe: StableDiffusionXLPipeline, device: torch.devi...

FILE: scripts/pulid/pulid_utils.py
  function seed_everything (line 13) | def seed_everything(seed):
  function instantiate_from_config (line 21) | def instantiate_from_config(config):
  function get_obj_from_str (line 29) | def get_obj_from_str(string, reload=False):
  function drop_seq_token (line 37) | def drop_seq_token(seq, drop_rate=0.5):
  function import_model_class_from_model_name_or_path (line 45) | def import_model_class_from_model_name_or_path(
  function resize_numpy_image_long (line 65) | def resize_numpy_image_long(image, resize_long_edge=768):
  function img2tensor (line 77) | def img2tensor(imgs, bgr2rgb=True, float32=True):
  function tensor2img (line 105) | def tensor2img(tensor, rgb2bgr=True, out_type=np.uint8, min_max=(0, 1)):

FILE: scripts/pulid_ext.py
  class Script (line 16) | class Script(scripts_manager.Script):
    method __init__ (line 17) | def __init__(self):
    method title (line 24) | def title(self):
    method show (line 27) | def show(self, _is_img2img):
    method dependencies (line 30) | def dependencies(self):
    method register (line 37) | def register(self): # register xyz grid elements
    method decode_image (line 62) | def decode_image(self,  b64):
    method load_images (line 66) | def load_images(self, files):
    method ui (line 86) | def ui(self, _is_img2img):
    method run (line 107) | def run(
    method after (line 216) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...
    method run_sdxl (line 238) | def run_sdxl(self, p: processing.StableDiffusionProcessing, images: li...
    method run_flux (line 295) | def run_flux(self, p: processing.StableDiffusionProcessing, images: li...

FILE: scripts/regional_prompting.py
  function hijack_register_modules (line 9) | def hijack_register_modules(self, **kwargs):
  class Script (line 24) | class Script(scripts_manager.Script):
    method title (line 25) | def title(self):
    method show (line 28) | def show(self, is_img2img):
    method change (line 31) | def change(self, mode):
    method ui (line 34) | def ui(self, _is_img2img):
    method run (line 46) | def run(self, p: processing.StableDiffusionProcessing, mode, grid, pow...

FILE: scripts/resadapter.py
  class Script (line 20) | class Script(scripts_manager.Script):
    method title (line 21) | def title(self):
    method show (line 24) | def show(self, is_img2img):
    method ui (line 28) | def ui(self, _is_img2img):
    method run (line 36) | def run(self, p: processing.StableDiffusionProcessing, model, weight):...

FILE: scripts/sd_upscale.py
  class Script (line 9) | class Script(scripts_manager.Script):
    method title (line 10) | def title(self):
    method show (line 13) | def show(self, is_img2img):
    method ui (line 16) | def ui(self, is_img2img):
    method run (line 26) | def run(self, p, _, overlap, upscaler_index, scale_factor): # pylint: ...

FILE: scripts/skip_layer_guidance.py
  class Script (line 9) | class Script(scripts_manager.Script):
    method __init__ (line 10) | def __init__(self):
    method title (line 14) | def title(self):
    method show (line 17) | def show(self, is_img2img):
    method ui (line 21) | def ui(self, _is_img2img):
    method register (line 31) | def register(self): # register xyz grid elements
    method run (line 59) | def run(self, p: processing.StableDiffusionProcessing, layers: str = '...

FILE: scripts/softfill.py
  function rescale_noise_cfg (line 89) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  function retrieve_latents (line 104) | def retrieve_latents(
  function retrieve_timesteps (line 118) | def retrieve_timesteps(
  class StableDiffusionXLSoftFillPipeline (line 162) | class StableDiffusionXLSoftFillPipeline(
    method __init__ (line 228) | def __init__(
    method encode_prompt (line 263) | def encode_prompt(
    method prepare_extra_step_kwargs (line 501) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 518) | def check_inputs(
    method get_timesteps (line 608) | def get_timesteps(self, num_inference_steps, strength, device, denoisi...
    method prepare_latents (line 644) | def prepare_latents(
    method encode_image (line 713) | def encode_image(self, image, device, num_images_per_prompt, output_hi...
    method prepare_ip_adapter_image_embeds (line 738) | def prepare_ip_adapter_image_embeds(
    method _get_add_time_ids (line 789) | def _get_add_time_ids(
    method upcast_vae (line 841) | def upcast_vae(self):
    method get_guidance_scale_embedding (line 859) | def get_guidance_scale_embedding(
    method guidance_scale (line 890) | def guidance_scale(self):
    method guidance_rescale (line 894) | def guidance_rescale(self):
    method clip_skip (line 898) | def clip_skip(self):
    method do_classifier_free_guidance (line 905) | def do_classifier_free_guidance(self):
    method cross_attention_kwargs (line 909) | def cross_attention_kwargs(self):
    method denoising_end (line 913) | def denoising_end(self):
    method denoising_start (line 917) | def denoising_start(self):
    method num_timesteps (line 921) | def num_timesteps(self):
    method interrupt (line 925) | def interrupt(self):
    method __call__ (line 930) | def __call__(
  class Script (line 1610) | class Script(scripts_manager.Script):
    method title (line 1613) | def title(self):
    method show (line 1616) | def show(self, is_img2img):
    method ui (line 1619) | def ui(self, _is_img2img):
    method run (line 1629) | def run(self, p: processing.StableDiffusionProcessingImg2Img, enabled,...
    method after (line 1668) | def after(self, p: processing.StableDiffusionProcessingImg2Img, *args,...

FILE: scripts/stablevideodiffusion.py
  class Script (line 17) | class Script(scripts_manager.Script):
    method title (line 18) | def title(self):
    method show (line 21) | def show(self, is_img2img):
    method ui (line 25) | def ui(self, is_img2img):
    method _encode_image (line 45) | def _encode_image(self, image: torch.Tensor, device, num_videos_per_pr...
    method _decode_latents (line 55) | def _decode_latents(self, latents: torch.Tensor, num_frames: int, deco...
    method run (line 70) | def run(self, p: processing.StableDiffusionProcessing, model, num_fram...

FILE: scripts/style_aligned/inversion.py
  function _get_text_embeddings (line 30) | def _get_text_embeddings(prompt: str, tokenizer, text_encoder, device):
  function _encode_text_sdxl (line 50) | def _encode_text_sdxl(model: StableDiffusionXLPipeline, prompt: str) -> ...
  function _encode_text_sdxl_with_negative (line 62) | def _encode_text_sdxl_with_negative(model: StableDiffusionXLPipeline, pr...
  function _encode_image (line 71) | def _encode_image(model: StableDiffusionXLPipeline, image: np.ndarray) -...
  function _next_step (line 78) | def _next_step(model: StableDiffusionXLPipeline, model_output: T, timest...
  function _get_noise_pred (line 89) | def _get_noise_pred(model: StableDiffusionXLPipeline, latent: T, t: T, c...
  function _ddim_loop (line 98) | def _ddim_loop(model: StableDiffusionXLPipeline, z0, prompt, guidance_sc...
  function make_inversion_callback (line 110) | def make_inversion_callback(zts, offset: int = 0):
  function ddim_inversion (line 120) | def ddim_inversion(model: StableDiffusionXLPipeline, x0: np.ndarray, pro...

FILE: scripts/style_aligned/sa_handler.py
  class StyleAlignedArgs (line 31) | class StyleAlignedArgs:
  function expand_first (line 44) | def expand_first(feat: T, scale=1.,) -> T:
  function concat_first (line 55) | def concat_first(feat: T, dim=2, scale=1.) -> T:
  function calc_mean_std (line 60) | def calc_mean_std(feat, eps: float = 1e-5) -> tuple[T, T]:
  function adain (line 66) | def adain(feat: T) -> T:
  class DefaultAttentionProcessor (line 75) | class DefaultAttentionProcessor(nn.Module):
    method __init__ (line 77) | def __init__(self):
    method __call__ (line 81) | def __call__(self, attn: attention_processor.Attention, hidden_states,...
  class SharedAttentionProcessor (line 86) | class SharedAttentionProcessor(DefaultAttentionProcessor):
    method shifted_scaled_dot_product_attention (line 88) | def shifted_scaled_dot_product_attention(self, attn: attention_process...
    method shared_call (line 94) | def shared_call( # pylint: disable=unused-argument
    method __call__ (line 168) | def __call__(self, attn: attention_processor.Attention, hidden_states,...
    method __init__ (line 181) | def __init__(self, style_aligned_args: StyleAlignedArgs):
  function _get_switch_vec (line 192) | def _get_switch_vec(total_num_layers, level):
  function init_attention_processors (line 209) | def init_attention_processors(pipeline: StableDiffusionXLPipeline, style...
  function register_shared_norm (line 233) | def register_shared_norm(pipeline: StableDiffusionXLPipeline,
  class Handler (line 266) | class Handler:
    method register (line 268) | def register(self, style_aligned_args: StyleAlignedArgs):
    method remove (line 273) | def remove(self):
    method __init__ (line 279) | def __init__(self, pipeline: StableDiffusionXLPipeline):

FILE: scripts/style_aligned_ext.py
  class Script (line 14) | class Script(scripts_manager.Script):
    method title (line 15) | def title(self):
    method show (line 18) | def show(self, is_img2img):
    method reset (line 21) | def reset(self):
    method preset (line 27) | def preset(self, preset):
    method ui (line 35) | def ui(self, _is_img2img): # ui elements
    method run (line 61) | def run(self, p: processing.StableDiffusionProcessing, image, prompt, ...
    method after (line 113) | def after(self, p: processing.StableDiffusionProcessing, *args): # pyl...

FILE: scripts/t_gate.py
  class Script (line 6) | class Script(scripts_manager.Script):
    method title (line 7) | def title(self):
    method show (line 10) | def show(self, is_img2img):
    method ui (line 14) | def ui(self, _is_img2img):
    method run (line 23) | def run(self, p: processing.StableDiffusionProcessing, enabled, gate_s...

FILE: scripts/text2video.py
  class Script (line 24) | class Script(scripts_manager.Script):
    method title (line 25) | def title(self):
    method show (line 28) | def show(self, is_img2img):
    method ui (line 32) | def ui(self, is_img2img):
    method run (line 56) | def run(self, p: processing.StableDiffusionProcessing, model_name, use...

FILE: scripts/tiling.py
  function asymmetricConv2DConvForward (line 16) | def asymmetricConv2DConvForward(self, input: Tensor, weight: Tensor, bia...
  class Script (line 24) | class Script(scripts_manager.Script):
    method __init__ (line 25) | def __init__(self):
    method title (line 31) | def title(self):
    method show (line 34) | def show(self, is_img2img):
    method ui (line 37) | def ui(self, _is_img2img): # ui elements
    method run (line 48) | def run(self, p: processing.StableDiffusionProcessing, tilex:bool=Fals...
    method after (line 76) | def after(self, p: processing.StableDiffusionProcessing, processed: pr...

FILE: scripts/xadapter/adapter.py
  function conv_nd (line 10) | def conv_nd(dims, *args, **kwargs):
  function avg_pool_nd (line 23) | def avg_pool_nd(dims, *args, **kwargs):
  function get_parameter_dtype (line 36) | def get_parameter_dtype(parameter: torch.nn.Module):
  class Downsample (line 58) | class Downsample(nn.Module):
    method __init__ (line 67) | def __init__(self, channels, use_conv, dims=2, out_channels=None, padd...
    method forward (line 81) | def forward(self, x):
  class Upsample (line 86) | class Upsample(nn.Module):
    method __init__ (line 87) | def __init__(self, channels, use_conv, dims=2, out_channels=None, padd...
    method forward (line 100) | def forward(self, x, output_size):
  class Linear (line 105) | class Linear(nn.Module):
    method __init__ (line 106) | def __init__(self, temb_channels, out_channels):
    method forward (line 110) | def forward(self, x):
  class ResnetBlock (line 115) | class ResnetBlock(nn.Module):
    method __init__ (line 117) | def __init__(self, in_c, out_c, down, up, ksize=3, sk=False, use_conv=...
    method forward (line 146) | def forward(self, x, output_size=None, temb=None):
  class Adapter_XL (line 168) | class Adapter_XL(nn.Module):
    method __init__ (line 170) | def __init__(self, in_channels=[1280, 640, 320], out_channels=[1280, 1...
    method make_zero_conv (line 252) | def make_zero_conv(self, channels):
    method dtype (line 257) | def dtype(self) -> torch.dtype:
    method forward (line 263) | def forward(self, x, t=None):
  function zero_module (line 304) | def zero_module(module):

FILE: scripts/xadapter/pipeline_sd_xl_adapter.py
  function rescale_noise_cfg (line 68) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class StableDiffusionXLAdapterPipeline (line 82) | class StableDiffusionXLAdapterPipeline(DiffusionPipeline, FromSingleFile...
    method __init__ (line 121) | def __init__(
    method enable_vae_slicing (line 171) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 179) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 187) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 196) | def disable_vae_tiling(self):
    method enable_model_cpu_offload (line 203) | def enable_model_cpu_offload(self, gpu_id=0):
    method encode_prompt (line 235) | def encode_prompt(
    method prepare_extra_step_kwargs (line 427) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 444) | def check_inputs(
    method prepare_latents (line 518) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 535) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method upcast_vae (line 552) | def upcast_vae(self):
    method __call__ (line 572) | def __call__(
    method load_lora_weights (line 1038) | def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Uni...
    method save_lora_weights (line 1070) | def save_lora_weights(
    method _remove_text_encoder_monkey_patch (line 1103) | def _remove_text_encoder_monkey_patch(self):
    method _encode_prompt_sd1_5 (line 1107) | def _encode_prompt_sd1_5(
    method decode_latents_sd1_5 (line 1270) | def decode_latents_sd1_5(self, latents):
    method check_inputs_sd1_5 (line 1283) | def check_inputs_sd1_5(
    method prepare_xl_latents_from_sd_1_5 (line 1330) | def prepare_xl_latents_from_sd_1_5(
    method sd1_5_add_noise (line 1408) | def sd1_5_add_noise(self, init_latents, timestep, generator, device, d...
    method get_timesteps (line 1421) | def get_timesteps(self, num_inference_steps, strength, device, denoisi...
    method prepare_latents_sd1_5 (line 1445) | def prepare_latents_sd1_5(self, batch_size, num_channels_latents, heig...

FILE: scripts/xadapter/pipeline_sd_xl_adapter_controlnet.py
  function rescale_noise_cfg (line 75) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class StableDiffusionXLAdapterControlnetPipeline (line 89) | class StableDiffusionXLAdapterControlnetPipeline(DiffusionPipeline, From...
    method __init__ (line 128) | def __init__(
    method enable_vae_slicing (line 184) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 192) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 200) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 209) | def disable_vae_tiling(self):
    method enable_model_cpu_offload (line 216) | def enable_model_cpu_offload(self, gpu_id=0):
    method encode_prompt (line 249) | def encode_prompt(
    method prepare_extra_step_kwargs (line 441) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 458) | def check_inputs(
    method prepare_latents (line 532) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 549) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method upcast_vae (line 566) | def upcast_vae(self):
    method __call__ (line 586) | def __call__(
    method load_lora_weights (line 1254) | def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Uni...
    method save_lora_weights (line 1286) | def save_lora_weights(
    method _remove_text_encoder_monkey_patch (line 1319) | def _remove_text_encoder_monkey_patch(self):
    method _encode_prompt_sd1_5 (line 1323) | def _encode_prompt_sd1_5(
    method decode_latents_sd1_5 (line 1484) | def decode_latents_sd1_5(self, latents):
    method check_inputs_sd1_5 (line 1497) | def check_inputs_sd1_5(
    method prepare_latents_sd1_5 (line 1637) | def prepare_latents_sd1_5(self, batch_size, num_channels_latents, heig...
    method prepare_image (line 1654) | def prepare_image(
    method check_image (line 1684) | def check_image(self, image, prompt, prompt_embeds):
    method prepare_xl_latents_from_sd_1_5 (line 1721) | def prepare_xl_latents_from_sd_1_5(
    method get_timesteps (line 1796) | def get_timesteps(self, num_inference_steps, strength, device, denoisi...
    method sd1_5_add_noise (line 1820) | def sd1_5_add_noise(self, init_latents, timestep, generator, device, d...

FILE: scripts/xadapter/pipeline_sd_xl_adapter_controlnet_img2img.py
  function rescale_noise_cfg (line 75) | def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
  class StableDiffusionXLAdapterControlnetI2IPipeline (line 89) | class StableDiffusionXLAdapterControlnetI2IPipeline(DiffusionPipeline, F...
    method __init__ (line 128) | def __init__(
    method enable_vae_slicing (line 183) | def enable_vae_slicing(self):
    method disable_vae_slicing (line 191) | def disable_vae_slicing(self):
    method enable_vae_tiling (line 199) | def enable_vae_tiling(self):
    method disable_vae_tiling (line 208) | def disable_vae_tiling(self):
    method enable_model_cpu_offload (line 215) | def enable_model_cpu_offload(self, gpu_id=0):
    method encode_prompt (line 248) | def encode_prompt(
    method prepare_extra_step_kwargs (line 440) | def prepare_extra_step_kwargs(self, generator, eta):
    method check_inputs (line 457) | def check_inputs(
    method prepare_latents (line 531) | def prepare_latents(self, batch_size, num_channels_latents, height, wi...
    method _get_add_time_ids (line 548) | def _get_add_time_ids(self, original_size, crops_coords_top_left, targ...
    method upcast_vae (line 565) | def upcast_vae(self):
    method __call__ (line 585) | def __call__(
    method load_lora_weights (line 1255) | def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Uni...
    method save_lora_weights (line 1287) | def save_lora_weights(
    method _remove_text_encoder_monkey_patch (line 1320) | def _remove_text_encoder_monkey_patch(self):
    method _encode_prompt_sd1_5 (line 1324) | def _encode_prompt_sd1_5(
    method decode_latents_sd1_5 (line 1487) | def decode_latents_sd1_5(self, latents):
    method check_inputs_sd1_5 (line 1500) | def check_inputs_sd1_5(
    method prepare_latents_sd1_5 (line 1656) | def prepare_latents_sd1_5(self, image, timestep, batch_size, num_image...
    method prepare_image (line 1714) | def prepare_image(
    method check_image (line 1744) | def check_image(self, image, prompt, prompt_embeds):
    method prepare_latents_from_noisy_latent (line 1781) | def prepare_latents_from_noisy_latent(self, latent, device, dtype, gen...
    method prepare_xl_latents_from_sd_1_5 (line 1800) | def prepare_xl_latents_from_sd_1_5(
    method get_timesteps (line 1877) | def get_timesteps(self, num_inference_steps, strength, device, denoisi...
    method sd1_5_add_noise (line 1901) | def sd1_5_add_noise(self, init_latents, timestep, generator, device, d...

FILE: scripts/xadapter/unet_adapter.py
  class UNet2DConditionOutput (line 49) | class UNet2DConditionOutput(BaseOutput):
  class UNet2DConditionModel (line 63) | class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoade...
    method __init__ (line 154) | def __init__(
    method attn_processors (line 578) | def attn_processors(self) -> Dict[str, AttentionProcessor]:
    method set_attn_processor (line 601) | def set_attn_processor(self, processor: Union[AttentionProcessor, Dict...
    method set_default_attn_processor (line 635) | def set_default_attn_processor(self):
    method set_attention_slice (line 641) | def set_attention_slice(self, slice_size):
    method _set_gradient_checkpointing (line 706) | def _set_gradient_checkpointing(self, module, value=False):
    method forward (line 710) | def forward(

FILE: scripts/xadapter/xadapter_hijacks.py
  class FourierEmbedder (line 5) | class FourierEmbedder(nn.Module):
    method __init__ (line 6) | def __init__(self, num_freqs=64, temperature=100):
    method __call__ (line 16) | def __call__(self, x):
  class PositionNet (line 21) | class PositionNet(nn.Module):
    method __init__ (line 22) | def __init__(self, positive_len, out_dim, fourier_freqs=8):
    method forward (line 43) | def forward(self, boxes, masks, positive_embeddings):

FILE: scripts/xadapter_ext.py
  class Script (line 13) | class Script(scripts_manager.Script):
    method title (line 14) | def title(self):
    method show (line 17) | def show(self, is_img2img):
    method ui (line 20) | def ui(self, _is_img2img):
    method run (line 36) | def run(self, p: processing.StableDiffusionProcessing, model, sampler,...

FILE: scripts/xyz/xyz_grid_classes.py
  class AxisOption (line 48) | class AxisOption:
    method __init__ (line 49) | def __init__(self, label, tipe, apply, fmt=format_value_add_label, con...
    method __repr__ (line 58) | def __repr__(self):
  class AxisOptionImg2Img (line 62) | class AxisOptionImg2Img(AxisOption):
    method __init__ (line 63) | def __init__(self, *args, **kwargs):
  class AxisOptionTxt2Img (line 68) | class AxisOptionTxt2Img(AxisOption):
    method __init__ (line 69) | def __init__(self, *args, **kwargs):
  class SharedSettingsStackHelper (line 74) | class SharedSettingsStackHelper():
    method __enter__ (line 111) | def __enter__(self):
    method __exit__ (line 146) | def __exit__(self, exc_type, exc_value, tb):

FILE: scripts/xyz/xyz_grid_draw.py
  function draw_xyz_grid (line 7) | def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, dra...

FILE: scripts/xyz/xyz_grid_shared.py
  function restore_comma (line 12) | def restore_comma(val: str):
  function apply_field (line 16) | def apply_field(field):
  function apply_task_arg (line 23) | def apply_task_arg(field):
  function apply_task_args (line 30) | def apply_task_args(p, x, xs):
  function apply_processing (line 40) | def apply_processing(p, x, xs):
  function apply_options (line 51) | def apply_options(p, x, xs):
  function apply_setting (line 62) | def apply_setting(field):
  function apply_seed (line 75) | def apply_seed(p, x, xs):
  function apply_prompt (line 81) | def apply_prompt(positive, negative, p, x, xs):
  function apply_prompt_primary (line 92) | def apply_prompt_primary(p, x, xs):
  function apply_prompt_refine (line 98) | def apply_prompt_refine(p, x, xs):
  function apply_prompt_detailer (line 102) | def apply_prompt_detailer(p, x, xs):
  function apply_prompt_all (line 106) | def apply_prompt_all(p, x, xs):
  function apply_order (line 112) | def apply_order(p, x, xs):
  function apply_sampler (line 129) | def apply_sampler(p, x, xs):
  function apply_hr_sampler_name (line 138) | def apply_hr_sampler_name(p, x, xs):
  function confirm_samplers (line 147) | def confirm_samplers(p, xs):
  function apply_sdnq_quant (line 153) | def apply_sdnq_quant(p, x, xs):
  function apply_sdnq_quant_te (line 160) | def apply_sdnq_quant_te(p, x, xs):
  function apply_checkpoint (line 167) | def apply_checkpoint(p, x, xs):
  function apply_refiner (line 179) | def apply_refiner(p, x, xs):
  function apply_unet (line 193) | def apply_unet(p, x, xs):
  function apply_clip_skip (line 204) | def apply_clip_skip(p, x, xs):
  function find_vae (line 209) | def find_vae(name: str):
  function apply_vae (line 223) | def apply_vae(p, x, xs):
  function list_lora (line 228) | def list_lora():
  function apply_lora (line 235) | def apply_lora(p, x, xs):
  function apply_lora_strength (line 245) | def apply_lora_strength(p, x, xs):
  function apply_te (line 254) | def apply_te(p, x, xs):
  function apply_guidance (line 260) | def apply_guidance(p, x, xs):
  function apply_styles (line 267) | def apply_styles(p: processing.StableDiffusionProcessingTxt2Img, x: str,...
  function apply_upscaler (line 272) | def apply_upscaler(p: processing.StableDiffusionProcessingTxt2Img, opt, x):
  function apply_context (line 280) | def apply_context(p: processing.StableDiffusionProcessingTxt2Img, opt, x):
  function apply_detailer (line 286) | def apply_detailer(p, opt, x):
  function apply_control (line 300) | def apply_control(field):
  function apply_override (line 359) | def apply_override(field):
  function format_bool (line 366) | def format_bool(p, opt, x):
  function format_value_add_label (line 370) | def format_value_add_label(p, opt, x):
  function format_value (line 376) | def format_value(p, opt, x):
  function format_value_join_list (line 382) | def format_value_join_list(p, opt, x):
  function do_nothing (line 386) | def do_nothing(p, x, xs):
  function format_nothing (line 390) | def format_nothing(p, opt, x):
  function str_permutations (line 394) | def str_permutations(x):
  function list_to_csv_string (line 399) | def list_to_csv_string(data_list: list):

FILE: scripts/xyz_grid.py
  class Script (line 24) | class Script(scripts_manager.Script):
    method title (line 27) | def title(self):
    method ui (line 30) | def ui(self, is_img2img):
    method run (line 159) | def run(self, p,

FILE: scripts/xyz_grid_on.py
  class Script (line 25) | class Script(scripts_manager.Script):
    method show (line 28) | def show(self, is_img2img):
    method title (line 31) | def title(self):
    method ui (line 34) | def ui(self, is_img2img):
    method process (line 167) | def process(self, p,
    method process_images (line 453) | def process_images(self, p, *args): # pylint: disable=W0221, W0613

FILE: webui.py
  function initialize (line 74) | def initialize():
  function load_model (line 162) | def load_model():
  function create_api (line 185) | def create_api(app):
  function async_policy (line 192) | def async_policy():
  function get_external_ip (line 217) | def get_external_ip():
  function get_remote_ip (line 228) | def get_remote_ip():
  function start_common (line 238) | def start_common():
  function mount_subpath (line 261) | def mount_subpath(app):
  function start_ui (line 273) | def start_ui():
  function webui (line 373) | def webui(restart=False):