stable-diffusion-webui/modules/initialize.py

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import importlib
import logging
import os
import sys
import warnings
from threading import Thread
from modules.timer import startup_timer
def imports():
logging.getLogger("torch.distributed.nn").setLevel(logging.ERROR) # sshh...
logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
import torch # noqa: F401
startup_timer.record("import torch")
import pytorch_lightning # noqa: F401
startup_timer.record("import torch")
warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
os.environ.setdefault('GRADIO_ANALYTICS_ENABLED', 'False')
import gradio # noqa: F401
startup_timer.record("import gradio")
from modules import paths, timer, import_hook, errors # noqa: F401
startup_timer.record("setup paths")
import ldm.modules.encoders.modules # noqa: F401
startup_timer.record("import ldm")
import sgm.modules.encoders.modules # noqa: F401
startup_timer.record("import sgm")
from modules import shared_init
shared_init.initialize()
startup_timer.record("initialize shared")
from modules import processing, gradio_extensons, ui # noqa: F401
startup_timer.record("other imports")
def check_versions():
from modules.shared_cmd_options import cmd_opts
if not cmd_opts.skip_version_check:
from modules import errors
errors.check_versions()
def initialize():
from modules import initialize_util
initialize_util.fix_torch_version()
initialize_util.fix_pytorch_lightning()
initialize_util.fix_asyncio_event_loop_policy()
initialize_util.validate_tls_options()
initialize_util.configure_sigint_handler()
initialize_util.configure_opts_onchange()
from modules import sd_models
sd_models.setup_model()
startup_timer.record("setup SD model")
from modules.shared_cmd_options import cmd_opts
from modules import codeformer_model
warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision.transforms.functional_tensor")
codeformer_model.setup_model(cmd_opts.codeformer_models_path)
startup_timer.record("setup codeformer")
from modules import gfpgan_model
gfpgan_model.setup_model(cmd_opts.gfpgan_models_path)
startup_timer.record("setup gfpgan")
initialize_rest(reload_script_modules=False)
def initialize_rest(*, reload_script_modules=False):
"""
Called both from initialize() and when reloading the webui.
"""
from modules.shared_cmd_options import cmd_opts
from modules import sd_samplers
sd_samplers.set_samplers()
startup_timer.record("set samplers")
from modules import extensions
extensions.list_extensions()
startup_timer.record("list extensions")
from modules import initialize_util
initialize_util.restore_config_state_file()
startup_timer.record("restore config state file")
from modules import shared, upscaler, scripts
if cmd_opts.ui_debug_mode:
shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
scripts.load_scripts()
return
from modules import sd_models
sd_models.list_models()
startup_timer.record("list SD models")
from modules import localization
localization.list_localizations(cmd_opts.localizations_dir)
startup_timer.record("list localizations")
with startup_timer.subcategory("load scripts"):
scripts.load_scripts()
if reload_script_modules and shared.opts.enable_reloading_ui_scripts:
for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]:
importlib.reload(module)
startup_timer.record("reload script modules")
from modules import modelloader
modelloader.load_upscalers()
startup_timer.record("load upscalers")
from modules import sd_vae
sd_vae.refresh_vae_list()
startup_timer.record("refresh VAE")
from modules import textual_inversion
textual_inversion.textual_inversion.list_textual_inversion_templates()
startup_timer.record("refresh textual inversion templates")
from modules import script_callbacks, sd_hijack_optimizations, sd_hijack
script_callbacks.on_list_optimizers(sd_hijack_optimizations.list_optimizers)
sd_hijack.list_optimizers()
startup_timer.record("scripts list_optimizers")
from modules import sd_unet
sd_unet.list_unets()
startup_timer.record("scripts list_unets")
def load_model():
"""
Accesses shared.sd_model property to load model.
After it's available, if it has been loaded before this access by some extension,
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its optimization may be None because the list of optimizers has not been filled
by that time, so we apply optimization again.
"""
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from modules import devices
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devices.torch_npu_set_device()
shared.sd_model # noqa: B018
if sd_hijack.current_optimizer is None:
sd_hijack.apply_optimizations()
devices.first_time_calculation()
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if not shared.cmd_opts.skip_load_model_at_start:
Thread(target=load_model).start()
from modules import shared_items
shared_items.reload_hypernetworks()
startup_timer.record("reload hypernetworks")
from modules import ui_extra_networks
ui_extra_networks.initialize()
ui_extra_networks.register_default_pages()
from modules import extra_networks
extra_networks.initialize()
extra_networks.register_default_extra_networks()
startup_timer.record("initialize extra networks")