mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
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65075896f2
Update pytorch lightning utilities
170 lines
5.7 KiB
Python
170 lines
5.7 KiB
Python
import importlib
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import logging
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import os
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import sys
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import warnings
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from threading import Thread
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from modules.timer import startup_timer
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def imports():
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logging.getLogger("torch.distributed.nn").setLevel(logging.ERROR) # sshh...
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logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
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import torch # noqa: F401
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startup_timer.record("import torch")
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import pytorch_lightning # noqa: F401
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startup_timer.record("import torch")
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warnings.filterwarnings(action="ignore", category=DeprecationWarning, module="pytorch_lightning")
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warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision")
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os.environ.setdefault('GRADIO_ANALYTICS_ENABLED', 'False')
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import gradio # noqa: F401
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startup_timer.record("import gradio")
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from modules import paths, timer, import_hook, errors # noqa: F401
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startup_timer.record("setup paths")
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import ldm.modules.encoders.modules # noqa: F401
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startup_timer.record("import ldm")
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import sgm.modules.encoders.modules # noqa: F401
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startup_timer.record("import sgm")
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from modules import shared_init
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shared_init.initialize()
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startup_timer.record("initialize shared")
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from modules import processing, gradio_extensons, ui # noqa: F401
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startup_timer.record("other imports")
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def check_versions():
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from modules.shared_cmd_options import cmd_opts
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if not cmd_opts.skip_version_check:
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from modules import errors
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errors.check_versions()
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def initialize():
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from modules import initialize_util
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initialize_util.fix_torch_version()
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initialize_util.fix_pytorch_lightning()
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initialize_util.fix_asyncio_event_loop_policy()
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initialize_util.validate_tls_options()
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initialize_util.configure_sigint_handler()
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initialize_util.configure_opts_onchange()
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from modules import sd_models
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sd_models.setup_model()
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startup_timer.record("setup SD model")
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from modules.shared_cmd_options import cmd_opts
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from modules import codeformer_model
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warnings.filterwarnings(action="ignore", category=UserWarning, module="torchvision.transforms.functional_tensor")
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codeformer_model.setup_model(cmd_opts.codeformer_models_path)
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startup_timer.record("setup codeformer")
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from modules import gfpgan_model
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gfpgan_model.setup_model(cmd_opts.gfpgan_models_path)
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startup_timer.record("setup gfpgan")
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initialize_rest(reload_script_modules=False)
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def initialize_rest(*, reload_script_modules=False):
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"""
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Called both from initialize() and when reloading the webui.
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"""
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from modules.shared_cmd_options import cmd_opts
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from modules import sd_samplers
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sd_samplers.set_samplers()
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startup_timer.record("set samplers")
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from modules import extensions
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extensions.list_extensions()
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startup_timer.record("list extensions")
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from modules import initialize_util
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initialize_util.restore_config_state_file()
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startup_timer.record("restore config state file")
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from modules import shared, upscaler, scripts
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if cmd_opts.ui_debug_mode:
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shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
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scripts.load_scripts()
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return
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from modules import sd_models
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sd_models.list_models()
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startup_timer.record("list SD models")
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from modules import localization
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localization.list_localizations(cmd_opts.localizations_dir)
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startup_timer.record("list localizations")
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with startup_timer.subcategory("load scripts"):
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scripts.load_scripts()
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if reload_script_modules and shared.opts.enable_reloading_ui_scripts:
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for module in [module for name, module in sys.modules.items() if name.startswith("modules.ui")]:
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importlib.reload(module)
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startup_timer.record("reload script modules")
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from modules import modelloader
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modelloader.load_upscalers()
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startup_timer.record("load upscalers")
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from modules import sd_vae
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sd_vae.refresh_vae_list()
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startup_timer.record("refresh VAE")
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from modules import textual_inversion
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textual_inversion.textual_inversion.list_textual_inversion_templates()
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startup_timer.record("refresh textual inversion templates")
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from modules import script_callbacks, sd_hijack_optimizations, sd_hijack
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script_callbacks.on_list_optimizers(sd_hijack_optimizations.list_optimizers)
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sd_hijack.list_optimizers()
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startup_timer.record("scripts list_optimizers")
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from modules import sd_unet
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sd_unet.list_unets()
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startup_timer.record("scripts list_unets")
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def load_model():
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"""
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Accesses shared.sd_model property to load model.
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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
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by that time, so we apply optimization again.
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"""
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from modules import devices
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devices.torch_npu_set_device()
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shared.sd_model # noqa: B018
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if sd_hijack.current_optimizer is None:
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sd_hijack.apply_optimizations()
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devices.first_time_calculation()
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if not shared.cmd_opts.skip_load_model_at_start:
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Thread(target=load_model).start()
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from modules import shared_items
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shared_items.reload_hypernetworks()
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startup_timer.record("reload hypernetworks")
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from modules import ui_extra_networks
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ui_extra_networks.initialize()
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ui_extra_networks.register_default_pages()
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from modules import extra_networks
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extra_networks.initialize()
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extra_networks.register_default_extra_networks()
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startup_timer.record("initialize extra networks")
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