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launch.py
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launch.py
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import os
import ssl
import sys
print('[System ARGV] ' + str(sys.argv))
root = os.path.dirname(os.path.abspath(__file__))
sys.path.append(root)
os.chdir(root)
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
os.environ["PYTORCH_MPS_HIGH_WATERMARK_RATIO"] = "0.0"
if "GRADIO_SERVER_PORT" not in os.environ:
os.environ["GRADIO_SERVER_PORT"] = "7865"
ssl._create_default_https_context = ssl._create_unverified_context
import platform
import fooocus_version
from build_launcher import build_launcher
from modules.launch_util import is_installed, run, python, run_pip, requirements_met, delete_folder_content
from modules.model_loader import load_file_from_url
REINSTALL_ALL = False
TRY_INSTALL_XFORMERS = False
def prepare_environment():
torch_index_url = os.environ.get('TORCH_INDEX_URL', "https://download.pytorch.org/whl/cu121")
torch_command = os.environ.get('TORCH_COMMAND',
f"pip install torch==2.1.0 torchvision==0.16.0 --extra-index-url {torch_index_url}")
requirements_file = os.environ.get('REQS_FILE', "requirements_versions.txt")
print(f"Python {sys.version}")
print(f"Fooocus version: {fooocus_version.version}")
if REINSTALL_ALL or not is_installed("torch") or not is_installed("torchvision"):
run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch", live=True)
if TRY_INSTALL_XFORMERS:
if REINSTALL_ALL or not is_installed("xformers"):
xformers_package = os.environ.get('XFORMERS_PACKAGE', 'xformers==0.0.23')
if platform.system() == "Windows":
if platform.python_version().startswith("3.10"):
run_pip(f"install -U -I --no-deps {xformers_package}", "xformers", live=True)
else:
print("Installation of xformers is not supported in this version of Python.")
print(
"You can also check this and build manually: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers#building-xformers-on-windows-by-duckness")
if not is_installed("xformers"):
exit(0)
elif platform.system() == "Linux":
run_pip(f"install -U -I --no-deps {xformers_package}", "xformers")
if REINSTALL_ALL or not requirements_met(requirements_file):
run_pip(f"install -r \"{requirements_file}\"", "requirements")
return
vae_approx_filenames = [
('xlvaeapp.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/xlvaeapp.pth'),
('vaeapp_sd15.pth', 'https://huggingface.co/lllyasviel/misc/resolve/main/vaeapp_sd15.pt'),
('xl-to-v1_interposer-v4.0.safetensors',
'https://huggingface.co/mashb1t/misc/resolve/main/xl-to-v1_interposer-v4.0.safetensors')
]
def ini_args():
from args_manager import args
return args
prepare_environment()
build_launcher()
args = ini_args()
if args.gpu_device_id is not None:
os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_device_id)
print("Set device to:", args.gpu_device_id)
if args.hf_mirror is not None :
os.environ['HF_MIRROR'] = str(args.hf_mirror)
print("Set hf_mirror to:", args.hf_mirror)
from modules import config
from modules.hash_cache import init_cache
os.environ["U2NET_HOME"] = config.path_inpaint
os.environ['GRADIO_TEMP_DIR'] = config.temp_path
if config.temp_path_cleanup_on_launch:
print(f'[Cleanup] Attempting to delete content of temp dir {config.temp_path}')
result = delete_folder_content(config.temp_path, '[Cleanup] ')
if result:
print("[Cleanup] Cleanup successful")
else:
print(f"[Cleanup] Failed to delete content of temp dir.")
def download_models(default_model, previous_default_models, checkpoint_downloads, embeddings_downloads, lora_downloads, vae_downloads):
for file_name, url in vae_approx_filenames:
load_file_from_url(url=url, model_dir=config.path_vae_approx, file_name=file_name)
load_file_from_url(
url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_expansion.bin',
model_dir=config.path_fooocus_expansion,
file_name='pytorch_model.bin'
)
if args.disable_preset_download:
print('Skipped model download.')
return default_model, checkpoint_downloads
if not args.always_download_new_model:
if not os.path.exists(os.path.join(config.paths_checkpoints[0], default_model)):
for alternative_model_name in previous_default_models:
if os.path.exists(os.path.join(config.paths_checkpoints[0], alternative_model_name)):
print(f'You do not have [{default_model}] but you have [{alternative_model_name}].')
print(f'Fooocus will use [{alternative_model_name}] to avoid downloading new models, '
f'but you are not using the latest models.')
print('Use --always-download-new-model to avoid fallback and always get new models.')
checkpoint_downloads = {}
default_model = alternative_model_name
break
for file_name, url in checkpoint_downloads.items():
load_file_from_url(url=url, model_dir=config.paths_checkpoints[0], file_name=file_name)
for file_name, url in embeddings_downloads.items():
load_file_from_url(url=url, model_dir=config.path_embeddings, file_name=file_name)
for file_name, url in lora_downloads.items():
load_file_from_url(url=url, model_dir=config.paths_loras[0], file_name=file_name)
for file_name, url in vae_downloads.items():
load_file_from_url(url=url, model_dir=config.path_vae, file_name=file_name)
return default_model, checkpoint_downloads
config.default_base_model_name, config.checkpoint_downloads = download_models(
config.default_base_model_name, config.previous_default_models, config.checkpoint_downloads,
config.embeddings_downloads, config.lora_downloads, config.vae_downloads)
config.update_files()
init_cache(config.model_filenames, config.paths_checkpoints, config.lora_filenames, config.paths_loras)
from webui import *