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