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| import os | |
| import json | |
| import math | |
| import numbers | |
| import args_manager | |
| import modules.flags | |
| import modules.sdxl_styles | |
| from modules.model_loader import load_file_from_url | |
| from modules.util import get_files_from_folder, makedirs_with_log | |
| from modules.flags import Performance, MetadataScheme | |
| def get_config_path(key, default_value): | |
| env = os.getenv(key) | |
| if env is not None and isinstance(env, str): | |
| print(f"Environment: {key} = {env}") | |
| return env | |
| else: | |
| return os.path.abspath(default_value) | |
| config_path = get_config_path('config_path', "./config.txt") | |
| config_example_path = get_config_path('config_example_path', "config_modification_tutorial.txt") | |
| config_dict = {} | |
| always_save_keys = [] | |
| visited_keys = [] | |
| try: | |
| with open(os.path.abspath(f'./presets/default.json'), "r", encoding="utf-8") as json_file: | |
| config_dict.update(json.load(json_file)) | |
| except Exception as e: | |
| print(f'Load default preset failed.') | |
| print(e) | |
| try: | |
| if os.path.exists(config_path): | |
| with open(config_path, "r", encoding="utf-8") as json_file: | |
| config_dict.update(json.load(json_file)) | |
| always_save_keys = list(config_dict.keys()) | |
| except Exception as e: | |
| print(f'Failed to load config file "{config_path}" . The reason is: {str(e)}') | |
| print('Please make sure that:') | |
| print(f'1. The file "{config_path}" is a valid text file, and you have access to read it.') | |
| print('2. Use "\\\\" instead of "\\" when describing paths.') | |
| print('3. There is no "," before the last "}".') | |
| print('4. All key/value formats are correct.') | |
| def try_load_deprecated_user_path_config(): | |
| global config_dict | |
| if not os.path.exists('user_path_config.txt'): | |
| return | |
| try: | |
| deprecated_config_dict = json.load(open('user_path_config.txt', "r", encoding="utf-8")) | |
| def replace_config(old_key, new_key): | |
| if old_key in deprecated_config_dict: | |
| config_dict[new_key] = deprecated_config_dict[old_key] | |
| del deprecated_config_dict[old_key] | |
| replace_config('modelfile_path', 'path_checkpoints') | |
| replace_config('lorafile_path', 'path_loras') | |
| replace_config('embeddings_path', 'path_embeddings') | |
| replace_config('vae_approx_path', 'path_vae_approx') | |
| replace_config('upscale_models_path', 'path_upscale_models') | |
| replace_config('inpaint_models_path', 'path_inpaint') | |
| replace_config('controlnet_models_path', 'path_controlnet') | |
| replace_config('clip_vision_models_path', 'path_clip_vision') | |
| replace_config('fooocus_expansion_path', 'path_fooocus_expansion') | |
| replace_config('temp_outputs_path', 'path_outputs') | |
| if deprecated_config_dict.get("default_model", None) == 'juggernautXL_version6Rundiffusion.safetensors': | |
| os.replace('user_path_config.txt', 'user_path_config-deprecated.txt') | |
| print('Config updated successfully in silence. ' | |
| 'A backup of previous config is written to "user_path_config-deprecated.txt".') | |
| return | |
| if input("Newer models and configs are available. " | |
| "Download and update files? [Y/n]:") in ['n', 'N', 'No', 'no', 'NO']: | |
| config_dict.update(deprecated_config_dict) | |
| print('Loading using deprecated old models and deprecated old configs.') | |
| return | |
| else: | |
| os.replace('user_path_config.txt', 'user_path_config-deprecated.txt') | |
| print('Config updated successfully by user. ' | |
| 'A backup of previous config is written to "user_path_config-deprecated.txt".') | |
| return | |
| except Exception as e: | |
| print('Processing deprecated config failed') | |
| print(e) | |
| return | |
| try_load_deprecated_user_path_config() | |
| preset = args_manager.args.preset | |
| if isinstance(preset, str): | |
| preset_path = os.path.abspath(f'./presets/{preset}.json') | |
| try: | |
| if os.path.exists(preset_path): | |
| with open(preset_path, "r", encoding="utf-8") as json_file: | |
| config_dict.update(json.load(json_file)) | |
| print(f'Loaded preset: {preset_path}') | |
| else: | |
| raise FileNotFoundError | |
| except Exception as e: | |
| print(f'Load preset [{preset_path}] failed') | |
| print(e) | |
| def get_path_output() -> str: | |
| """ | |
| Checking output path argument and overriding default path. | |
| """ | |
| global config_dict | |
| path_output = get_dir_or_set_default('path_outputs', '../outputs/', make_directory=True) | |
| if args_manager.args.output_path: | |
| print(f'[CONFIG] Overriding config value path_outputs with {args_manager.args.output_path}') | |
| config_dict['path_outputs'] = path_output = args_manager.args.output_path | |
| return path_output | |
| def get_dir_or_set_default(key, default_value, as_array=False, make_directory=False): | |
| global config_dict, visited_keys, always_save_keys | |
| if key not in visited_keys: | |
| visited_keys.append(key) | |
| if key not in always_save_keys: | |
| always_save_keys.append(key) | |
| v = os.getenv(key) | |
| if v is not None: | |
| print(f"Environment: {key} = {v}") | |
| config_dict[key] = v | |
| else: | |
| v = config_dict.get(key, None) | |
| if isinstance(v, str): | |
| if make_directory: | |
| makedirs_with_log(v) | |
| if os.path.exists(v) and os.path.isdir(v): | |
| return v if not as_array else [v] | |
| elif isinstance(v, list): | |
| if make_directory: | |
| for d in v: | |
| makedirs_with_log(d) | |
| if all([os.path.exists(d) and os.path.isdir(d) for d in v]): | |
| return v | |
| if v is not None: | |
| print(f'Failed to load config key: {json.dumps({key:v})} is invalid or does not exist; will use {json.dumps({key:default_value})} instead.') | |
| if isinstance(default_value, list): | |
| dp = [] | |
| for path in default_value: | |
| abs_path = os.path.abspath(os.path.join(os.path.dirname(__file__), path)) | |
| dp.append(abs_path) | |
| os.makedirs(abs_path, exist_ok=True) | |
| else: | |
| dp = os.path.abspath(os.path.join(os.path.dirname(__file__), default_value)) | |
| os.makedirs(dp, exist_ok=True) | |
| if as_array: | |
| dp = [dp] | |
| config_dict[key] = dp | |
| return dp | |
| paths_checkpoints = get_dir_or_set_default('path_checkpoints', ['../models/checkpoints/'], True) | |
| paths_loras = get_dir_or_set_default('path_loras', ['../models/loras/'], True) | |
| path_embeddings = get_dir_or_set_default('path_embeddings', '../models/embeddings/') | |
| path_vae_approx = get_dir_or_set_default('path_vae_approx', '../models/vae_approx/') | |
| path_upscale_models = get_dir_or_set_default('path_upscale_models', '../models/upscale_models/') | |
| path_inpaint = get_dir_or_set_default('path_inpaint', '../models/inpaint/') | |
| path_controlnet = get_dir_or_set_default('path_controlnet', '../models/controlnet/') | |
| path_clip_vision = get_dir_or_set_default('path_clip_vision', '../models/clip_vision/') | |
| path_fooocus_expansion = get_dir_or_set_default('path_fooocus_expansion', '../models/prompt_expansion/fooocus_expansion') | |
| path_outputs = get_path_output() | |
| def get_config_item_or_set_default(key, default_value, validator, disable_empty_as_none=False): | |
| global config_dict, visited_keys | |
| if key not in visited_keys: | |
| visited_keys.append(key) | |
| v = os.getenv(key) | |
| if v is not None: | |
| print(f"Environment: {key} = {v}") | |
| config_dict[key] = v | |
| if key not in config_dict: | |
| config_dict[key] = default_value | |
| return default_value | |
| v = config_dict.get(key, None) | |
| if not disable_empty_as_none: | |
| if v is None or v == '': | |
| v = 'None' | |
| if validator(v): | |
| return v | |
| else: | |
| if v is not None: | |
| print(f'Failed to load config key: {json.dumps({key:v})} is invalid; will use {json.dumps({key:default_value})} instead.') | |
| config_dict[key] = default_value | |
| return default_value | |
| default_base_model_name = get_config_item_or_set_default( | |
| key='default_model', | |
| default_value='model.safetensors', | |
| validator=lambda x: isinstance(x, str) | |
| ) | |
| previous_default_models = get_config_item_or_set_default( | |
| key='previous_default_models', | |
| default_value=[], | |
| validator=lambda x: isinstance(x, list) and all(isinstance(k, str) for k in x) | |
| ) | |
| default_refiner_model_name = get_config_item_or_set_default( | |
| key='default_refiner', | |
| default_value='None', | |
| validator=lambda x: isinstance(x, str) | |
| ) | |
| default_refiner_switch = get_config_item_or_set_default( | |
| key='default_refiner_switch', | |
| default_value=0.8, | |
| validator=lambda x: isinstance(x, numbers.Number) and 0 <= x <= 1 | |
| ) | |
| default_loras_min_weight = get_config_item_or_set_default( | |
| key='default_loras_min_weight', | |
| default_value=-2, | |
| validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10 | |
| ) | |
| default_loras_max_weight = get_config_item_or_set_default( | |
| key='default_loras_max_weight', | |
| default_value=2, | |
| validator=lambda x: isinstance(x, numbers.Number) and -10 <= x <= 10 | |
| ) | |
| default_loras = get_config_item_or_set_default( | |
| key='default_loras', | |
| default_value=[ | |
| [ | |
| "None", | |
| 1.0 | |
| ], | |
| [ | |
| "None", | |
| 1.0 | |
| ], | |
| [ | |
| "None", | |
| 1.0 | |
| ], | |
| [ | |
| "None", | |
| 1.0 | |
| ], | |
| [ | |
| "None", | |
| 1.0 | |
| ] | |
| ], | |
| validator=lambda x: isinstance(x, list) and all(len(y) == 2 and isinstance(y[0], str) and isinstance(y[1], numbers.Number) for y in x) | |
| ) | |
| default_max_lora_number = get_config_item_or_set_default( | |
| key='default_max_lora_number', | |
| default_value=len(default_loras) if isinstance(default_loras, list) and len(default_loras) > 0 else 5, | |
| validator=lambda x: isinstance(x, int) and x >= 1 | |
| ) | |
| default_cfg_scale = get_config_item_or_set_default( | |
| key='default_cfg_scale', | |
| default_value=7.0, | |
| validator=lambda x: isinstance(x, numbers.Number) | |
| ) | |
| default_sample_sharpness = get_config_item_or_set_default( | |
| key='default_sample_sharpness', | |
| default_value=2.0, | |
| validator=lambda x: isinstance(x, numbers.Number) | |
| ) | |
| default_sampler = get_config_item_or_set_default( | |
| key='default_sampler', | |
| default_value='dpmpp_2m_sde_gpu', | |
| validator=lambda x: x in modules.flags.sampler_list | |
| ) | |
| default_scheduler = get_config_item_or_set_default( | |
| key='default_scheduler', | |
| default_value='karras', | |
| validator=lambda x: x in modules.flags.scheduler_list | |
| ) | |
| default_styles = get_config_item_or_set_default( | |
| key='default_styles', | |
| default_value=[ | |
| "Fooocus V2", | |
| "Fooocus Enhance", | |
| "Fooocus Sharp" | |
| ], | |
| validator=lambda x: isinstance(x, list) and all(y in modules.sdxl_styles.legal_style_names for y in x) | |
| ) | |
| default_prompt_negative = get_config_item_or_set_default( | |
| key='default_prompt_negative', | |
| default_value='', | |
| validator=lambda x: isinstance(x, str), | |
| disable_empty_as_none=True | |
| ) | |
| default_prompt = get_config_item_or_set_default( | |
| key='default_prompt', | |
| default_value='', | |
| validator=lambda x: isinstance(x, str), | |
| disable_empty_as_none=True | |
| ) | |
| default_performance = get_config_item_or_set_default( | |
| key='default_performance', | |
| default_value=Performance.SPEED.value, | |
| validator=lambda x: x in Performance.list() | |
| ) | |
| default_advanced_checkbox = get_config_item_or_set_default( | |
| key='default_advanced_checkbox', | |
| default_value=False, | |
| validator=lambda x: isinstance(x, bool) | |
| ) | |
| default_max_image_number = get_config_item_or_set_default( | |
| key='default_max_image_number', | |
| default_value=32, | |
| validator=lambda x: isinstance(x, int) and x >= 1 | |
| ) | |
| default_output_format = get_config_item_or_set_default( | |
| key='default_output_format', | |
| default_value='png', | |
| validator=lambda x: x in modules.flags.output_formats | |
| ) | |
| default_image_number = get_config_item_or_set_default( | |
| key='default_image_number', | |
| default_value=2, | |
| validator=lambda x: isinstance(x, int) and 1 <= x <= default_max_image_number | |
| ) | |
| checkpoint_downloads = get_config_item_or_set_default( | |
| key='checkpoint_downloads', | |
| default_value={}, | |
| validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items()) | |
| ) | |
| lora_downloads = get_config_item_or_set_default( | |
| key='lora_downloads', | |
| default_value={}, | |
| validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items()) | |
| ) | |
| embeddings_downloads = get_config_item_or_set_default( | |
| key='embeddings_downloads', | |
| default_value={}, | |
| validator=lambda x: isinstance(x, dict) and all(isinstance(k, str) and isinstance(v, str) for k, v in x.items()) | |
| ) | |
| available_aspect_ratios = get_config_item_or_set_default( | |
| key='available_aspect_ratios', | |
| default_value=[ | |
| '704*1408', '704*1344', '768*1344', '768*1280', '832*1216', '832*1152', | |
| '896*1152', '896*1088', '960*1088', '960*1024', '1024*1024', '1024*960', | |
| '1088*960', '1088*896', '1152*896', '1152*832', '1216*832', '1280*768', | |
| '1344*768', '1344*704', '1408*704', '1472*704', '1536*640', '1600*640', | |
| '1664*576', '1728*576' | |
| ], | |
| validator=lambda x: isinstance(x, list) and all('*' in v for v in x) and len(x) > 1 | |
| ) | |
| default_aspect_ratio = get_config_item_or_set_default( | |
| key='default_aspect_ratio', | |
| default_value='1152*896' if '1152*896' in available_aspect_ratios else available_aspect_ratios[0], | |
| validator=lambda x: x in available_aspect_ratios | |
| ) | |
| default_inpaint_engine_version = get_config_item_or_set_default( | |
| key='default_inpaint_engine_version', | |
| default_value='v2.6', | |
| validator=lambda x: x in modules.flags.inpaint_engine_versions | |
| ) | |
| default_cfg_tsnr = get_config_item_or_set_default( | |
| key='default_cfg_tsnr', | |
| default_value=7.0, | |
| validator=lambda x: isinstance(x, numbers.Number) | |
| ) | |
| default_overwrite_step = get_config_item_or_set_default( | |
| key='default_overwrite_step', | |
| default_value=-1, | |
| validator=lambda x: isinstance(x, int) | |
| ) | |
| default_overwrite_switch = get_config_item_or_set_default( | |
| key='default_overwrite_switch', | |
| default_value=-1, | |
| validator=lambda x: isinstance(x, int) | |
| ) | |
| example_inpaint_prompts = get_config_item_or_set_default( | |
| key='example_inpaint_prompts', | |
| default_value=[ | |
| 'highly detailed face', 'detailed girl face', 'detailed man face', 'detailed hand', 'beautiful eyes' | |
| ], | |
| validator=lambda x: isinstance(x, list) and all(isinstance(v, str) for v in x) | |
| ) | |
| default_save_metadata_to_images = get_config_item_or_set_default( | |
| key='default_save_metadata_to_images', | |
| default_value=False, | |
| validator=lambda x: isinstance(x, bool) | |
| ) | |
| default_metadata_scheme = get_config_item_or_set_default( | |
| key='default_metadata_scheme', | |
| default_value=MetadataScheme.FOOOCUS.value, | |
| validator=lambda x: x in [y[1] for y in modules.flags.metadata_scheme if y[1] == x] | |
| ) | |
| metadata_created_by = get_config_item_or_set_default( | |
| key='metadata_created_by', | |
| default_value='', | |
| validator=lambda x: isinstance(x, str) | |
| ) | |
| example_inpaint_prompts = [[x] for x in example_inpaint_prompts] | |
| config_dict["default_loras"] = default_loras = default_loras[:default_max_lora_number] + [['None', 1.0] for _ in range(default_max_lora_number - len(default_loras))] | |
| possible_preset_keys = [ | |
| "default_model", | |
| "default_refiner", | |
| "default_refiner_switch", | |
| "default_loras_min_weight", | |
| "default_loras_max_weight", | |
| "default_loras", | |
| "default_max_lora_number", | |
| "default_cfg_scale", | |
| "default_sample_sharpness", | |
| "default_sampler", | |
| "default_scheduler", | |
| "default_performance", | |
| "default_prompt", | |
| "default_prompt_negative", | |
| "default_styles", | |
| "default_aspect_ratio", | |
| "default_save_metadata_to_images", | |
| "checkpoint_downloads", | |
| "embeddings_downloads", | |
| "lora_downloads", | |
| ] | |
| REWRITE_PRESET = False | |
| if REWRITE_PRESET and isinstance(args_manager.args.preset, str): | |
| save_path = 'presets/' + args_manager.args.preset + '.json' | |
| with open(save_path, "w", encoding="utf-8") as json_file: | |
| json.dump({k: config_dict[k] for k in possible_preset_keys}, json_file, indent=4) | |
| print(f'Preset saved to {save_path}. Exiting ...') | |
| exit(0) | |
| def add_ratio(x): | |
| a, b = x.replace('*', ' ').split(' ')[:2] | |
| a, b = int(a), int(b) | |
| g = math.gcd(a, b) | |
| return f'{a}×{b} <span style="color: grey;"> \U00002223 {a // g}:{b // g}</span>' | |
| default_aspect_ratio = add_ratio(default_aspect_ratio) | |
| available_aspect_ratios = [add_ratio(x) for x in available_aspect_ratios] | |
| # Only write config in the first launch. | |
| if not os.path.exists(config_path): | |
| with open(config_path, "w", encoding="utf-8") as json_file: | |
| json.dump({k: config_dict[k] for k in always_save_keys}, json_file, indent=4) | |
| # Always write tutorials. | |
| with open(config_example_path, "w", encoding="utf-8") as json_file: | |
| cpa = config_path.replace("\\", "\\\\") | |
| json_file.write(f'You can modify your "{cpa}" using the below keys, formats, and examples.\n' | |
| f'Do not modify this file. Modifications in this file will not take effect.\n' | |
| f'This file is a tutorial and example. Please edit "{cpa}" to really change any settings.\n' | |
| + 'Remember to split the paths with "\\\\" rather than "\\", ' | |
| 'and there is no "," before the last "}". \n\n\n') | |
| json.dump({k: config_dict[k] for k in visited_keys}, json_file, indent=4) | |
| model_filenames = [] | |
| lora_filenames = [] | |
| sdxl_lcm_lora = 'sdxl_lcm_lora.safetensors' | |
| def get_model_filenames(folder_paths, name_filter=None): | |
| extensions = ['.pth', '.ckpt', '.bin', '.safetensors', '.fooocus.patch'] | |
| files = [] | |
| for folder in folder_paths: | |
| files += get_files_from_folder(folder, extensions, name_filter) | |
| return files | |
| def update_all_model_names(): | |
| global model_filenames, lora_filenames | |
| model_filenames = get_model_filenames(paths_checkpoints) | |
| lora_filenames = get_model_filenames(paths_loras) | |
| return | |
| def downloading_inpaint_models(v): | |
| assert v in modules.flags.inpaint_engine_versions | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/fooocus_inpaint_head.pth', | |
| model_dir=path_inpaint, | |
| file_name='fooocus_inpaint_head.pth' | |
| ) | |
| head_file = os.path.join(path_inpaint, 'fooocus_inpaint_head.pth') | |
| patch_file = None | |
| if v == 'v1': | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/inpaint.fooocus.patch', | |
| model_dir=path_inpaint, | |
| file_name='inpaint.fooocus.patch' | |
| ) | |
| patch_file = os.path.join(path_inpaint, 'inpaint.fooocus.patch') | |
| if v == 'v2.5': | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/inpaint_v25.fooocus.patch', | |
| model_dir=path_inpaint, | |
| file_name='inpaint_v25.fooocus.patch' | |
| ) | |
| patch_file = os.path.join(path_inpaint, 'inpaint_v25.fooocus.patch') | |
| if v == 'v2.6': | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/fooocus_inpaint/resolve/main/inpaint_v26.fooocus.patch', | |
| model_dir=path_inpaint, | |
| file_name='inpaint_v26.fooocus.patch' | |
| ) | |
| patch_file = os.path.join(path_inpaint, 'inpaint_v26.fooocus.patch') | |
| return head_file, patch_file | |
| def downloading_sdxl_lcm_lora(): | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/sdxl_lcm_lora.safetensors', | |
| model_dir=paths_loras[0], | |
| file_name=sdxl_lcm_lora | |
| ) | |
| return sdxl_lcm_lora | |
| def downloading_controlnet_canny(): | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/control-lora-canny-rank128.safetensors', | |
| model_dir=path_controlnet, | |
| file_name='control-lora-canny-rank128.safetensors' | |
| ) | |
| return os.path.join(path_controlnet, 'control-lora-canny-rank128.safetensors') | |
| def downloading_controlnet_cpds(): | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_xl_cpds_128.safetensors', | |
| model_dir=path_controlnet, | |
| file_name='fooocus_xl_cpds_128.safetensors' | |
| ) | |
| return os.path.join(path_controlnet, 'fooocus_xl_cpds_128.safetensors') | |
| def downloading_ip_adapters(v): | |
| assert v in ['ip', 'face'] | |
| results = [] | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/clip_vision_vit_h.safetensors', | |
| model_dir=path_clip_vision, | |
| file_name='clip_vision_vit_h.safetensors' | |
| ) | |
| results += [os.path.join(path_clip_vision, 'clip_vision_vit_h.safetensors')] | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_ip_negative.safetensors', | |
| model_dir=path_controlnet, | |
| file_name='fooocus_ip_negative.safetensors' | |
| ) | |
| results += [os.path.join(path_controlnet, 'fooocus_ip_negative.safetensors')] | |
| if v == 'ip': | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/ip-adapter-plus_sdxl_vit-h.bin', | |
| model_dir=path_controlnet, | |
| file_name='ip-adapter-plus_sdxl_vit-h.bin' | |
| ) | |
| results += [os.path.join(path_controlnet, 'ip-adapter-plus_sdxl_vit-h.bin')] | |
| if v == 'face': | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/ip-adapter-plus-face_sdxl_vit-h.bin', | |
| model_dir=path_controlnet, | |
| file_name='ip-adapter-plus-face_sdxl_vit-h.bin' | |
| ) | |
| results += [os.path.join(path_controlnet, 'ip-adapter-plus-face_sdxl_vit-h.bin')] | |
| return results | |
| def downloading_upscale_model(): | |
| load_file_from_url( | |
| url='https://huggingface.co/lllyasviel/misc/resolve/main/fooocus_upscaler_s409985e5.bin', | |
| model_dir=path_upscale_models, | |
| file_name='fooocus_upscaler_s409985e5.bin' | |
| ) | |
| return os.path.join(path_upscale_models, 'fooocus_upscaler_s409985e5.bin') | |
| update_all_model_names() | |