From 3bf6dde3a5db5af9ed5a2c616b90c191554bc30a Mon Sep 17 00:00:00 2001 From: hiyouga Date: Sat, 30 Mar 2024 23:09:12 +0800 Subject: [PATCH] support save args in webui #2807 #3046 some ideas are borrowed from @marko1616 Former-commit-id: 7a086ed33388551e0f835adf61fac638f96ed188 --- src/llmtuner/extras/misc.py | 1 + src/llmtuner/webui/common.py | 21 ++++++ src/llmtuner/webui/components/eval.py | 4 +- src/llmtuner/webui/components/train.py | 66 +++++++++++++------ src/llmtuner/webui/engine.py | 5 +- src/llmtuner/webui/interface.py | 18 ++---- src/llmtuner/webui/locales.py | 88 ++++++++++++++++++++++---- src/llmtuner/webui/manager.py | 46 ++++++++------ src/llmtuner/webui/runner.py | 50 +++++++++++---- 9 files changed, 219 insertions(+), 80 deletions(-) diff --git a/src/llmtuner/extras/misc.py b/src/llmtuner/extras/misc.py index 85761f1d..c7b687e9 100644 --- a/src/llmtuner/extras/misc.py +++ b/src/llmtuner/extras/misc.py @@ -66,6 +66,7 @@ def check_dependencies() -> None: require_version("accelerate>=0.27.2", "To fix: pip install accelerate>=0.27.2") require_version("peft>=0.10.0", "To fix: pip install peft>=0.10.0") require_version("trl>=0.8.1", "To fix: pip install trl>=0.8.1") + require_version("gradio>4.0.0,<=4.21.0", "To fix: pip install gradio==4.21.0") def count_parameters(model: torch.nn.Module) -> Tuple[int, int]: diff --git a/src/llmtuner/webui/common.py b/src/llmtuner/webui/common.py index 67e6ff2a..798e6408 100644 --- a/src/llmtuner/webui/common.py +++ b/src/llmtuner/webui/common.py @@ -20,6 +20,7 @@ from ..extras.misc import use_modelscope ADAPTER_NAMES = {WEIGHTS_NAME, SAFETENSORS_WEIGHTS_NAME} DEFAULT_CACHE_DIR = "cache" +DEFAULT_CONFIG_DIR = "config" DEFAULT_DATA_DIR = "data" DEFAULT_SAVE_DIR = "saves" USER_CONFIG = "user.config" @@ -33,6 +34,10 @@ def get_config_path() -> os.PathLike: return os.path.join(DEFAULT_CACHE_DIR, USER_CONFIG) +def get_save_path(config_path: str) -> os.PathLike: + return os.path.join(DEFAULT_CONFIG_DIR, config_path) + + def load_config() -> Dict[str, Any]: try: with open(get_config_path(), "r", encoding="utf-8") as f: @@ -52,6 +57,22 @@ def save_config(lang: str, model_name: Optional[str] = None, model_path: Optiona json.dump(user_config, f, indent=2, ensure_ascii=False) +def load_args(config_path: str) -> Optional[Dict[str, Any]]: + try: + with open(get_save_path(config_path), "r", encoding="utf-8") as f: + return json.load(f) + except Exception: + return None + + +def save_args(config_path: str, config_dict: Dict[str, Any]) -> str: + os.makedirs(DEFAULT_CONFIG_DIR, exist_ok=True) + with open(get_save_path(config_path), "w", encoding="utf-8") as f: + json.dump(config_dict, f, indent=2, ensure_ascii=False) + + return str(get_save_path(config_path)) + + def get_model_path(model_name: str) -> str: user_config = load_config() path_dict: Dict[DownloadSource, str] = SUPPORTED_MODELS.get(model_name, defaultdict(str)) diff --git a/src/llmtuner/webui/components/eval.py b/src/llmtuner/webui/components/eval.py index 452b06fb..4d2fe5c0 100644 --- a/src/llmtuner/webui/components/eval.py +++ b/src/llmtuner/webui/components/eval.py @@ -46,8 +46,8 @@ def create_eval_tab(engine: "Engine") -> Dict[str, "Component"]: with gr.Row(): cmd_preview_btn = gr.Button() - start_btn = gr.Button() - stop_btn = gr.Button() + start_btn = gr.Button(variant="primary") + stop_btn = gr.Button(variant="stop") with gr.Row(): resume_btn = gr.Checkbox(visible=False, interactive=False, value=False) diff --git a/src/llmtuner/webui/components/train.py b/src/llmtuner/webui/components/train.py index c7220b08..52c8fdb6 100644 --- a/src/llmtuner/webui/components/train.py +++ b/src/llmtuner/webui/components/train.py @@ -27,8 +27,6 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: dataset = gr.Dropdown(multiselect=True, scale=4) preview_elems = create_preview_box(dataset_dir, dataset) - dataset_dir.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False) - input_elems.update({training_stage, dataset_dir, dataset}) elem_dict.update(dict(training_stage=training_stage, dataset_dir=dataset_dir, dataset=dataset, **preview_elems)) @@ -127,19 +125,30 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: with gr.Accordion(open=False) as lora_tab: with gr.Row(): - lora_rank = gr.Slider(value=8, minimum=1, maximum=1024, step=1, scale=1) - lora_alpha = gr.Slider(value=16, minimum=1, maximum=2048, step=1, scale=1) - lora_dropout = gr.Slider(value=0.1, minimum=0, maximum=1, step=0.01, scale=1) - lora_target = gr.Textbox(scale=2) + lora_rank = gr.Slider(value=8, minimum=1, maximum=1024, step=1) + lora_alpha = gr.Slider(value=16, minimum=1, maximum=2048, step=1) + lora_dropout = gr.Slider(value=0.1, minimum=0, maximum=1, step=0.01) + loraplus_lr_ratio = gr.Slider(value=0, minimum=0, maximum=64, step=0.01) + create_new_adapter = gr.Checkbox() with gr.Row(): use_rslora = gr.Checkbox(scale=1) use_dora = gr.Checkbox(scale=1) - create_new_adapter = gr.Checkbox(scale=1) + lora_target = gr.Textbox(scale=2) additional_target = gr.Textbox(scale=2) input_elems.update( - {lora_rank, lora_alpha, lora_dropout, lora_target, use_rslora, use_dora, create_new_adapter, additional_target} + { + lora_rank, + lora_alpha, + lora_dropout, + loraplus_lr_ratio, + create_new_adapter, + use_rslora, + use_dora, + lora_target, + additional_target, + } ) elem_dict.update( dict( @@ -147,10 +156,11 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: lora_rank=lora_rank, lora_alpha=lora_alpha, lora_dropout=lora_dropout, - lora_target=lora_target, + loraplus_lr_ratio=loraplus_lr_ratio, + create_new_adapter=create_new_adapter, use_rslora=use_rslora, use_dora=use_dora, - create_new_adapter=create_new_adapter, + lora_target=lora_target, additional_target=additional_target, ) ) @@ -161,13 +171,6 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: dpo_ftx = gr.Slider(value=0, minimum=0, maximum=10, step=0.01, scale=1) reward_model = gr.Dropdown(multiselect=True, allow_custom_value=True, scale=2) - training_stage.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False).then( - list_adapters, - [engine.manager.get_elem_by_id("top.model_name"), engine.manager.get_elem_by_id("top.finetuning_type")], - [reward_model], - queue=False, - ).then(autoset_packing, [training_stage], [packing], queue=False) - input_elems.update({dpo_beta, dpo_ftx, reward_model}) elem_dict.update(dict(rlhf_tab=rlhf_tab, dpo_beta=dpo_beta, dpo_ftx=dpo_ftx, reward_model=reward_model)) @@ -177,7 +180,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: galore_rank = gr.Slider(value=16, minimum=1, maximum=1024, step=1, scale=2) galore_update_interval = gr.Slider(value=200, minimum=1, maximum=1024, step=1, scale=2) galore_scale = gr.Slider(value=0.25, minimum=0, maximum=1, step=0.01, scale=2) - galore_target = gr.Textbox(value="mlp,attn", scale=3) + galore_target = gr.Textbox(value="all", scale=3) input_elems.update({use_galore, galore_rank, galore_update_interval, galore_scale, galore_target}) elem_dict.update( @@ -193,13 +196,16 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: with gr.Row(): cmd_preview_btn = gr.Button() - start_btn = gr.Button() - stop_btn = gr.Button() + arg_save_btn = gr.Button() + arg_load_btn = gr.Button() + start_btn = gr.Button(variant="primary") + stop_btn = gr.Button(variant="stop") with gr.Row(): with gr.Column(scale=3): with gr.Row(): output_dir = gr.Textbox() + config_path = gr.Textbox() with gr.Row(): resume_btn = gr.Checkbox(visible=False, interactive=False) @@ -211,20 +217,38 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: with gr.Column(scale=1): loss_viewer = gr.Plot() - input_elems.add(output_dir) + input_elems.update({output_dir, config_path}) output_elems = [output_box, process_bar] cmd_preview_btn.click(engine.runner.preview_train, input_elems, output_elems, concurrency_limit=None) + arg_save_btn.click(engine.runner.save_args, input_elems, output_elems, concurrency_limit=None) + arg_load_btn.click( + engine.runner.load_args, + [engine.manager.get_elem_by_id("top.lang"), config_path], + list(input_elems), + concurrency_limit=None, + ) start_btn.click(engine.runner.run_train, input_elems, output_elems) stop_btn.click(engine.runner.set_abort, queue=False) resume_btn.change(engine.runner.monitor, outputs=output_elems, concurrency_limit=None) + dataset_dir.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False) + training_stage.change(list_dataset, [dataset_dir, training_stage], [dataset], queue=False).then( + list_adapters, + [engine.manager.get_elem_by_id("top.model_name"), engine.manager.get_elem_by_id("top.finetuning_type")], + [reward_model], + queue=False, + ).then(autoset_packing, [training_stage], [packing], queue=False) + elem_dict.update( dict( cmd_preview_btn=cmd_preview_btn, + arg_save_btn=arg_save_btn, + arg_load_btn=arg_load_btn, start_btn=start_btn, stop_btn=stop_btn, output_dir=output_dir, + config_path=config_path, resume_btn=resume_btn, process_bar=process_bar, output_box=output_box, diff --git a/src/llmtuner/webui/engine.py b/src/llmtuner/webui/engine.py index 7f76f799..0ee7f047 100644 --- a/src/llmtuner/webui/engine.py +++ b/src/llmtuner/webui/engine.py @@ -38,8 +38,9 @@ class Engine: if not self.pure_chat: init_dict["train.dataset"] = {"choices": list_dataset().choices} init_dict["eval.dataset"] = {"choices": list_dataset().choices} - init_dict["train.output_dir"] = {"value": "train_" + get_time()} - init_dict["eval.output_dir"] = {"value": "eval_" + get_time()} + init_dict["train.output_dir"] = {"value": "train_{}".format(get_time())} + init_dict["train.config_path"] = {"value": "{}.json".format(get_time())} + init_dict["eval.output_dir"] = {"value": "eval_{}".format(get_time())} if user_config.get("last_model", None): init_dict["top.model_name"] = {"value": user_config["last_model"]} diff --git a/src/llmtuner/webui/interface.py b/src/llmtuner/webui/interface.py index d943594d..f89d3ca5 100644 --- a/src/llmtuner/webui/interface.py +++ b/src/llmtuner/webui/interface.py @@ -1,5 +1,4 @@ import gradio as gr -from transformers.utils.versions import require_version from .common import save_config from .components import ( @@ -14,9 +13,6 @@ from .css import CSS from .engine import Engine -require_version("gradio>4.0.0,<=4.21.0", "To fix: pip install gradio==4.21.0") - - def create_ui(demo_mode: bool = False) -> gr.Blocks: engine = Engine(demo_mode=demo_mode, pure_chat=False) @@ -29,21 +25,21 @@ def create_ui(demo_mode: bool = False) -> gr.Blocks: ) gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button") - engine.manager.add_elem_dict("top", create_top()) + engine.manager.add_elems("top", create_top()) lang: "gr.Dropdown" = engine.manager.get_elem_by_id("top.lang") with gr.Tab("Train"): - engine.manager.add_elem_dict("train", create_train_tab(engine)) + engine.manager.add_elems("train", create_train_tab(engine)) with gr.Tab("Evaluate & Predict"): - engine.manager.add_elem_dict("eval", create_eval_tab(engine)) + engine.manager.add_elems("eval", create_eval_tab(engine)) with gr.Tab("Chat"): - engine.manager.add_elem_dict("infer", create_infer_tab(engine)) + engine.manager.add_elems("infer", create_infer_tab(engine)) if not demo_mode: with gr.Tab("Export"): - engine.manager.add_elem_dict("export", create_export_tab(engine)) + engine.manager.add_elems("export", create_export_tab(engine)) demo.load(engine.resume, outputs=engine.manager.get_elem_list(), concurrency_limit=None) lang.change(engine.change_lang, [lang], engine.manager.get_elem_list(), queue=False) @@ -57,10 +53,10 @@ def create_web_demo() -> gr.Blocks: with gr.Blocks(title="Web Demo", css=CSS) as demo: lang = gr.Dropdown(choices=["en", "zh"]) - engine.manager.add_elem_dict("top", dict(lang=lang)) + engine.manager.add_elems("top", dict(lang=lang)) chat_box, _, _, chat_elems = create_chat_box(engine, visible=True) - engine.manager.add_elem_dict("infer", dict(chat_box=chat_box, **chat_elems)) + engine.manager.add_elems("infer", dict(chat_box=chat_box, **chat_elems)) demo.load(engine.resume, outputs=engine.manager.get_elem_list(), concurrency_limit=None) lang.change(engine.change_lang, [lang], engine.manager.get_elem_list(), queue=False) diff --git a/src/llmtuner/webui/locales.py b/src/llmtuner/webui/locales.py index 4f329e8e..f6d6d421 100644 --- a/src/llmtuner/webui/locales.py +++ b/src/llmtuner/webui/locales.py @@ -628,18 +628,32 @@ LOCALES = { "info": "LoRA 权重随机丢弃的概率。", }, }, - "lora_target": { + "loraplus_lr_ratio": { "en": { - "label": "LoRA modules (optional)", - "info": "Name(s) of modules to apply LoRA. Use commas to separate multiple modules.", + "label": "LoRA+ LR ratio", + "info": "The LR ratio of the B matrices in LoRA.", }, "ru": { - "label": "Модули LoRA (опционально)", - "info": "Имена модулей для применения LoRA. Используйте запятые для разделения нескольких модулей.", + "label": "LoRA+ LR коэффициент", + "info": "Коэффициент LR матриц B в LoRA.", }, "zh": { - "label": "LoRA 作用模块（非必填）", - "info": "应用 LoRA 的模块名称。使用英文逗号分隔多个名称。", + "label": "LoRA+ 学习率比例", + "info": "LoRA+ 中 B 矩阵的学习率倍数。", + }, + }, + "create_new_adapter": { + "en": { + "label": "Create new adapter", + "info": "Create a new adapter with randomly initialized weight upon the existing one.", + }, + "ru": { + "label": "Создать новый адаптер", + "info": "Создать новый адаптер с случайной инициализацией веса на основе существующего.", + }, + "zh": { + "label": "新建适配器", + "info": "在现有的适配器上创建一个随机初始化后的新适配器。", }, }, "use_rslora": { @@ -670,18 +684,18 @@ LOCALES = { "info": "使用权重分解的 LoRA。", }, }, - "create_new_adapter": { + "lora_target": { "en": { - "label": "Create new adapter", - "info": "Create a new adapter with randomly initialized weight upon the existing one.", + "label": "LoRA modules (optional)", + "info": "Name(s) of modules to apply LoRA. Use commas to separate multiple modules.", }, "ru": { - "label": "Создать новый адаптер", - "info": "Создать новый адаптер с случайной инициализацией веса на основе существующего.", + "label": "Модули LoRA (опционально)", + "info": "Имена модулей для применения LoRA. Используйте запятые для разделения нескольких модулей.", }, "zh": { - "label": "新建适配器", - "info": "在现有的适配器上创建一个随机初始化后的新适配器。", + "label": "LoRA 作用模块（非必填）", + "info": "应用 LoRA 的模块名称。使用英文逗号分隔多个名称。", }, }, "additional_target": { @@ -849,6 +863,28 @@ LOCALES = { "value": "预览命令", }, }, + "arg_save_btn": { + "en": { + "value": "Save arguments", + }, + "ru": { + "value": "Сохранить аргументы", + }, + "zh": { + "value": "保存训练参数", + }, + }, + "arg_load_btn": { + "en": { + "value": "Load arguments", + }, + "ru": { + "value": "Загрузить аргументы", + }, + "zh": { + "value": "载入训练参数", + }, + }, "start_btn": { "en": { "value": "Start", @@ -885,6 +921,20 @@ LOCALES = { "info": "保存结果的路径。", }, }, + "config_path": { + "en": { + "label": "Config path", + "info": "Path to config saving arguments.", + }, + "ru": { + "label": "Путь к конфигурации", + "info": "Путь для сохранения аргументов конфигурации.", + }, + "zh": { + "label": "配置路径", + "info": "保存训练参数的配置文件路径。", + }, + }, "output_box": { "en": { "value": "Ready.", @@ -1236,6 +1286,11 @@ ALERTS = { "ru": "Неверная схема JSON.", "zh": "Json 格式错误。", }, + "err_config_not_found": { + "en": "Config file is not found.", + "ru": "Файл конфигурации не найден.", + "zh": "未找到配置文件。", + }, "warn_no_cuda": { "en": "CUDA environment was not detected.", "ru": "Среда CUDA не обнаружена.", @@ -1256,6 +1311,11 @@ ALERTS = { "ru": "Завершено.", "zh": "训练完毕。", }, + "info_config_saved": { + "en": "Arguments have been saved at: ", + "ru": "Аргументы были сохранены по адресу: ", + "zh": "训练参数已保存至：", + }, "info_loading": { "en": "Loading model...", "ru": "Загрузка модели...", diff --git a/src/llmtuner/webui/manager.py b/src/llmtuner/webui/manager.py index 266a1f3a..a67c0995 100644 --- a/src/llmtuner/webui/manager.py +++ b/src/llmtuner/webui/manager.py @@ -7,27 +7,30 @@ if TYPE_CHECKING: class Manager: def __init__(self) -> None: - self._elem_dicts: Dict[str, Dict[str, "Component"]] = {} + self._id_to_elem: Dict[str, "Component"] = {} + self._elem_to_id: Dict["Component", str] = {} - def add_elem_dict(self, tab_name: str, elem_dict: Dict[str, "Component"]) -> None: + def add_elems(self, tab_name: str, elem_dict: Dict[str, "Component"]) -> None: r""" - Adds a elem dict. + Adds elements to manager. """ - self._elem_dicts[tab_name] = elem_dict + for elem_name, elem in elem_dict.items(): + elem_id = "{}.{}".format(tab_name, elem_name) + self._id_to_elem[elem_id] = elem + self._elem_to_id[elem] = elem_id def get_elem_list(self) -> List["Component"]: r""" Returns the list of all elements. """ - return [elem for elem_dict in self._elem_dicts.values() for elem in elem_dict.values()] + return list(self._id_to_elem.values()) def get_elem_iter(self) -> Generator[Tuple[str, "Component"], None, None]: r""" Returns an iterator over all elements with their names. """ - for elem_dict in self._elem_dicts.values(): - for elem_name, elem in elem_dict.items(): - yield elem_name, elem + for elem_id, elem in self._id_to_elem.items(): + yield elem_id.split(".")[-1], elem def get_elem_by_id(self, elem_id: str) -> "Component": r""" @@ -35,21 +38,26 @@ class Manager: Example: top.lang, train.dataset """ - tab_name, elem_name = elem_id.split(".") - return self._elem_dicts[tab_name][elem_name] + return self._id_to_elem[elem_id] + + def get_id_by_elem(self, elem: "Component") -> str: + r""" + Gets id by element. + """ + return self._elem_to_id[elem] def get_base_elems(self) -> Set["Component"]: r""" Gets the base elements that are commonly used. """ return { - self._elem_dicts["top"]["lang"], - self._elem_dicts["top"]["model_name"], - self._elem_dicts["top"]["model_path"], - self._elem_dicts["top"]["finetuning_type"], - self._elem_dicts["top"]["adapter_path"], - self._elem_dicts["top"]["quantization_bit"], - self._elem_dicts["top"]["template"], - self._elem_dicts["top"]["rope_scaling"], - self._elem_dicts["top"]["booster"], + self._id_to_elem["top.lang"], + self._id_to_elem["top.model_name"], + self._id_to_elem["top.model_path"], + self._id_to_elem["top.finetuning_type"], + self._id_to_elem["top.adapter_path"], + self._id_to_elem["top.quantization_bit"], + self._id_to_elem["top.template"], + self._id_to_elem["top.rope_scaling"], + self._id_to_elem["top.booster"], } diff --git a/src/llmtuner/webui/runner.py b/src/llmtuner/webui/runner.py index 753225af..ab646051 100644 --- a/src/llmtuner/webui/runner.py +++ b/src/llmtuner/webui/runner.py @@ -15,7 +15,7 @@ from ..extras.constants import TRAINING_STAGES from ..extras.logging import LoggerHandler from ..extras.misc import get_device_count, torch_gc from ..train import run_exp -from .common import get_module, get_save_dir, load_config +from .common import get_module, get_save_dir, load_args, load_config, save_args from .locales import ALERTS from .utils import gen_cmd, get_eval_results, update_process_bar @@ -150,23 +150,21 @@ class Runner: args["disable_tqdm"] = True if args["finetuning_type"] == "freeze": - args["num_layer_trainable"] = int(get("train.num_layer_trainable")) + args["num_layer_trainable"] = get("train.num_layer_trainable") args["name_module_trainable"] = get("train.name_module_trainable") elif args["finetuning_type"] == "lora": - args["lora_rank"] = int(get("train.lora_rank")) - args["lora_alpha"] = int(get("train.lora_alpha")) - args["lora_dropout"] = float(get("train.lora_dropout")) - args["lora_target"] = get("train.lora_target") or get_module(get("top.model_name")) + args["lora_rank"] = get("train.lora_rank") + args["lora_alpha"] = get("train.lora_alpha") + args["lora_dropout"] = get("train.lora_dropout") + args["loraplus_lr_ratio"] = get("train.loraplus_lr_ratio") or None + args["create_new_adapter"] = get("train.create_new_adapter") args["use_rslora"] = get("train.use_rslora") args["use_dora"] = get("train.use_dora") + args["lora_target"] = get("train.lora_target") or get_module(get("top.model_name")) args["additional_target"] = get("train.additional_target") or None - if args["stage"] in ["rm", "ppo", "dpo"]: - args["create_new_adapter"] = args["quantization_bit"] is None - else: - args["create_new_adapter"] = get("train.create_new_adapter") if args["use_llama_pro"]: - args["num_layer_trainable"] = int(get("train.num_layer_trainable")) + args["num_layer_trainable"] = get("train.num_layer_trainable") if args["stage"] == "ppo": args["reward_model"] = ",".join( @@ -305,3 +303,33 @@ class Runner: finish_info = ALERTS["err_failed"][lang] yield self._finalize(lang, finish_info), gr.Slider(visible=False) + + def save_args(self, data: Dict[Component, Any]) -> Tuple[str, "gr.Slider"]: + error = self._initialize(data, do_train=True, from_preview=True) + if error: + gr.Warning(error) + return error, gr.Slider(visible=False) + + config_dict: Dict[str, Any] = {} + lang = data[self.manager.get_elem_by_id("top.lang")] + config_path = data[self.manager.get_elem_by_id("train.config_path")] + skip_ids = ["top.lang", "top.model_path", "train.output_dir", "train.config_path"] + for elem, value in data.items(): + elem_id = self.manager.get_id_by_elem(elem) + if elem_id not in skip_ids: + config_dict[elem_id] = value + + save_path = save_args(config_path, config_dict) + return ALERTS["info_config_saved"][lang] + save_path, gr.Slider(visible=False) + + def load_args(self, lang: str, config_path: str) -> Dict[Component, Any]: + config_dict = load_args(config_path) + if config_dict is None: + gr.Warning(ALERTS["err_config_not_found"][lang]) + return {self.manager.get_elem_by_id("top.lang"): lang} + + output_dict: Dict["Component", Any] = {} + for elem_id, value in config_dict.items(): + output_dict[self.manager.get_elem_by_id(elem_id)] = value + + return output_dict