# Copyright (c) ModelScope Contributors. All rights reserved. import gradio as gr from typing import Type from swift.dataset import get_dataset_list from ..base import BaseUI class Dataset(BaseUI): group = 'llm_train' locale_dict = { 'dataset': { 'label': { 'zh': '数据集名称', 'en': 'Dataset Code' }, 'info': { 'zh': '选择训练的数据集,支持复选/本地路径', 'en': 'The dataset(s) to train the models, support multi select and local folder/files' } }, 'max_length': { 'label': { 'zh': '句子最大长度', 'en': 'The max length', }, 'info': { 'zh': '设置输入模型的最大长度', 'en': 'Set the max length input to the model', } }, 'split_dataset_ratio': { 'label': { 'zh': '验证集拆分比例', 'en': 'Split ratio of eval dataset' }, 'info': { 'zh': '表示将总数据的多少拆分到验证集中', 'en': 'Split the datasets by this ratio for eval' } }, 'padding_free': { 'label': { 'zh': '无填充批处理', 'en': 'Padding-free batching' }, 'info': { 'zh': '将一个batch中的数据进行展平而避免数据padding', 'en': 'Flatten the data in a batch to avoid data padding' } }, 'dataset_param': { 'label': { 'zh': '数据集设置', 'en': 'Dataset settings' }, }, } @classmethod def do_build_ui(cls, base_tab: Type['BaseUI']): with gr.Accordion(elem_id='dataset_param', open=True): with gr.Row(): gr.Dropdown( elem_id='dataset', multiselect=True, choices=get_dataset_list(), scale=20, allow_custom_value=True) gr.Slider(elem_id='split_dataset_ratio', minimum=0.0, maximum=1.0, step=0.05, scale=10) gr.Slider(elem_id='max_length', minimum=32, maximum=32768, value=1024, step=1, scale=10) gr.Checkbox(elem_id='padding_free', scale=10)