# Copyright (c) Alibaba, Inc. and its affiliates. from functools import partial from typing import Type import gradio as gr from swift.llm import ModelType from swift.llm.model.register import get_all_models from swift.ui.base import BaseUI class RLHF(BaseUI): group = 'llm_train' locale_dict = { 'rlhf_tab': { 'label': { 'zh': '人类对齐参数设置', 'en': 'RLHF settings' }, }, 'rlhf_type': { 'label': { 'zh': '人类对齐算法类型', 'en': 'RLHF type' }, }, 'ref_model_type': { 'label': { 'zh': '选择ref模型', 'en': 'Select ref model' }, 'info': { 'zh': 'SWIFT已支持的模型名称', 'en': 'Base model supported by SWIFT' } }, 'ref_model': { 'label': { 'zh': 'ref模型id或路径', 'en': 'Ref model id or path' }, 'info': { 'zh': '实际的模型id或路径', 'en': 'The actual model id or path' } }, 'beta': { 'label': { 'zh': 'KL正则项系数', 'en': 'KL regression ratio' }, }, 'rpo_alpha': { 'label': { 'zh': 'DPO中混合sft交叉熵的系数', 'en': 'DPO Cross Entropy ratio' }, }, 'simpo_gamma': { 'label': { 'zh': 'SimPO reward margin', 'en': 'SimPO reward margin' }, }, 'desirable_weight': { 'label': { 'zh': 'KTO符合项系数', 'en': 'KTO desirable ratio' }, }, 'undesirable_weight': { 'label': { 'zh': 'KTO不符合项系数', 'en': 'KTO undesirable ratio' }, } } @classmethod def do_build_ui(cls, base_tab: Type['BaseUI']): with gr.Accordion(elem_id='rlhf_tab', open=False): with gr.Blocks(): with gr.Row(): gr.Dropdown(elem_id='rlhf_type', value=None) gr.Dropdown( elem_id='ref_model', scale=20, value=None, choices=get_all_models(), allow_custom_value=True) gr.Dropdown(elem_id='ref_model_type', choices=ModelType.get_model_name_list(), value=None, scale=20) with gr.Row(): gr.Slider(elem_id='beta', minimum=0., maximum=5.0, step=0.1, scale=20) gr.Slider(elem_id='rpo_alpha', minimum=0., maximum=2, step=0.1, scale=20) gr.Slider(elem_id='simpo_gamma', minimum=0., maximum=2.0, step=0.1, scale=20) gr.Slider(elem_id='desirable_weight', minimum=0., maximum=2.0, step=0.1, scale=20) gr.Slider(elem_id='undesirable_weight', minimum=0., maximum=2.0, step=0.1, scale=20) @classmethod def after_build_ui(cls, base_tab: Type['BaseUI']): cls.element('ref_model').change( partial(cls.update_input_model, allow_keys=['ref_model_type'], has_record=False, is_ref_model=True), inputs=[cls.element('ref_model')], outputs=[cls.element('ref_model_type')])