569 lines
26 KiB
Python
569 lines
26 KiB
Python
# -*- coding: utf-8 -*-
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# Copyright (c) Alibaba, Inc. and its affiliates.
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import copy
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import json
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import os
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import queue
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import time
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import gradio as gr
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import yaml
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from scepter.modules.utils.config import Config
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from scepter.modules.utils.file_system import FS
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from scepter.studio.self_train.self_train_ui.component_names import ModelUIName
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from scepter.studio.self_train.utils.config_parser import get_base_model_list
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from scepter.studio.utils.uibase import UIBase
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refresh_symbol = '\U0001f504' # 🔄
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delete_symbol = '\U0001f5d1' # 🗑️
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stop_symbol = '\U000025A0'
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add_symbol = '\U00002795' # ➕
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confirm_symbol = '\U00002714' # ✔️
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class ModelUI(UIBase):
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def __init__(self, cfg, all_cfg_value, is_debug=False, language='en'):
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self.BASE_CFG_VALUE = all_cfg_value
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self.language = language
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self.base_model_info = get_base_model_list(self.BASE_CFG_VALUE)
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self.work_dir, _ = FS.map_to_local(cfg.WORK_DIR)
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os.makedirs(self.work_dir, exist_ok=True)
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self.default_model_name = 'step-last'
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self.old_default_model_name = 'checkpoint.pth'
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self.delete_folder_queue = queue.Queue()
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self.user_level_model_list = {}
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if not self.work_dir.endswith('/'):
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self.work_dir += '/'
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self.load_history()
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self.is_debug = is_debug
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self.component_names = ModelUIName(language)
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def load_history(self, user_name='admin'):
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have_model_list = []
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for one_dir in FS.walk_dir(self.work_dir):
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if one_dir.startswith(self.work_dir):
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one_dir = one_dir[len(self.work_dir):]
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if not os.path.isdir(os.path.join(self.work_dir, one_dir)):
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continue
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params_file = os.path.join(self.work_dir, one_dir, 'params.json')
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if FS.exists(params_file):
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try:
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params = json.load(open(params_file, 'r'))
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except:
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continue
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model_user_name = params.get('user_name', 'example')
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if model_user_name == user_name or model_user_name in [
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'example'
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] or user_name == 'admin':
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# parse params
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status_file = os.path.join(self.work_dir, one_dir,
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'status.json')
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if FS.exists(status_file):
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try:
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status = json.load(open(status_file, 'r'))
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except:
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continue
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status['model_name'] = one_dir
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have_model_list.append(status)
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have_model_list.sort(key=lambda x: x['start_time'])
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self.user_level_model_list[user_name] = [
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v['model_name'] for v in have_model_list
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]
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def get_ckpt_list(self, output_model):
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all_ckpt_list = []
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if output_model is None or output_model == '':
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return all_ckpt_list
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output_model_path = os.path.join(self.work_dir, output_model)
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all_ckpt_path = os.path.join(output_model_path, 'checkpoints')
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if os.path.exists(all_ckpt_path):
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for name in os.listdir(all_ckpt_path):
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if name == self.default_model_name:
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continue
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path = os.path.join(all_ckpt_path, name)
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if os.path.isdir(path):
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all_ckpt_list.append(name)
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all_ckpt_list = sorted(all_ckpt_list,
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key=lambda x: int(x.split('-')[-1]))
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if os.path.exists(os.path.join(all_ckpt_path,
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self.default_model_name)):
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all_ckpt_list.append(self.default_model_name)
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return all_ckpt_list
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def get_gallery_list(self, model_name, ckpt_name):
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ckpt_probe_dir = os.path.join(self.work_dir, model_name, 'eval_probe',
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ckpt_name, 'image')
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all_gallery_list = []
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if os.path.exists(ckpt_probe_dir):
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for name in os.listdir(ckpt_probe_dir):
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path = os.path.join(ckpt_probe_dir, name)
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all_gallery_list.append(path)
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return all_gallery_list
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def create_ui(self, *args, **kwargs):
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with gr.Group():
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gr.Markdown(self.component_names.output_model_block)
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with gr.Row(variant='panel', equal_height=True):
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with gr.Column(scale=7, min_width=0):
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self.output_model_name = gr.Dropdown(
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label=self.component_names.output_model_name,
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choices=self.user_level_model_list.get('admin', []),
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value=None,
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show_label=False,
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container=False,
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interactive=True)
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with gr.Column(scale=2, min_width=0):
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self.output_ckpt_name = gr.Dropdown(
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label=self.component_names.output_ckpt_name,
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value=None,
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choices=[],
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show_label=False,
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container=False,
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interactive=True)
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with gr.Column(scale=1, min_width=0):
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self.refresh_model_gbtn = gr.Button(value=refresh_symbol)
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with gr.Column(scale=1, min_width=0):
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self.add_model_gbtn = gr.Button(value=add_symbol)
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with gr.Column(scale=1, min_width=0):
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self.stop_model_gbtn = gr.Button(value=stop_symbol)
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with gr.Column(scale=1, min_width=0):
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self.delete_model_gbtn = gr.Button(value=delete_symbol)
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with gr.Row(variant='panel', equal_height=True,
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visible=False) as self.extra_model_panel:
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with gr.Column(scale=4, min_width=0):
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self.extra_model_txt = gr.Text(
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label=self.component_names.extra_model_gtxt,
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show_label=False,
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container=False,
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placeholder='Add Extra Model')
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with gr.Column(scale=1, min_width=0):
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self.confirm_add = gr.Button(value=confirm_symbol)
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with gr.Row(variant='panel', equal_height=True):
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with gr.Column(scale=3, min_width=0):
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with gr.Group():
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self.log_message = gr.Text(
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placeholder='Please select model'
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'or press export button.',
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autoscroll=True,
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lines=10,
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label=self.component_names.log_block)
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with gr.Column(scale=1, min_width=0,
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visible=False) as self.export_log_panel:
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# with gr.Column(scale=1, min_width=0):
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self.export_log = gr.Button(
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value=self.component_names.btn_export_log)
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# with gr.Column(scale=1, min_width=0):
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self.export_url = gr.File(
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label=self.component_names.export_file,
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visible=False,
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value=None,
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interactive=False,
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show_label=True)
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with gr.Row(variant='panel', equal_height=True):
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with gr.Accordion(label=self.component_names.gallery_block,
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open=True):
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self.eval_gallery = gr.Gallery(
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label=self.component_names.eval_gallery,
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value=[],
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preview=True,
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selected_index=None)
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with gr.Row():
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with gr.Column(scale=1, min_width=0):
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self.go_to_inferece_btn = gr.Button(
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self.component_names.go_to_inference)
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def set_callbacks(self, trainer_ui, manager):
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self.manager = manager
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def model_name_change(model_name):
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if model_name is None:
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return '', gr.Column(), None, []
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message = trainer_ui.trainer_ins.get_log(model_name)
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status = trainer_ui.trainer_ins.get_status(model_name)
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ckpt_list = self.get_ckpt_list(model_name)
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ckpt_value = ckpt_list[-1] if len(ckpt_list) > 0 else None
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ckpt_list = ckpt_list if isinstance(ckpt_list, list) and len(ckpt_list) > 0 else None
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if ckpt_value is not None and len(ckpt_value) > 0:
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gallery_value = self.get_gallery_list(model_name, ckpt_value)
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else:
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gallery_value = []
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select_index = 0 if len(gallery_value) > 0 else None
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return (message, gr.Column(visible=status in ('running',
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'success')),
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gr.Dropdown(choices=ckpt_list, value=ckpt_value),
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gr.Gallery(value=gallery_value,
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preview=True,
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selected_index=select_index))
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self.output_model_name.change(fn=model_name_change,
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inputs=[self.output_model_name],
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outputs=[
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self.log_message,
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self.export_log_panel,
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self.output_ckpt_name,
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self.eval_gallery
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],
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queue=False)
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def ckpt_name_change(model_name, ckpt_value):
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if ckpt_value is not None and len(ckpt_value) > 0:
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gallery_value = self.get_gallery_list(model_name, ckpt_value)
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else:
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gallery_value = []
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if len(gallery_value) > 0:
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return gr.Gallery(value=gallery_value,
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preview=True,
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selected_index=0)
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else:
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return gr.Gallery(value=gallery_value,
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preview=True,
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selected_index=None)
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self.output_ckpt_name.change(
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fn=ckpt_name_change,
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inputs=[self.output_model_name, self.output_ckpt_name],
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outputs=[self.eval_gallery],
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queue=False)
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def add_model():
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return gr.Row(visible=True)
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self.add_model_gbtn.click(fn=add_model,
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inputs=[],
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outputs=[self.extra_model_panel],
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queue=False)
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def confirm_add(model_name, login_user_name):
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model_folder = os.path.join(self.work_dir, model_name)
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have_model = os.path.exists(model_folder)
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if not have_model:
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gr.Error(self.component_names.model_err5.format(model_name))
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self.load_history(login_user_name)
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if model_name not in self.user_level_model_list[
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login_user_name] and have_model:
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self.user_level_model_list[login_user_name].append(model_name)
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return gr.Row(visible=False), gr.Dropdown(
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choices=self.user_level_model_list[login_user_name],
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value=model_name)
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self.confirm_add.click(
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fn=confirm_add,
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inputs=[self.extra_model_txt, manager.user_name],
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outputs=[self.extra_model_panel, self.output_model_name],
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queue=False)
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def refresh_model(model_name, login_user_name):
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if not self.delete_folder_queue.empty():
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try:
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del_folder = self.delete_folder_queue.get_nowait()
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if os.path.exists(del_folder):
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os.system(f'rm -rf {del_folder}')
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self.delete_folder_queue.put_nowait(del_folder)
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except Exception:
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pass
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message = trainer_ui.trainer_ins.get_log(model_name)
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status = trainer_ui.trainer_ins.get_status(model_name)
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ckpt_list = self.get_ckpt_list(model_name)
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ckpt_value = ckpt_list[-1] if len(ckpt_list) > 0 else None
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ckpt_list = ckpt_list if isinstance(ckpt_list, list) and len(ckpt_list) > 0 else None
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ret_gallery = ckpt_name_change(model_name, ckpt_value)
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model_list = self.user_level_model_list.get(login_user_name, [])
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self.load_history(login_user_name)
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return (message, gr.Column(visible=status in ('running',
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'success')),
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gr.Dropdown(choices=model_list,
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value=model_name),
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gr.Dropdown(choices=ckpt_list,
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value=ckpt_value), ret_gallery)
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self.refresh_model_gbtn.click(
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fn=refresh_model,
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inputs=[self.output_model_name, manager.user_name],
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outputs=[
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self.log_message, self.export_log_panel,
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self.output_model_name, self.output_ckpt_name,
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self.eval_gallery
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],
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queue=False)
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def delete_model(model_name, login_user_name):
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index = 0
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trainer_ui.trainer_ins.stop_task(model_name)
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self.load_history(login_user_name)
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model_list = self.user_level_model_list.get(login_user_name, [])
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if model_name in model_list:
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index = model_list.index(model_name)
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model_list.remove(model_name)
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folder = os.path.join(self.work_dir, model_name)
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for _ in range(1):
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if os.path.exists(folder):
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try:
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os.system(f'rm -rf {folder}')
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except Exception:
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time.sleep(2)
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else:
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break
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self.delete_folder_queue.put_nowait(folder)
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if index <= len(model_list) - 1:
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model_name = model_list[index]
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elif len(model_list) > 0:
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model_name = model_list[-1]
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else:
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model_name = None
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self.user_level_model_list[login_user_name] = model_list
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return gr.Dropdown(choices=model_list, value=model_name)
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self.delete_model_gbtn.click(
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fn=delete_model,
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inputs=[self.output_model_name, manager.user_name],
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outputs=[self.output_model_name])
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||
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def stop_model(model_name, login_user_name):
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trainer_ui.trainer_ins.stop_task(model_name)
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if not self.delete_folder_queue.empty():
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||
try:
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del_folder = self.delete_folder_queue.get_nowait()
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if os.path.exists(del_folder):
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os.system(f'rm -rf {del_folder}')
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self.delete_folder_queue.put_nowait(del_folder)
|
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except Exception:
|
||
pass
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message = trainer_ui.trainer_ins.get_log(model_name)
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status = trainer_ui.trainer_ins.get_status(model_name)
|
||
ckpt_list = self.get_ckpt_list(model_name)
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||
ckpt_value = ckpt_list[-1] if len(ckpt_list) > 0 else None
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ckpt_list = ckpt_list if isinstance(ckpt_list, list) and len(ckpt_list) > 0 else None
|
||
ret_gallery = ckpt_name_change(model_name, ckpt_value)
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self.load_history(login_user_name)
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return (message, gr.Column(visible=status in ('running',
|
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'success')),
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gr.Dropdown(choices=self.user_level_model_list.get(
|
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login_user_name, []),
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value=model_name),
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||
gr.Dropdown(choices=ckpt_list,
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value=ckpt_value), ret_gallery)
|
||
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||
self.stop_model_gbtn.click(
|
||
fn=stop_model,
|
||
inputs=[self.output_model_name, manager.user_name],
|
||
outputs=[
|
||
self.log_message, self.export_log_panel,
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self.output_model_name, self.output_ckpt_name,
|
||
self.eval_gallery
|
||
])
|
||
|
||
def go_to_inferece(output_model, output_ckpt_name):
|
||
if output_ckpt_name is None or output_ckpt_name.strip() == '':
|
||
raise gr.Error(message="The model file doesn't exist.")
|
||
params_path = os.path.join(self.work_dir, output_model,
|
||
'params.json')
|
||
if os.path.exists(params_path):
|
||
params_info = json.loads(open(params_path).read())
|
||
assert params_info['work_name'] == output_model
|
||
base_model = params_info['base_model']
|
||
base_model_revision = params_info['base_model_revision']
|
||
tuner_name = params_info['tuner_name']
|
||
model_path = os.path.join(self.work_dir, output_model,
|
||
'checkpoints', output_ckpt_name)
|
||
eval_prompts = params_info[
|
||
'eval_prompts'] if 'eval_prompts' in params_info else []
|
||
image_dir = os.path.join(self.work_dir, output_model,
|
||
'eval_probe', output_ckpt_name,
|
||
'image')
|
||
if os.path.exists(image_dir):
|
||
image_path = [
|
||
os.path.join(image_dir, name)
|
||
for name in os.listdir(image_dir)
|
||
]
|
||
else:
|
||
image_path = []
|
||
else:
|
||
_, base_model, base_model_revision, tuner_name, _ = output_model.split(
|
||
'@', 4)
|
||
model_path = os.path.join(self.work_dir, output_model,
|
||
self.old_default_model_name)
|
||
output_ckpt_name = self.old_default_model_name
|
||
image_path = []
|
||
eval_prompts = []
|
||
params_info = {}
|
||
|
||
if isinstance(image_path, list):
|
||
image_path = image_path[0] if len(image_path) > 0 else None
|
||
if isinstance(eval_prompts, list):
|
||
eval_prompts = eval_prompts[0] if len(eval_prompts) > 0 else ''
|
||
cfg_file = os.path.join(self.work_dir, output_model,
|
||
f'meta_{output_ckpt_name}.yaml')
|
||
output_model = output_model + '@' + output_ckpt_name
|
||
tuner_dict = {
|
||
'NAME':
|
||
output_model,
|
||
'NAME_ZH':
|
||
output_model,
|
||
# 'BASE_MODEL': base_model,
|
||
'BASE_MODEL':
|
||
base_model_revision,
|
||
'TUNER_TYPE':
|
||
tuner_name,
|
||
'DESCRIPTION':
|
||
'',
|
||
'MODEL_PATH':
|
||
model_path,
|
||
'IMAGE_PATH':
|
||
image_path,
|
||
'PROMPT_EXAMPLE':
|
||
eval_prompts,
|
||
'SOURCE':
|
||
'self_train',
|
||
'CKPT_NAME':
|
||
output_ckpt_name,
|
||
'PARAMS':
|
||
params_info,
|
||
'IS_SHARE':
|
||
self.BASE_CFG_VALUE[base_model][base_model_revision]
|
||
['is_share']
|
||
}
|
||
tuner_cfg = Config(cfg_dict=tuner_dict, load=False)
|
||
|
||
if not os.path.exists(model_path):
|
||
gr.Error(self.component_names.model_err4)
|
||
self.manager.inference.model_manage_ui.pipe_manager.register_tuner(
|
||
tuner_cfg,
|
||
name=tuner_cfg.NAME_ZH
|
||
if self.language == 'zh' else tuner_cfg.NAME,
|
||
is_customized=True)
|
||
|
||
pipeline_level_modules = self.manager.inference.model_manage_ui.pipe_manager.pipeline_level_modules
|
||
if tuner_cfg.BASE_MODEL not in pipeline_level_modules:
|
||
gr.Error(self.component_names.model_err3 +
|
||
tuner_cfg.BASE_MODEL)
|
||
pipeline_ins = pipeline_level_modules[tuner_cfg.BASE_MODEL]
|
||
diffusion_model = f"{tuner_cfg.BASE_MODEL}_{pipeline_ins.diffusion_model['name']}"
|
||
|
||
default_choices = self.manager.inference.model_manage_ui.pipe_manager.module_level_choices
|
||
if 'customized_tuners' in default_choices:
|
||
if tuner_cfg.BASE_MODEL not in default_choices[
|
||
'customized_tuners']:
|
||
default_choices['customized_tuners'] = {}
|
||
tunner_choices = default_choices['customized_tuners'][
|
||
tuner_cfg.BASE_MODEL]['choices']
|
||
tunner_default = default_choices['customized_tuners'][
|
||
tuner_cfg.BASE_MODEL]['default']
|
||
if not isinstance(tunner_default, list):
|
||
tunner_default = [tunner_default]
|
||
else:
|
||
tunner_choices = []
|
||
tunner_default = []
|
||
|
||
with open(cfg_file, 'w') as f_out:
|
||
yaml.dump(copy.deepcopy(tuner_cfg.cfg_dict),
|
||
f_out,
|
||
encoding='utf-8',
|
||
allow_unicode=True,
|
||
default_flow_style=False)
|
||
|
||
# example_image = tuner_cfg.get('IMAGE_PATH', None)
|
||
# if isinstance(example_image, list) and len(example_image)>0:
|
||
# example_image = example_image[0]
|
||
#
|
||
# prompt_example = tuner_cfg.get('PROMPT_EXAMPLE', None)
|
||
# if isinstance(prompt_example, list) and len(prompt_example)>0:
|
||
# prompt_example = prompt_example[0]
|
||
|
||
base_model = tuner_cfg.get('BASE_MODEL', '')
|
||
|
||
if not base_model == '':
|
||
if base_model not in manager.inference.tuner_ui.name_level_tuners:
|
||
manager.inference.tuner_ui.name_level_tuners[
|
||
base_model] = {}
|
||
manager.inference.tuner_ui.name_level_tuners[base_model][
|
||
output_model] = tuner_cfg
|
||
|
||
if tuner_cfg.BASE_MODEL == 'EDIT':
|
||
selected_tab = 'stylebooth_ui'
|
||
checkboxes = [
|
||
'使用微调', 'StyleBooth'
|
||
] if self.language == 'zh' else ['Use Tuners', 'StyleBooth']
|
||
else:
|
||
selected_tab = 'tuner_ui'
|
||
checkboxes = ['使用微调'
|
||
] if self.language == 'zh' else ['Use Tuners']
|
||
|
||
return (
|
||
gr.Tabs(selected='inference'), cfg_file,
|
||
gr.Tabs(selected=selected_tab),
|
||
gr.CheckboxGroup(value=checkboxes),
|
||
gr.Dropdown(value=diffusion_model),
|
||
gr.Dropdown(choices=tunner_choices, value=tunner_default)
|
||
# gr.Text(value=tuner_cfg.get('TUNER_TYPE', '')),
|
||
# gr.Text(value=tuner_cfg.get('BASE_MODEL', '')),
|
||
# gr.Image(value=example_image),
|
||
# gr.Text(value=tuner_cfg.get('DESCRIPTION', '')),
|
||
# gr.Text(value=prompt_example)
|
||
)
|
||
|
||
self.go_to_inferece_btn.click(
|
||
go_to_inferece,
|
||
inputs=[self.output_model_name, self.output_ckpt_name],
|
||
outputs=[
|
||
manager.tabs, manager.inference.infer_info,
|
||
manager.inference.setting_tab,
|
||
manager.inference.check_box_for_setting,
|
||
manager.inference.model_manage_ui.diffusion_model,
|
||
manager.inference.tuner_ui.custom_tuner_model
|
||
# manager.inference.tuner_ui.tuner_type,
|
||
# manager.inference.tuner_ui.base_model,
|
||
# manager.inference.tuner_ui.tuner_example,
|
||
# manager.inference.tuner_ui.tuner_desc,
|
||
# manager.inference.tuner_ui.tuner_prompt_example
|
||
],
|
||
queue=True)
|
||
|
||
def export_train_log(model_name):
|
||
current_log_folder = os.path.join(self.work_dir, model_name)
|
||
_ = trainer_ui.trainer_ins.get_log(model_name)
|
||
out_log = os.path.join(current_log_folder, 'output_std_log.txt')
|
||
if os.path.exists(out_log):
|
||
zip_path = f'{trainer_ui.current_train_model}_log.zip'
|
||
cache_folder = f'{trainer_ui.current_train_model}_log'
|
||
if not os.path.exists(
|
||
os.path.join(current_log_folder, 'tensorboard')):
|
||
os.makedirs(os.path.join(current_log_folder,
|
||
'tensorboard'),
|
||
exist_ok=True)
|
||
res = os.popen(
|
||
f"cd {current_log_folder} && mkdir -p '{cache_folder}' "
|
||
f"&& cp -rf tensorboard '{cache_folder}/tensorboard' "
|
||
f"&& cp -rf 'output_std_log.txt' '{cache_folder}/output_std_log.txt' "
|
||
f"&& zip -r '{zip_path}' '{cache_folder}'/* "
|
||
f"&& rm -rf '{cache_folder}'")
|
||
print(res.readlines())
|
||
return gr.File(value=os.path.join(current_log_folder,
|
||
zip_path),
|
||
visible=True)
|
||
else:
|
||
gr.Error(self.component_names.training_warn1)
|
||
return gr.File()
|
||
|
||
self.export_log.click(export_train_log,
|
||
inputs=[self.output_model_name],
|
||
outputs=[self.export_url],
|
||
queue=False)
|
||
|
||
def model_name_change(login_user_name):
|
||
self.load_history(login_user_name)
|
||
model_list = self.user_level_model_list.get(login_user_name, [])
|
||
if len(model_list) > 0:
|
||
model_name = model_list[-1]
|
||
else:
|
||
model_name = None
|
||
return gr.Dropdown(choices=model_list, value=model_name)
|
||
|
||
manager.user_name.change(model_name_change,
|
||
inputs=[manager.user_name],
|
||
outputs=[self.output_model_name],
|
||
queue=False)
|