colomi
0eb61f3e60
包含： - hair_service_sd: 换发型/换发色算法服务 (端口 8801) - photo_service: LoRA 训练调度服务 (端口 32678) - stable-diffusion-webui: SD WebUI 推理服务 (端口 57860) - kohya_ss_home: 训练环境代码 - meidaojia: 监控测试脚本 - setup.sh: 一键部署脚本 (conda环境恢复 + 配置生成 + 完整性检查) - start_all_services.sh: 启动3个服务 - configure.ini.template: 路径模板化 (BASE_DIR自动推导) - conda_envs/py310.yml: py310 环境定义 大文件 (weights/, models/, data/, conda_envs/*.tar.gz 等) 通过 .gitignore 排除， 由网盘单独上传。
124 lines
3.9 KiB
Python
Executable File
124 lines
3.9 KiB
Python
Executable File
import json
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import os
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import os.path
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import threading
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import diskcache
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import tqdm
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from modules.paths import data_path, script_path
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cache_filename = os.environ.get('SD_WEBUI_CACHE_FILE', os.path.join(data_path, "cache.json"))
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cache_dir = os.environ.get('SD_WEBUI_CACHE_DIR', os.path.join(data_path, "cache"))
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caches = {}
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cache_lock = threading.Lock()
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def dump_cache():
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"""old function for dumping cache to disk; does nothing since diskcache."""
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pass
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def make_cache(subsection: str) -> diskcache.Cache:
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return diskcache.Cache(
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os.path.join(cache_dir, subsection),
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size_limit=2**32, # 4 GB, culling oldest first
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disk_min_file_size=2**18, # keep up to 256KB in Sqlite
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)
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def convert_old_cached_data():
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try:
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with open(cache_filename, "r", encoding="utf8") as file:
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data = json.load(file)
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except FileNotFoundError:
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return
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except Exception:
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os.replace(cache_filename, os.path.join(script_path, "tmp", "cache.json"))
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print('[ERROR] issue occurred while trying to read cache.json; old cache has been moved to tmp/cache.json')
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return
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total_count = sum(len(keyvalues) for keyvalues in data.values())
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with tqdm.tqdm(total=total_count, desc="converting cache") as progress:
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for subsection, keyvalues in data.items():
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cache_obj = caches.get(subsection)
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if cache_obj is None:
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cache_obj = make_cache(subsection)
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caches[subsection] = cache_obj
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for key, value in keyvalues.items():
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cache_obj[key] = value
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progress.update(1)
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def cache(subsection):
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"""
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Retrieves or initializes a cache for a specific subsection.
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Parameters:
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subsection (str): The subsection identifier for the cache.
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Returns:
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diskcache.Cache: The cache data for the specified subsection.
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"""
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cache_obj = caches.get(subsection)
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if not cache_obj:
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with cache_lock:
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if not os.path.exists(cache_dir) and os.path.isfile(cache_filename):
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convert_old_cached_data()
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cache_obj = caches.get(subsection)
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if not cache_obj:
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cache_obj = make_cache(subsection)
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caches[subsection] = cache_obj
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return cache_obj
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def cached_data_for_file(subsection, title, filename, func):
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"""
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Retrieves or generates data for a specific file, using a caching mechanism.
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Parameters:
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subsection (str): The subsection of the cache to use.
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title (str): The title of the data entry in the subsection of the cache.
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filename (str): The path to the file to be checked for modifications.
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func (callable): A function that generates the data if it is not available in the cache.
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Returns:
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dict or None: The cached or generated data, or None if data generation fails.
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The `cached_data_for_file` function implements a caching mechanism for data stored in files.
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It checks if the data associated with the given `title` is present in the cache and compares the
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modification time of the file with the cached modification time. If the file has been modified,
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the cache is considered invalid and the data is regenerated using the provided `func`.
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Otherwise, the cached data is returned.
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If the data generation fails, None is returned to indicate the failure. Otherwise, the generated
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or cached data is returned as a dictionary.
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"""
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existing_cache = cache(subsection)
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ondisk_mtime = os.path.getmtime(filename)
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entry = existing_cache.get(title)
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if entry:
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cached_mtime = entry.get("mtime", 0)
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if ondisk_mtime > cached_mtime:
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entry = None
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if not entry or 'value' not in entry:
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value = func()
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if value is None:
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return None
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entry = {'mtime': ondisk_mtime, 'value': value}
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existing_cache[title] = entry
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dump_cache()
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return entry['value']
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