Shaun ZhouandClaude Opus 5
f4eff8beee
- config: yaml `_base_` 继承 + 深度合并 + 命令行 `--set a.b.c=value` 覆盖，检测循环引用 - registry: 组件按名注册与构建，模型/数据集共用 - device: require_cuda() 守卫，按 CLAUDE.md 约定禁止在无 Nvidia GPU 的设备上训练； 评估与导出走 resolve_device() 允许 CPU - labels: multilabel / multiclass 两种图像级标签形式的共用定义 - logging / seed: 控制台+文件日志、随机种子与 cudnn 确定性 Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
34 lines
743 B
Python
34 lines
743 B
Python
"""随机种子与 cudnn 确定性设置。"""
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from __future__ import annotations
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import os
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import random
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def seed_everything(seed: int, deterministic: bool = False) -> int:
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random.seed(seed)
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os.environ["PYTHONHASHSEED"] = str(seed)
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try:
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import numpy as np
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np.random.seed(seed)
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except ImportError: # pragma: no cover
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pass
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try:
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import torch
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torch.manual_seed(seed)
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torch.cuda.manual_seed_all(seed)
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if deterministic:
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torch.backends.cudnn.deterministic = True
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torch.backends.cudnn.benchmark = False
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else:
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torch.backends.cudnn.benchmark = True
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except ImportError: # pragma: no cover
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pass
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return seed
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