固定随机种子-本人备忘录

本文全部经验来自 目标检测tricks-如何固定随机种子(以yolov7为例)_哔哩哔哩_bilibili

添加固定随机种子代码到yolov7的utils/general.py文件中代码如下：

import pkg_resources as pkg
def check_version(current='0.0.0', minimum='0.0.0', name='version ', pinned=False, hard=False, verbose=False):
    # Check version vs. required version
    current, minimum = (pkg.parse_version(x) for x in (current, minimum))
    result = (current == minimum) if pinned else (current >= minimum)  # bool
    return result


def set_seeds(seed=0, deterministic=False):
    # Initialize random number generator (RNG) seeds https://pytorch.org/docs/stable/notes/randomness.html
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    torch.cuda.manual_seed_all(seed)  # for Multi-GPU, exception safe
    # torch.backends.cudnn.benchmark = True  # AutoBatch problem https://github.com/ultralytics/yolov5/issues/9287
    if deterministic and check_version(torch.__version__, '1.12.0'):  # https://github.com/ultralytics/yolov5/pull/8213
        torch.use_deterministic_algorithms(True)
        torch.backends.cudnn.deterministic = True
        os.environ['CUBLAS_WORKSPACE_CONFIG'] = ':4096:8'
        os.environ['PYTHONHASHSEED'] = str(seed)

在train,py文件里添加：

1.在import里添加set_seeds导入

2.在train.py文件里把1的位置注释掉，添加2的代码

结束，所有工作添加完成。