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再現性についてのお願い

恐らく後から追加してくださる予定だったと思うのですが,念のため早い内に共有しておきたいのでご確認ください.
論文にまとめる段階で,結果の再現性の確保をお願いします.
計算のパフォーマンスは落ちてしまいますが,よろしくお願いいたします!

ランダムシードの固定

def init_seed(seed=1234):
    """
    PyTorchの再現性を確保する.
    計算の冒頭で呼び出せば良い.
    
    Parameters
    ----------
    seed: integer
        ランダムシード値
        
    Returns
    ----------
    None
    
    """
    np.random.seed(seed)
    random.seed(seed)
    torch.manual_seed(seed)
    torch.backends.cudnn.deterministic = True
    torch.backends.cudnn.benchmark = False

GeneratorのWorkerの固定

また,torch.utils.data.DataLoaderで複数のWorkerを指定する場合も再現性の確保が必要です.

def worker_init_fn(worker_id):
    """
    PyTorchのtorch.utils.data.DataLoaderで複数のWorkerを指定する場合に再現性を確保する.
    この関数をoption"worker_init_fn"で指定する.
    """
    new_seed = np.random.get_state()[1][0] + worker_id
    np.random.seed(new_seed)
    random.seed(new_seed)
    return

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