import random
import numpy as np
import torch

def set_random_seed(seed):
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    torch.cuda.manual_seed_all(seed)
    random.seed(seed)
    np.random.seed(seed)

def length2mask(length, size=None):
    batch_size = len(length)
    size = int(max(length)) if size is None else size
    mask = (torch.arange(size, dtype=torch.int64).unsqueeze(0).repeat(batch_size, 1)
                > (torch.LongTensor(length) - 1).unsqueeze(1)).cuda()
    return mask