model.eval()

with torch.no_grad():
   for ...

def setup_seed(seed):
    np.random.seed(seed)
    random.seed(seed)
    torch.manual_seed(seed) #cpu
    torch.cuda.manual_seed_all(seed)  #并行g(shù)pu
    torch.backends.cudnn.deterministic = True  #cpu/gpu結(jié)果一致
    torch.backends.cudnn.benchmark = True   #訓(xùn)練集變化不大時使訓(xùn)練加速