pytorch预测之解决多次预测结果不一致问题

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gpu
    torch.backends.cudnn.deterministic = True  #cpu/gpu结果一致
    torch.backends.cudnn.benchmark = True   #训练集变化不大时使训练加速