numpy随机种子
#此时x,y产生的随机数一致 np.random.seed(22) x = np.random.randint(1,10,(3,3)) np.random.seed(22) y = np.random.randint(1,10,(3,3)) #此时x,y不一致，但是每次运行生成的x,y与第一次生成的x,y一致 np.random.seed(22) x = np.random.randint(1,10,(3,3)) y = np.random.randint(1,10,(3,3))numpy–>tensor 类别转换
#x = x.astype(np.float32) np与np数据类型转换 #y = y.float() tensor与tensor数据类型转换 x = np.random.randn(3,3) x = torch.from_numpy(x) x = torch.Tensor(x) x = torch.from_numpy(x).double()tensor–>numpy
x = torch.randn(3,3) x = np.array(x) x = x.numpy()