Update image links in tensor_cn.md

Author: Echo-Nie

docs/guides/beginner/tensor_cn.md

@@ -120,7 +120,7 @@ Tensor(shape=[2, 2, 5], dtype=int64, place=Place(gpu:0), stop_gradient=True,
 上述不同维度的 Tensor 可视化的表示如下图所示：
 
 
-<center><img src="https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/01_paddle2.0_introduction/basic_concept/images/Tensor_2.0.png?raw=true" width="800" ></center>
+<center><img src="https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/beginner/images/Tensor_2.0.png" width="800" ></center>
 <br><center>图 1 不同维度的 Tensor 可视化表示</center>
 
 需要注意的是，Tensor 必须形如矩形，即在任何一个维度上，元素的数量必须相等，否则会抛出异常，示例如下：
@@ -270,7 +270,7 @@ ndim_4_Tensor = paddle.ones([2, 3, 4, 5])
 ```
 
 
-<center><img src="https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/01_paddle2.0_introduction/basic_concept/images/Axis_2.0.png?raw=true" width="800" ></center>
+<center><img src="https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/beginner/images/Axis_2.0.png" width="800" ></center>
 <br><center>图 2 Tensor 的 shape、axis、dimension、ndim 之间的关系</center>
 
 ```python
@@ -649,7 +649,7 @@ print(z.shape)
 ```
 
 
-<center><img src="https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/01_paddle2.0_introduction/basic_concept/images/Tensor_broadcast.png?raw=true" width="800" ></center>
+<center><img src="https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/beginner/images/Tensor_broadcast.png" width="800" ></center>
 <br><center>图 3 Tensor 广播示例</center>
 
 ## <span id="newtensor6">六、Tensor 与 Numpy 数组相互转换</span>