upgrade to use paddle-2.0 API for sample code of paddle.t (#28726)

python/paddle/tensor/linalg.py

@@ -613,25 +613,25 @@ def dot(x, y, name=None):
 
 def t(input, name=None):
     """
-	:alias_main: paddle.t
-	:alias: paddle.t,paddle.tensor.t,paddle.tensor.linalg.t
-
     Transpose <=2-D tensor. 
     0-D and 1-D tensors are returned as it is and 2-D tensor is equal to 
-    the fluid.layers.transpose function which perm dimensions set 0 and 1.
+    the paddle.transpose function which perm dimensions set 0 and 1.
     
     Args:
-        input (Variable): The input Tensor. It is a N-D (N<=2) Tensor of data types float16, float32, float64, int32.
+        input (Tensor): The input Tensor. It is a N-D (N<=2) Tensor of data types float16, float32, float64, int32.
         name(str, optional): The default value is None.  Normally there is no need for 
             user to set this property.  For more information, please refer to :ref:`api_guide_Name`
     Returns:
-        Variable: A transposed n-D Tensor, with data type being float16, float32, float64, int32, int64.
+        Tensor: A transposed n-D Tensor, with data type being float16, float32, float64, int32, int64.
     
     For Example:
+
         .. code-block:: text
+
              # Example 1 (0-D tensor)
              x = tensor([0.79])
              paddle.t(x) = tensor([0.79])
+
              # Example 2 (1-D tensor)
              x = tensor([0.79, 0.84, 0.32])
              paddle.t(x) = tensor([0.79, 0.84, 0.32])
@@ -644,14 +644,14 @@ def t(input, name=None):
                                   [0.32, 0.57])
 
      Examples:
+
         .. code-block:: python
+
             import paddle
-            import paddle.fluid as fluid
-            x = fluid.data(name='x', shape=[2, 3],
-                            dtype='float32')
+            x = paddle.ones(shape=[2, 3], dtype='int32')
             x_transposed = paddle.t(x)
-            print x_transposed.shape
-            #(3L, 2L)
+            print(x_transposed.shape)
+            # [3, 2]
     """
     if len(input.shape) > 2:
         raise ValueError(