fix docstring for expand, expand_as and tile. (#26529)

* fix docstring, test=document_fix

python/paddle/tensor/manipulation.py

@@ -910,7 +910,7 @@ def chunk(x, chunks, axis=0, name=None):
             paddle.disable_static()
             # x is a Tensor which shape is [3, 9, 5]
             x_np = np.random.random([3, 9, 5]).astype("int32")
-            x = paddle.to_variable(x_np)
+            x = paddle.to_tensor(x_np)
 
             out0, out1, out22 = paddle.chunk(x, chunks=3, axis=1)
             # out0.shape [3, 3, 5]
@@ -957,17 +957,17 @@ def tile(x, repeat_times, name=None):
             np_data = np.array([1, 2, 3]).astype('int32')
             data = paddle.to_tensor(np_data)
             out = paddle.tile(data, repeat_times=[2, 1])
-			np_out = out.numpy()
+            np_out = out.numpy()
             # [[1, 2, 3], [1, 2, 3]]
 
             out = paddle.tile(data, repeat_times=[2, 2])
-			np_out = out.numpy()
+            np_out = out.numpy()
             # [[1, 2, 3, 1, 2, 3], [1, 2, 3, 1, 2, 3]]
 
             np_repeat_times = np.array([2, 1]).astype("int32")
             repeat_times = paddle.to_tensor(np_repeat_times)
             out = paddle.tile(data, repeat_times=repeat_times)
-			np_out = out.numpy()
+            np_out = out.numpy()
             # [[1, 2, 3], [1, 2, 3]]
     """
     check_variable_and_dtype(
@@ -1043,7 +1043,7 @@ def expand_as(x, y, name=None):
             data_x = paddle.to_tensor(np_data_x)
             data_y = paddle.to_tensor(np_data_y)
             out = paddle.expand_as(data_x, data_y)
-			np_out = out.numpy()
+            np_out = out.numpy()
             # [[1, 2, 3], [1, 2, 3]]
     """
     check_variable_and_dtype(
@@ -1096,13 +1096,7 @@ def expand(x, shape, name=None):
             np_data = np.array([1, 2, 3]).astype('int32')
             data = paddle.to_tensor(np_data)
             out = paddle.expand(data, shape=[2, 3])
-			out = out.numpy()
-            # [[1, 2, 3], [1, 2, 3]]
-
-            np_shape = np.array([2, 3]).astype('int32')
-            shape = paddle.to_tensor(np_shape)
-            out = paddle.expand(data, shape=shape)
-			out = out.numpy()
+            out = out.numpy()
             # [[1, 2, 3], [1, 2, 3]]
     """
     check_variable_and_dtype(