diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 760f5ce58bf268919667db1c0623ce2096d2bdae..3ac43df872e377e96f49d6852744febde219d69d 100755
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -5459,7 +5459,7 @@ def transpose(x, perm, name=None):
 
     Args:
         x (Variable): The input Tensor. It is a N-D Tensor of data types float32, float64, int32.
-        perm (list): Permute the input according to the data of perm.
+        perm (list|tuple): Permute the input according to the data of perm.
         name (str): The name of this layer. It is optional.
 
     Returns:
@@ -5492,14 +5492,12 @@ def transpose(x, perm, name=None):
 
         .. code-block:: python
 
-            # use append_batch_size=False to avoid prepending extra
-            # batch size in shape
-            import paddle.fluid as fluid
-            x = fluid.layers.data(name='x', shape=[2, 3, 4],
-                            dtype='float32', append_batch_size=False)
-            x_transposed = fluid.layers.transpose(x, perm=[1, 0, 2])
-            print x_transposed.shape
-            #(3L, 2L, 4L)
+            import paddle
+
+            x = paddle.randn([2, 3, 4])
+            x_transposed = paddle.transpose(x, perm=[1, 0, 2])
+            print(x_transposed.shape)
+            # [3L, 2L, 4L]
 
     """
     if in_dygraph_mode():
@@ -5509,8 +5507,9 @@ def transpose(x, perm, name=None):
     check_variable_and_dtype(
         x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'],
         'transpose')
-    check_type(perm, 'perm', list, 'transpose')
-
+    check_type(perm, 'perm', (list, tuple), 'transpose')
+    if isinstance(perm, tuple):
+        perm = list(perm)
     if len(perm) != len(x.shape):
         raise ValueError(
             "Input(perm) is the permutation of dimensions of Input(x), "
diff --git a/python/paddle/fluid/tests/unittests/test_transpose_op.py b/python/paddle/fluid/tests/unittests/test_transpose_op.py
index 56333211469db5705d04cc5ca253bf01679190a5..f72df8cbe4640941d014b310325a8bb56d8af65f 100644
--- a/python/paddle/fluid/tests/unittests/test_transpose_op.py
+++ b/python/paddle/fluid/tests/unittests/test_transpose_op.py
@@ -21,6 +21,7 @@ import paddle
 import paddle.fluid as fluid
 from paddle.fluid import Program, program_guard
 
+paddle.enable_static()
 
 class TestTransposeOp(OpTest):
     def setUp(self):
@@ -113,6 +114,7 @@ class TestCase9(TestTransposeOp):
 
 class TestTransposeOpError(unittest.TestCase):
     def test_errors(self):
+        paddle.enable_static()
         with program_guard(Program(), Program()):
             x = fluid.layers.data(name='x', shape=[10, 5, 3], dtype='float64')
 
@@ -149,6 +151,39 @@ class TestTransposeOpError(unittest.TestCase):
 
             self.assertRaises(ValueError, test_each_elem_value_check)
 
+class TestTransposeApi(unittest.TestCase):
+    def test_static_out(self):
+        paddle.enable_static()
+        with paddle.static.program_guard(paddle.static.Program()):
+            x = paddle.static.data(name='x', shape=[2, 3, 4], dtype='float32')
+            x_trans1 = paddle.transpose(x, perm=[1, 0, 2])
+            x_trans2 = paddle.transpose(x, perm=(2, 1, 0))
+            place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            x_np = np.random.random([2, 3, 4]).astype("float32")
+            result1, result2 = exe.run(feed={"x": x_np}, fetch_list=[x_trans1, x_trans2])
+            expected_result1 = np.transpose(x_np, [1, 0, 2])
+            expected_result2 = np.transpose(x_np, (2, 1, 0))
+            
+            np.testing.assert_array_equal(result1, expected_result1)
+            np.testing.assert_array_equal(result2, expected_result2)
+
+    def test_dygraph_out(self):
+        # This is an old test before 2.0 API so we need to disable static
+        # to trigger dygraph
+        paddle.disable_static()
+        x = paddle.randn([2, 3, 4])
+        x_trans1 = paddle.transpose(x, perm=[1, 0, 2])
+        x_trans2 = paddle.transpose(x, perm=(2, 1, 0))
+        x_np = x.numpy()
+        expected_result1 = np.transpose(x_np, [1, 0, 2])
+        expected_result2 = np.transpose(x_np, (2, 1, 0))
+
+        np.testing.assert_array_equal(x_trans1.numpy(), expected_result1)
+        np.testing.assert_array_equal(x_trans2.numpy(), expected_result2)
+        # This is an old test before 2.0 API so we enable static again after
+        # dygraph test
+        paddle.enable_static()
 
 class TestTAPI(unittest.TestCase):
     def test_out(self):