diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 11a4d933245dde73a092d0d014f2fc63a175f999..7233d27e847512e7eaa5682247b3b363159973fc 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -12796,16 +12796,14 @@ def hash(input, hash_size, num_hash=1, name=None):
 
             place = fluid.core.CPUPlace()
 
-            x = fluid.data(name="x", shape=[1], dtype="int32", lod_level=1)
-            res = fluid.layers.hash(name="res",input=x, hash_size=1000, num_hash=4)
+            x = fluid.data(name="x", shape=[2,2], dtype="int32", lod_level=1)
+            res = fluid.layers.hash(name="res", input=x, hash_size=1000, num_hash=4)
 
             exe = fluid.Executor(place)
             exe.run(fluid.default_startup_program())
             in1 = np.array([[1,2],[3,4]]).astype("int32")
             print(in1)
-            x_i = fluid.core.LoDTensor()
-            x_i.set(in1,place)
-            x_i.set_recursive_sequence_lengths([[0,2]])
+            x_i = fluid.create_lod_tensor(in1, [[0, 2]], place)
             res = exe.run(fluid.default_main_program(), feed={'x':x_i}, fetch_list=[res], return_numpy=False)
             print(np.array(res[0]))
             # [[[722]
@@ -12818,8 +12816,8 @@ def hash(input, hash_size, num_hash=1, name=None):
             #   [901]]]
     """
     check_variable_and_dtype(input, 'input', ['int32', 'int64'], 'hash')
-    check_type(hash_size, 'hash_size', ['int32', 'int64'], 'hash')
-    check_type(num_hash, 'num_hash', ['int32', 'int64'], 'hash')
+    check_type(hash_size, 'hash_size', int, 'hash')
+    check_type(num_hash, 'num_hash', int, 'hash')
     helper = LayerHelper('hash', **locals())
     out = helper.create_variable_for_type_inference(
         helper.input_dtype(), stop_gradient=True)