diff --git a/python/paddle/fluid/layers/control_flow.py b/python/paddle/fluid/layers/control_flow.py
index 2002b8a95decfd6d6c55538e2dff0a793828dd9b..96417ecda0a749e187dd0c27401a60053a685087 100755
--- a/python/paddle/fluid/layers/control_flow.py
+++ b/python/paddle/fluid/layers/control_flow.py
@@ -3788,7 +3788,7 @@ def reorder_lod_tensor_by_rank(x, rank_table):
     return out
 
 
-def is_empty(x, cond=None):
+def is_empty(x, name=None):
     """
     :alias_main: paddle.is_empty
 	:alias: paddle.is_empty,paddle.tensor.is_empty,paddle.tensor.logic.is_empty
@@ -3798,35 +3798,60 @@ def is_empty(x, cond=None):
 
     Args:
         x (Variable): The Variable to be tested.
-        cond (Variable, optional): Output parameter. Default: None. If this parameter is given, it
-                              saves the test result of given 'x'.
+        name (str, optional): The default value is ``None`` . Normally users
+                            don't have to set this parameter. For more information,
+                            please refer to :ref:`api_guide_Name` .
 
     Returns:
         Variable: A bool scalar. True if 'x' is an empty Variable.
 
-    Raises:
-        TypeError: If input cond is not a variable, or cond's dtype is
-                   not bool.
-
     Examples:
         .. code-block:: python
 
-          import paddle.fluid as fluid
-          input = fluid.layers.data(name="input", shape=[4, 32, 32], dtype="float32")
-          res = fluid.layers.is_empty(x=input)
-          # or:
-          # fluid.layers.is_empty(x=input, cond=res)
+            # static mode
+            import numpy as np
+            import paddle
+
+            paddle.enable_static()
+            input = paddle.static.data(name="input", shape=[4, 32, 32], dtype="float32")
+            res = paddle.is_empty(x=input)
+
+            exe = paddle.static.Executor(paddle.CPUPlace())
+            data = np.ones((4, 32, 32)).astype(np.float32)
+            out = exe.run(feed={'input':data}, fetch_list=[res])
+            print("is_empty: ", out)
+            # ('out:', [array([False])])
+
+
+        .. code-block:: python
+
+            # dygraph_mode
+            import paddle
+
+            input = paddle.rand(shape=[4, 32, 32], dtype='float32')
+            res = paddle.is_empty(x=input)
+            print("res:", res)
+            # ('res:', Tensor: eager_tmp_1
+            #    - place: CPUPlace
+            #    - shape: [1]
+            #    - layout: NCHW
+            #    - dtype: bool
+            #    - data: [0])
 
     """
+    if in_dygraph_mode():
+        assert isinstance(
+            x, Variable
+        ), "The input data 'x' in is_empty must be Variable in dygraph mode"
+        return core.ops.is_empty(x)
+
     check_variable_and_dtype(x, 'x', ['float32', 'float64', 'int32', 'int64'],
                              'is_empty')
-    check_type(cond, 'cond', (Variable, type(None)), 'is_empty')
+    check_type(name, "name", (str, type(None)), "is_empty")
+
     helper = LayerHelper("is_empty", **locals())
-    if cond is None:
-        cond = helper.create_variable_for_type_inference(dtype='bool')
-        cond.stop_gradient = True
-    else:
-        check_dtype(cond.dtype, 'cond', ['bool'], 'is_empty')
+    cond = helper.create_variable_for_type_inference(dtype='bool')
+    cond.stop_gradient = True
     helper.append_op(
         type='is_empty', inputs={'X': [x]}, outputs={'Out': [cond]})
     return cond