diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py
index e33b34cc9254b18a18c293fb3670203fecdeb38f..2d874b4806c9e1449a170017440c4b5038ff93bf 100644
--- a/python/paddle/fluid/layers/tensor.py
+++ b/python/paddle/fluid/layers/tensor.py
@@ -685,8 +685,9 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
     """
 
     attrs = {'force_cpu': force_cpu}
+    dtype = convert_dtype(dtype)
     if not isinstance(value, Variable):
-        if convert_dtype(dtype) in ['int64', 'int32']:
+        if dtype in ['int64', 'int32']:
             attrs['str_value'] = str(int(value))
         else:
             attrs['str_value'] = str(float(value))
@@ -697,7 +698,7 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
             out = _varbase_creator(dtype=dtype)
 
         if isinstance(value, Variable):
-            if convert_dtype(dtype) in ['int64', 'int32']:
+            if dtype in ['int64', 'int32']:
                 attrs['str_value'] = str(int(value.numpy()))
             else:
                 attrs['str_value'] = str(float(value.numpy()))
@@ -712,6 +713,8 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None):
     helper = LayerHelper("fill_constant", **locals())
     inputs = {}
     if isinstance(value, Variable):
+        if convert_dtype(value.dtype) != dtype:
+            value = cast(value, dtype)
         inputs['ValueTensor'] = value
 
     check_dtype(dtype, 'dtype',
diff --git a/python/paddle/fluid/tests/unittests/test_fill_constant_op.py b/python/paddle/fluid/tests/unittests/test_fill_constant_op.py
index 3eb761f925a677dcbaa3d7e39221299013f84b33..aefc809bd5cb852d3fde95dff4550e506c5f1c12 100644
--- a/python/paddle/fluid/tests/unittests/test_fill_constant_op.py
+++ b/python/paddle/fluid/tests/unittests/test_fill_constant_op.py
@@ -269,18 +269,26 @@ class TestFillConstantAPI(unittest.TestCase):
         out_6 = fluid.layers.fill_constant(
             shape=shape_tensor_int64, dtype=np.float32, value=1.1)
 
-        val = fluid.layers.fill_constant(shape=[1], dtype=np.float32, value=1.1)
+        val1 = fluid.layers.fill_constant(
+            shape=[1], dtype=np.float32, value=1.1)
+        val2 = fluid.layers.fill_constant(
+            shape=[1], dtype=np.float64, value=1.1)
         out_7 = fluid.layers.fill_constant(
-            shape=shape_tensor_int64, dtype=np.float32, value=val)
+            shape=shape_tensor_int64, dtype=np.float32, value=val1)
+
+        out_8 = fluid.layers.fill_constant(
+            shape=shape_tensor_int64, dtype=np.float32, value=val2)
 
         exe = fluid.Executor(place=fluid.CPUPlace())
-        res_1, res_2, res_3, res_4, res_5, res_6, res_7 = exe.run(
+        res_1, res_2, res_3, res_4, res_5, res_6, res_7, res_8 = exe.run(
             fluid.default_main_program(),
             feed={
                 "shape_tensor_int32": np.array([1, 2]).astype("int32"),
                 "shape_tensor_int64": np.array([1, 2]).astype("int64"),
             },
-            fetch_list=[out_1, out_2, out_3, out_4, out_5, out_6, out_7])
+            fetch_list=[
+                out_1, out_2, out_3, out_4, out_5, out_6, out_7, out_8
+            ])
 
         assert np.array_equal(res_1, np.full([1, 2], 1.1, dtype="float32"))
         assert np.array_equal(res_2, np.full([1, 2], 1.1, dtype="float32"))
@@ -289,6 +297,31 @@ class TestFillConstantAPI(unittest.TestCase):
         assert np.array_equal(res_5, np.full([1, 2], 1.1, dtype="float32"))
         assert np.array_equal(res_6, np.full([1, 2], 1.1, dtype="float32"))
         assert np.array_equal(res_7, np.full([1, 2], 1.1, dtype="float32"))
+        assert np.array_equal(res_8, np.full([1, 2], 1.1, dtype="float32"))
+
+
+class TestFillConstantImperative(unittest.TestCase):
+    def test_api(self):
+        with fluid.dygraph.guard():
+            data1 = np.array([1, 2]).astype('int32')
+            data2 = np.array([1.1]).astype('float32')
+            shape = fluid.dygraph.to_variable(data1)
+            val = fluid.dygraph.to_variable(data2)
+            res1 = fluid.layers.fill_constant(
+                shape=[1, 2], dtype='float32', value=1.1)
+            res2 = fluid.layers.fill_constant(
+                shape=shape, dtype='float32', value=1.1)
+            res3 = fluid.layers.fill_constant(
+                shape=shape, dtype='float32', value=val)
+            assert np.array_equal(
+                res1.numpy(), np.full(
+                    [1, 2], 1.1, dtype="float32"))
+            assert np.array_equal(
+                res2.numpy(), np.full(
+                    [1, 2], 1.1, dtype="float32"))
+            assert np.array_equal(
+                res3.numpy(), np.full(
+                    [1, 2], 1.1, dtype="float32"))
 
 
 class TestFillConstantOpError(unittest.TestCase):
diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py
index 8b07bddfc15fc27310430d77c45e11d038ac6b59..02c908be347ab00ce29babd01f227e8367e259f2 100644
--- a/python/paddle/tensor/creation.py
+++ b/python/paddle/tensor/creation.py
@@ -248,7 +248,7 @@ def zeros(shape, dtype=None, name=None):
           
           # shape is a Tensor
           shape = paddle.fill_constant(shape=[2], dtype='int32', value=2)
-          data3 = paddle.ones(shape=shape, dtype='int32') 
+          data3 = paddle.zeros(shape=shape, dtype='int32') 
           # [[0 0]
           #  [0 0]]
     """