diff --git a/python/paddle/fluid/dygraph/math_op_patch.py b/python/paddle/fluid/dygraph/math_op_patch.py
index b15e6388884c7b194654f3c3b71b8c111f76e565..d2c779a85497917179736777dac25efa7cfba228 100644
--- a/python/paddle/fluid/dygraph/math_op_patch.py
+++ b/python/paddle/fluid/dygraph/math_op_patch.py
@@ -37,9 +37,6 @@ def monkey_patch_math_varbase():
     The difference is, in dygraph mode, use auto-generated op functions for better performance.
     """
 
-    def safe_get_dtype(var):
-        return var.dtype
-
     @no_grad
     def create_tensor(value, dtype, shape):
         out = _varbase_creator(dtype=dtype)
@@ -96,8 +93,9 @@ def monkey_patch_math_varbase():
                     print("new var's dtype is: {}, numpy dtype is {}".format(new_variable.dtype, new_variable.numpy().dtype))
 
         """
-        return core.ops.cast(self, 'in_dtype', self.dtype, 'out_dtype',
-                             convert_np_dtype_to_dtype_(dtype))
+        if not isinstance(dtype, core.VarDesc.VarType):
+            dtype = convert_np_dtype_to_dtype_(dtype)
+        return core.ops.cast(self, 'in_dtype', self.dtype, 'out_dtype', dtype)
 
     def _scalar_elementwise_op_(var, scale, bias):
         return core.ops.scale(var, 'scale', scale, 'bias', bias)
@@ -175,7 +173,7 @@ def monkey_patch_math_varbase():
                 elif isinstance(other_var, int):
                     return scalar_method(self, float(other_var))
 
-            lhs_dtype = safe_get_dtype(self)
+            lhs_dtype = self.dtype
 
             if not isinstance(other_var, core.VarBase):
                 if reverse:
@@ -185,7 +183,7 @@ def monkey_patch_math_varbase():
                     # add fill_op 
                     other_var = create_scalar(value=other_var, dtype=lhs_dtype)
 
-            rhs_dtype = safe_get_dtype(other_var)
+            rhs_dtype = other_var.dtype
             if lhs_dtype != rhs_dtype:
                 other_var = astype(other_var, lhs_dtype)
             if reverse:
diff --git a/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py b/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py
index 34f14b759526026f66930a4ba5322b5363fbb50f..14c3fb7c8bf06908bd8eabffbe46887a6546f6d2 100644
--- a/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py
+++ b/python/paddle/fluid/tests/unittests/test_math_op_patch_var_base.py
@@ -15,7 +15,6 @@
 from __future__ import print_function
 
 import unittest
-from decorator_helper import prog_scope
 import paddle.fluid as fluid
 import numpy as np
 import six
@@ -23,7 +22,7 @@ import six
 
 class TestMathOpPatchesVarBase(unittest.TestCase):
     def setUp(self):
-        self.shape = [10, 10]
+        self.shape = [10, 1024]
         self.dtype = np.float32
 
     def test_add(self):
@@ -251,6 +250,29 @@ class TestMathOpPatchesVarBase(unittest.TestCase):
                     rtol=1e-05,
                     atol=0.0))
 
+    def test_add_different_dtype(self):
+        a_np = np.random.random(self.shape).astype(np.float32)
+        b_np = np.random.random(self.shape).astype(np.float16)
+        with fluid.dygraph.guard():
+            a = fluid.dygraph.to_variable(a_np)
+            b = fluid.dygraph.to_variable(b_np)
+            res = a + b
+            self.assertTrue(np.array_equal(res.numpy(), a_np + b_np))
+
+    def test_astype(self):
+        a_np = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
+        with fluid.dygraph.guard():
+            a = fluid.dygraph.to_variable(a_np)
+            res1 = a.astype(np.float16)
+            res2 = a.astype('float16')
+            res3 = a.astype(fluid.core.VarDesc.VarType.FP16)
+
+            self.assertEqual(res1.dtype, res2.dtype)
+            self.assertEqual(res1.dtype, res3.dtype)
+
+            self.assertTrue(np.array_equal(res1.numpy(), res2.numpy()))
+            self.assertTrue(np.array_equal(res1.numpy(), res3.numpy()))
+
 
 if __name__ == '__main__':
     unittest.main()