diff --git a/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h b/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h
index a5909aad99a82529a0739cd28b1b72a146524f76..8afe2133c0488bbe04ec4803aac5dce6573f634d 100644
--- a/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h
+++ b/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h
@@ -26,14 +26,34 @@ namespace operators {
 template <typename T>
 struct FloorDivFunctor {
   inline HOSTDEVICE T operator()(T a, T b) const {
-    return static_cast<T>(floor(a / b));
+#ifdef __CUDA_ARCH__
+    if (b == 0) {
+      printf("Error: Divide by zero encounter in floor_divide\n");
+      asm("trap;");
+    }
+#else
+    if (b == 0)
+      PADDLE_THROW(platform::errors::InvalidArgument(
+          "Divide by zero encounter in floor_divide"));
+#endif
+    return static_cast<T>(std::trunc(a / b));
   }
 };
 
 template <typename T>
 struct InverseFloorDivFunctor {
   inline HOSTDEVICE T operator()(T a, T b) const {
-    return static_cast<T>(floor(b / a));
+#ifdef __CUDA_ARCH__
+    if (a == 0) {
+      printf("Error: Divide by zero encounter in floor_divide\n");
+      asm("trap;");
+    }
+#else
+    if (a == 0)
+      PADDLE_THROW(platform::errors::InvalidArgument(
+          "Divide by zero encounter in floor_divide"));
+#endif
+    return static_cast<T>(std::trunc(b / a));
   }
 };
 
diff --git a/paddle/fluid/operators/elementwise/elementwise_mod_op.h b/paddle/fluid/operators/elementwise/elementwise_mod_op.h
index 4306a471b76c5bd4f0a5284052d7d39aa5fbc279..47bd6af0b95ace2b9b753e38cfc5f191bc1bb942 100644
--- a/paddle/fluid/operators/elementwise/elementwise_mod_op.h
+++ b/paddle/fluid/operators/elementwise/elementwise_mod_op.h
@@ -24,13 +24,19 @@ namespace operators {
 
 template <typename T>
 struct ModFunctor {
-  inline HOSTDEVICE T operator()(T a, T b) const { return a % b; }
+  inline HOSTDEVICE T operator()(T a, T b) const {
+    T res = a % b;
+    if ((res != 0) && ((res < 0) != (b < 0))) res += b;
+    return res;
+  }
 };
 
 template <typename T>
 struct ModFunctorFP {
   inline HOSTDEVICE T operator()(T a, T b) const {
-    return fmod(b + fmod(a, b), b);
+    T res = fmod(a, b);
+    if ((res != 0) && ((b < 0) != (res < 0))) res += b;
+    return res;
   }
 };
 
diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_floordiv_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_floordiv_op.py
index 4fe085ce854726676bc1b1bef650419b3ebbfc86..0b6acc7615395ed99a484e0e56f9c62447a1f345 100644
--- a/python/paddle/fluid/tests/unittests/test_elementwise_floordiv_op.py
+++ b/python/paddle/fluid/tests/unittests/test_elementwise_floordiv_op.py
@@ -193,6 +193,27 @@ class TestFloorDivideAPI(unittest.TestCase):
                 z_expected = np.array([2., 0., 2.])
                 self.assertEqual((z_expected == z.numpy()).all(), True)
 
+        with fluid.dygraph.guard(fluid.CPUPlace()):
+            # divide by zero 
+            np_x = np.array([2, 3, 4])
+            np_y = np.array([0])
+            x = paddle.to_tensor(np_x)
+            y = paddle.to_tensor(np_y)
+            try:
+                z = x // y
+            except Exception as e:
+                print("Error: Divide by zero encounter in floor_divide\n")
+
+            # divide by zero 
+            np_x = np.array([2])
+            np_y = np.array([0, 0, 0])
+            x = paddle.to_tensor(np_x, dtype="int32")
+            y = paddle.to_tensor(np_y, dtype="int32")
+            try:
+                z = x // y
+            except Exception as e:
+                print("Error: Divide by zero encounter in floor_divide\n")
+
 
 if __name__ == '__main__':
     unittest.main()
diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_mod_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_mod_op.py
index 25769a42aa261c0b5ae9fe2795a337c668580a99..f5d8b4f704da8acd97475444346522f63d3724fd 100644
--- a/python/paddle/fluid/tests/unittests/test_elementwise_mod_op.py
+++ b/python/paddle/fluid/tests/unittests/test_elementwise_mod_op.py
@@ -204,6 +204,22 @@ class TestRemainderAPI(unittest.TestCase):
                 z_expected = np.array([1., 0., 1., 1., 0., 1.])
                 self.assertEqual((z_expected == z.numpy()).all(), True)
 
+                np_x = np.array([-3.3, 11.5, -2, 3.5])
+                np_y = np.array([-1.2, 2., 3.3, -2.3])
+                x = paddle.to_tensor(np_x)
+                y = paddle.to_tensor(np_y)
+                z = x % y
+                z_expected = np.array([-0.9, 1.5, 1.3, -1.1])
+                self.assertEqual(np.allclose(z_expected, z.numpy()), True)
+
+                np_x = np.array([-3, 11, -2, 3])
+                np_y = np.array([-1, 2, 3, -2])
+                x = paddle.to_tensor(np_x, dtype="int64")
+                y = paddle.to_tensor(np_y, dtype="int64")
+                z = x % y
+                z_expected = np.array([0, 1, 1, -1])
+                self.assertEqual(np.allclose(z_expected, z.numpy()), True)
+
 
 if __name__ == '__main__':
     unittest.main()