diff --git a/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h b/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h
index 5dc93740949e6e7c25be564927c8fcffde1a18d6..721c23e38307fddb63d41baddc395afa94f40336 100644
--- a/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h
+++ b/paddle/fluid/operators/elementwise/elementwise_floordiv_op.h
@@ -61,8 +61,15 @@ void elementwise_floor_div(const framework::ExecutionContext &ctx,
                            const framework::Tensor *x,
                            const framework::Tensor *y, framework::Tensor *z) {
   int axis = ctx.Attr<int>("axis");
-  ElementwiseComputeEx<FloorDivFunctor<T>, DeviceContext, T>(
-      ctx, x, y, axis, FloorDivFunctor<T>(), z);
+  auto x_dims = x->dims();
+  auto y_dims = y->dims();
+  if (x_dims.size() >= y_dims.size()) {
+    ElementwiseComputeEx<FloorDivFunctor<T>, DeviceContext, T>(
+        ctx, x, y, axis, FloorDivFunctor<T>(), z);
+  } else {
+    ElementwiseComputeEx<InverseFloorDivFunctor<T>, DeviceContext, T>(
+        ctx, x, y, axis, InverseFloorDivFunctor<T>(), z);
+  }
 }
 
 template <typename DeviceContext, typename T>
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 f339081e31b87b8d5584fd4f866e0aaf6f391ea7..007affc14084956870e50e0e1b6b650d13cc3926 100644
--- a/python/paddle/fluid/tests/unittests/test_elementwise_floordiv_op.py
+++ b/python/paddle/fluid/tests/unittests/test_elementwise_floordiv_op.py
@@ -67,6 +67,13 @@ class TestElementwiseModOp_scalar(TestElementwiseModOp):
         self.out = np.floor_divide(self.x, self.y)
 
 
+class TestElementwiseModOpInverse(TestElementwiseModOp):
+    def init_input_output(self):
+        self.x = np.random.uniform(0, 10000, [10]).astype(self.dtype)
+        self.y = np.random.uniform(0, 1000, [10, 10]).astype(self.dtype)
+        self.out = np.floor_divide(self.x, self.y)
+
+
 class TestFloorDivideOp(unittest.TestCase):
     def test_name(self):
         with fluid.program_guard(fluid.Program()):