diff --git a/paddle/fluid/pybind/imperative.cc b/paddle/fluid/pybind/imperative.cc
index 8b01f02ee2c3a..4403eb469723a 100644
--- a/paddle/fluid/pybind/imperative.cc
+++ b/paddle/fluid/pybind/imperative.cc
@@ -985,6 +985,12 @@ void BindImperative(py::module *m_ptr) {
                 auto value_tensor =
                     value_obj.cast<std::shared_ptr<imperative::VarBase>>();
                 ins.insert({"ValueTensor", {value_tensor}});
+
+                // pass the stop_gradient from value to tensor
+                if (!value_tensor->OverridedStopGradient() &&
+                    self->OverridedStopGradient()) {
+                  self->SetOverridedStopGradient(false);
+                }
               } else if (py::isinstance<py::array>(value_obj)) {
                 auto value_tensor = std::shared_ptr<imperative::VarBase>(
                     new imperative::VarBase(false,
diff --git a/python/paddle/fluid/tests/unittests/test_set_value_op.py b/python/paddle/fluid/tests/unittests/test_set_value_op.py
index 21f506d03ce68..e9809318cb393 100644
--- a/python/paddle/fluid/tests/unittests/test_set_value_op.py
+++ b/python/paddle/fluid/tests/unittests/test_set_value_op.py
@@ -1154,6 +1154,18 @@ def set_value5(t, value):
             msg="The gradient of input should be \n{},\n but reveived {}".
             format(value_grad, value.grad.numpy()))
 
+        # case 6: pass stop_gradient from value to x
+        x = paddle.zeros([8, 8], dtype='float32')
+        value = paddle.to_tensor([10], dtype='float32', stop_gradient=False)
+
+        self.assertTrue(x.stop_gradient)
+        self.assertTrue(x.is_leaf)
+
+        x[0, :] = value
+
+        self.assertTrue(~x.stop_gradient)
+        self.assertTrue(~x.is_leaf)
+
     def test_static_graph(self):
         paddle.enable_static()