diff --git a/imperative/python/megengine/autodiff/grad_manager.py b/imperative/python/megengine/autodiff/grad_manager.py
index a64b4fd1..54575a70 100644
--- a/imperative/python/megengine/autodiff/grad_manager.py
+++ b/imperative/python/megengine/autodiff/grad_manager.py
@@ -112,6 +112,14 @@ class GradManager:
             else:
                 logger.warning("params with index {} is not attached.".format(idx))
 
+    def clear_grad(self):
+        r"""
+        For advanced usage: set the grad attribute to None for registered parameters.
+        It could be more convenient when there is more than one Optimizer.
+        """
+        for param in self._param_dict.values():
+            param.grad = None
+
     def _register_after_backward_callback(self, callback):
         self._after_backward_callback.append(callback)
         return self
diff --git a/imperative/python/megengine/optimizer/optimizer.py b/imperative/python/megengine/optimizer/optimizer.py
index cf869cdf..fc9ebf0b 100644
--- a/imperative/python/megengine/optimizer/optimizer.py
+++ b/imperative/python/megengine/optimizer/optimizer.py
@@ -91,7 +91,7 @@ class Optimizer(metaclass=ABCMeta):
             if not isinstance(param, Parameter):
                 raise TypeError(
                     "optimizer can only optimize Parameters, but one of the params is "
-                    + type(param)
+                    + str(type(param))
                 )
 
         for name, default in self._defaults.items():
@@ -159,7 +159,6 @@ class Optimizer(metaclass=ABCMeta):
 
     def clear_grad(self):
         r"""Set the grad attribute to None for all parameters.
-
         """
         for param_group in self.param_groups:
             for param in param_group["params"]:
diff --git a/imperative/python/test/unit/autodiff/test_grad_manger.py b/imperative/python/test/unit/autodiff/test_grad_manger.py
index 372b3816..f54bd02a 100644
--- a/imperative/python/test/unit/autodiff/test_grad_manger.py
+++ b/imperative/python/test/unit/autodiff/test_grad_manger.py
@@ -29,8 +29,7 @@ def test_basic():
     np.testing.assert_equal(w.grad.numpy(), [[1], [3], [5]])
     np.testing.assert_equal(b.grad.numpy(), [1])
 
-    w.grad = None
-    b.grad = None
+    gm.clear_grad()
     with gm:
         p = F.matmul(x, w)
         y = p + b