diff --git a/mindspore/ccsrc/frontend/optimizer/irpass/parameter_eliminate.h b/mindspore/ccsrc/frontend/optimizer/irpass/parameter_eliminate.h
index 01e417a1610..55d9a22e0eb 100644
--- a/mindspore/ccsrc/frontend/optimizer/irpass/parameter_eliminate.h
+++ b/mindspore/ccsrc/frontend/optimizer/irpass/parameter_eliminate.h
@@ -138,6 +138,7 @@ class ParameterEliminator {
     }
     TraceGuard trace_guard(std::make_shared<TraceCopy>(caller->debug_info()));
     auto new_caller = caller->func_graph()->NewCNode(new_args);
+    new_caller->set_abstract(caller->abstract());
     tr->Replace(caller, new_caller);
   }
 };
diff --git a/tests/ut/python/ops/test_control_ops.py b/tests/ut/python/ops/test_control_ops.py
index 880698e4980..5d1ecbae560 100644
--- a/tests/ut/python/ops/test_control_ops.py
+++ b/tests/ut/python/ops/test_control_ops.py
@@ -750,6 +750,23 @@ def test_while_scalar():
     out = net(x, y)
 
 
+def test_while_with_weight_in_condition():
+    class Net(nn.Cell):
+        def __init__(self):
+            super(Net, self).__init__()
+            self.loop = Parameter(Tensor(1, dtype=ms.float32), name="loop")
+
+        def construct(self, x):
+            while self.loop < 5:
+                self.loop += 1
+                x += 1
+            return x
+
+    net = Net()
+    x = Tensor(-1, dtype=ms.float32)
+    grad_all(net)(x)
+
+
 def test_mixed_precision_cast():
     x = Tensor(np.ones([2, 3], dtype=np.float32))
     z = F.mixed_precision_cast(mstype.float16, x)