diff --git a/imperative/python/megengine/core/tensor/megbrain_graph.py b/imperative/python/megengine/core/tensor/megbrain_graph.py
index eaa3d6b2aa17563d00c067a7022cf8f36c1cc602..1bff175b254734107273b33380412a172b4b56f0 100644
--- a/imperative/python/megengine/core/tensor/megbrain_graph.py
+++ b/imperative/python/megengine/core/tensor/megbrain_graph.py
@@ -489,7 +489,7 @@ def apply_backward_varnode(op: BackwardGraph, *args: VarNode):
         graph._make_const_for_backward,
         args,
     )
-    return _unwrap(outputs)
+    return outputs
 
 
 set_cpp_apply_backward_varnode(apply_backward_varnode)
diff --git a/imperative/python/megengine/jit/tracing.py b/imperative/python/megengine/jit/tracing.py
index 203efe0aab2a60f12a215c4052592f3e4e7f034b..c4b70d6cdefd988acd24dc5dbfa15825e58622f8 100644
--- a/imperative/python/megengine/jit/tracing.py
+++ b/imperative/python/megengine/jit/tracing.py
@@ -830,7 +830,10 @@ class trace:
                         name=info.name,
                     )
                 ivars.append(h2v[h])
-            ovars = G.apply_normal_varnode(op, *ivars)
+            if isinstance(op, BackwardGraph):
+                ovars = G.apply_backward_varnode(op, *ivars)
+            else:
+                ovars = G.apply_normal_varnode(op, *ivars)
 
             AutoNaming.record_opnode(ovars[0].op)
 
diff --git a/imperative/python/test/unit/jit/test_tracing.py b/imperative/python/test/unit/jit/test_tracing.py
index 44ac4f044b28cdd1e8361f330ae041130849a4c5..480587a925843212da548b2bf7252ec2af5299bd 100644
--- a/imperative/python/test/unit/jit/test_tracing.py
+++ b/imperative/python/test/unit/jit/test_tracing.py
@@ -247,6 +247,34 @@ def test_dump_volatile():
     )
 
 
+def test_dump_backward_graph():
+    x0 = tensor(np.random.randn(3, 4))
+    x1 = tensor(np.random.randn(3, 4))
+
+    gm = GradManager().attach(x0)
+
+    @trace(symbolic=True, capture_as_const=True)
+    def f(x0, x1):
+        with gm:
+            y = x0 * x1
+            gm.backward(y, F.ones_like(y))
+            dx0 = x0.grad
+        return y, dx0
+
+    y, dx0 = f(x0, x1)
+    np.testing.assert_equal(dx0.numpy(), x1)
+
+    file = io.BytesIO()
+    f.dump(file, optimize_for_inference=False)
+    file.seek(0)
+
+    infer_cg = cgtools.GraphInference(file)
+    results = list((infer_cg.run(x0, x1)).values())
+
+    np.testing.assert_equal(results[0], y)
+    np.testing.assert_equal(results[1], dx0)
+
+
 @pytest.mark.parametrize("trace_mode", [False, True])
 def test_trace_profiler(trace_mode):
     @trace(symbolic=trace_mode, profiling=True)