diff --git a/test/spmd/test_xla_sharding.py b/test/spmd/test_xla_sharding.py
index 46e12e383be..6fccfe32800 100644
--- a/test/spmd/test_xla_sharding.py
+++ b/test/spmd/test_xla_sharding.py
@@ -714,7 +714,7 @@ def test_xla_sharded_hlo_dump(self):
                             partition_spec)
     xst2 = xst1 + 5
     hlo = torch_xla._XLAC._get_xla_tensors_hlo([xst2.global_tensor])
-    self.assertIn('%p1.4 = f32[1,8]{1,0} parameter(1), sharding', hlo)
+    self.assertIn('%p1.3 = f32[1,8]{1,0} parameter(1), sharding', hlo)
     # scalar 5 should be implicitly replicated, so the pre-optimization HLO
     # shouldn't mark it with sharding.
     self.assertNotIn('%p0.2 = f32[] parameter(0), sharding={replicated}', hlo)