diff --git a/tests/python/frontend/mxnet/test_forward.py b/tests/python/frontend/mxnet/test_forward.py
index 8a1763266a7d..eee0e95d2505 100644
--- a/tests/python/frontend/mxnet/test_forward.py
+++ b/tests/python/frontend/mxnet/test_forward.py
@@ -1938,7 +1938,17 @@ def verify(data_shape, axis, use_length, length):
 @pytest.mark.parametrize(
     "data_shape, row_sel, col",
     [
-        ((5, 7), (0, 1, 2, 3, 4,), 2),
+        (
+            (5, 7),
+            (
+                0,
+                1,
+                2,
+                3,
+                4,
+            ),
+            2,
+        ),
     ],
 )
 @pytest.mark.parametrize("dtype", ["float64", "float32"])
@@ -1946,12 +1956,16 @@ def verify(data_shape, axis, use_length, length):
 @pytest.mark.parametrize("kind", ["graph", "vm", "debug"])
 def test_forward_npi_advanced_indexing_multiple(data_shape, row_sel, col, dtype, target, ctx, kind):
     data_np = np.random.uniform(size=data_shape).astype(dtype)
-    data = mx.sym.var("data")
     ref_res = mx.np.array(data_np)[row_sel, col]
 
-    # TODO need to add the proper symbol operator
-    mx_sym = mx.sym.np.(data.as_np_ndarray()[row_sel, col])
-    mod, _ = relay.frontend.from_mxnet(mx_sym, shape={"data": data_shape}, dtype=dtype)
+    row_sel_sym = mx.sym.var("row_sel").as_np_ndarray()
+    data_sym = mx.sym.var("data").as_np_ndarray()
+    col_sym = mx.sym.var("col").as_np_ndarray()
+    mx_sym = data_sym[row_sel_sym, col_sym]
+
+    mod, _ = relay.frontend.from_mxnet(
+        mx_sym, shape={"data": data_shape, "row_sel": row_sel, "col": col}, dtype=dtype
+    )
     intrp = relay.create_executor(kind, mod=mod, ctx=ctx, target=target)
     op_res = intrp.evaluate()(data_np)
     tvm.testing.assert_allclose(op_res.asnumpy(), ref_res.asnumpy(), rtol=1e-5)