diff --git a/nnvm/python/nnvm/to_relay.py b/nnvm/python/nnvm/to_relay.py
index 2a7b27877b686..3c75dc5a3fb98 100644
--- a/nnvm/python/nnvm/to_relay.py
+++ b/nnvm/python/nnvm/to_relay.py
@@ -480,6 +480,7 @@ def to_relay(graph, shape_dict, dtype_dict, params):
                     "nnvm.to_relay: unsupported operator: {0}".format(op_name))
 
     outputs = [relay_map[nid] for nid in output_ids]
+    outputs = [x if not isinstance(x, expr.TupleWrapper) else x.astuple() for x in outputs]
     if len(outputs) == 1:
         body = outputs[0]
     else:
diff --git a/nnvm/tests/python/compiler/test_to_relay.py b/nnvm/tests/python/compiler/test_to_relay.py
index 25037cfd3587e..200c13aebf23c 100644
--- a/nnvm/tests/python/compiler/test_to_relay.py
+++ b/nnvm/tests/python/compiler/test_to_relay.py
@@ -31,6 +31,23 @@ def check_model(sym, shapes, dtypes, params):
     relay_out = relay_rts.evaluate(relay_model)(*list(inputs.values()))
     np.testing.assert_allclose(nnvm_out.asnumpy(), relay_out.asnumpy())
 
+
+def test_split_concatenate():
+    shape = (2, 16)
+
+    tensor = nnvm.sym.Variable("tensor", shape=shape)
+
+    splited = nnvm.sym.split(tensor, indices_or_sections=2, axis=1)
+
+    concatenated = nnvm.sym.concatenate(*splited, axis=1)
+
+    shapes = {"tensor": shape}
+    dtypes = {"tensor": 'float32'}
+    params = {}
+
+    check_model(concatenated, shapes, dtypes, params)
+
+
 # def test_mlp():
 #     mlp, params = testing.mlp.get_workload(1)
 #     shapes =  { "data": (10, 3, 224, 224) }