diff --git a/src/relay/op/tensor/transform.cc b/src/relay/op/tensor/transform.cc
index 4ca875023f912..a0ea8f2e60a36 100644
--- a/src/relay/op/tensor/transform.cc
+++ b/src/relay/op/tensor/transform.cc
@@ -1137,6 +1137,12 @@ bool TileRel(const Array<Type>& types,
   CHECK(reps.defined())
     << "repetition array is not defined. data.ndim = " << ndim;
   const size_t rndim = reps.size();
+  for (size_t i = 0; i < rndim; ++i) {
+    if (const tvm::ir::IntImm* val = reps[i].as<tvm::ir::IntImm>()) {
+      CHECK_GT(val->value, 0)
+          << "Tile reps value should always be larger than 0, but get: " << val->value;
+    }
+  }
   size_t tndim = (ndim > rndim) ? ndim : rndim;
   // re-construct data shape or reps shape
   std::vector<IndexExpr> data_shape;
diff --git a/tests/python/relay/test_op_level3.py b/tests/python/relay/test_op_level3.py
index ec92c0a9a0eb8..1933c97c48b61 100644
--- a/tests/python/relay/test_op_level3.py
+++ b/tests/python/relay/test_op_level3.py
@@ -504,9 +504,9 @@ def verify_tile(dshape, reps):
                 intrp = relay.create_executor(kind, ctx=ctx, target=target)
                 op_res = intrp.evaluate(func)(x_data)
                 tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
-    verify_tile((2, 3, 4), (0, 2, 1))
-    verify_tile((2, 3, 4), (0, 2))
-    verify_tile((2, 3), (0, 2, 1))
+    verify_tile((2, 3, 4), (3, 2, 1))
+    verify_tile((2, 3, 4), (1, 2))
+    verify_tile((2, 3), (3, 2, 1))
 
 def test_repeat():
     def verify_repeat(dshape, repeats, axis):
@@ -525,21 +525,22 @@ def verify_repeat(dshape, repeats, axis):
 
 def test_stack():
     def verify_stack(dshapes, axis):
-        dshapes = np.array(dshapes, dtype="int32")
-        x = relay.var("input_shapes", relay.TensorType(dshapes.shape, "int32"))
+        y = []
+        for shape in dshapes:
+            y.append(relay.var("input", relay.TensorType(shape, "float32")))
+        x = relay.Tuple(y)
         z = relay.stack(x, axis=axis)
 
-        func = relay.Function([x], z)
+        func = relay.Function(y, z)
         x_data = [np.random.normal(size=shape).astype("float32") for shape in dshapes]
         ref_res = np.stack(x_data, axis=axis)
 
         for target, ctx in ctx_list():
             for kind in ["graph", "debug"]:
                 intrp = relay.create_executor(kind, ctx=ctx, target=target)
-                op_res = intrp.evaluate(func)(x_data)
+                op_res = intrp.evaluate(func)(*x_data)
                 tvm.testing.assert_allclose(op_res.asnumpy(), ref_res, rtol=1e-5)
-    verify_stack([[2,], [2,], [2,]], -1)
-    verify_stack([(2,), (2,), (2,)], 1)
+    verify_stack([(2,), (2,), (2,)], -1)
     verify_stack([(2,), (2,), (2,)], 0)
     verify_stack([(2, 2, 4), (2, 2, 4), (2, 2, 4)], 1)
     verify_stack([(2, 2, 3, 4), (2, 2, 3, 4), (2, 2, 3, 4), (2, 2, 3, 4)], -1)
@@ -591,5 +592,5 @@ def verify_reverse(dshape, axis):
     test_arange()
     test_reverse()
     test_stack()
-    test_repeat()
     test_tile()
+    test_repeat()