diff --git a/tests/test_optimizers.py b/tests/test_optimizers.py
index 61ebc63a9..7ab159d0e 100644
--- a/tests/test_optimizers.py
+++ b/tests/test_optimizers.py
@@ -116,6 +116,52 @@ def test_transpose_with_concat(self, input_shape, perm, inner_perm):
                          }
             self.run_transpose_compare(["res"], feed_dict, model_proto, remaining_transpose_num=1)
 
+    @parameterized.expand([
+        ((2, 3, 4, 5), [0, 3, 1, 2], [0, 2, 3, 1]),
+        ((2, 3, 4, 5, 6), [0, 4, 1, 2, 3], [0, 2, 3, 4, 1]),
+        ((2, 3, 4, 5, 6), [0, 2, 3, 4, 1], [0, 4, 1, 2, 3]),
+    ])
+    def test_transpose_with_split(self, input_shape, perm, inner_perm):
+        input_shape_with_trans = [input_shape[i] for i in perm]
+        output_before_trans = list(input_shape)
+        output_shape = [output_before_trans[i] for i in perm]
+        for axis in range(len(input_shape)):
+            node1 = helper.make_node("Transpose", ["X"], ["Y"], perm=inner_perm, name="trans1")
+            node2 = helper.make_node("Split", ["Y"], ["Z"], axis=axis, name="split")
+            node3 = helper.make_node("Transpose", ["Z"], ["res"], perm=perm, name="trans2")
+
+            graph = helper.make_graph(
+                [node1, node2, node3],
+                "test_transpose_with_split",
+                [helper.make_tensor_value_info("X", TensorProto.FLOAT, input_shape_with_trans)],
+                [helper.make_tensor_value_info("res", TensorProto.FLOAT, output_shape)],
+            )
+
+            model_proto = self.make_model(graph, producer_name="onnx-tests")
+            feed_dict = {"X": np.random.randn(*input_shape_with_trans).astype(np.float32)}
+            self.run_transpose_compare(["res"], feed_dict, model_proto, remaining_transpose_num=0)
+
+    @parameterized.expand([
+        ((1, -1), (1, 1710), (1710,), [1, 0]),
+        ((3, 1, 1, 5, -1), (3, 1, 1, 5, 6), (3, 5, 6), [0, 2, 3, 4, 1]),
+    ])
+    @check_opset_max_version(12, "split attribute changed to input in opset 13")
+    def test_transpose_with_split_dynamic_shape(self, input_shape, specific_input, output_shape, perm):
+        node1 = helper.make_node("Transpose", ["X"], ["Y"], perm=perm, name="trans")
+        node2 = helper.make_node("Split", ["Y"], ["Z"], axis=1, split=[1], name="split")
+        node3 = helper.make_node("Squeeze", ["Z"], ["B"], name="squeeze")
+
+        graph = helper.make_graph(
+            [node1, node2, node3],
+            "test_transpose_with_split_dynamic_shape",
+            [helper.make_tensor_value_info("X", TensorProto.FLOAT, input_shape)],
+            [helper.make_tensor_value_info("B", TensorProto.FLOAT, output_shape)],
+        )
+
+        model_proto = self.make_model(graph, producer_name="onnx-tests")
+        self.run_transpose_compare(["B"], {"X": np.random.randn(*specific_input).astype(np.float32)},
+                                   model_proto, remaining_transpose_num=0)
+
     @parameterized.expand([
         ((2, 3, 4), [2, 0, 1], [1, 2, 0]),
         ((2, 3, 4, 5), [0, 2, 3, 1], [0, 3, 1, 2]),