code: def test_label_encoder_int_string(self):
      X = make_tensor_value_info("X", TensorProto.INT64, [None, None])
      Y = make_tensor_value_info("Y", TensorProto.STRING, [None, None])
      node1 = make_node(
          "LabelEncoder",
          ["X"],
          ["Y"],
          domain="ai.onnx.ml",
          default_string="NONE",
          keys_int64s=[1, 2, 3, 4],
          values_strings=["a", "b", "cc", "ddd"],
      )
      graph = make_graph([node1], "ml", [X], [Y])
      onx = make_model_gen_version(graph, opset_imports=OPSETS)
      check_model(onx)
      x = np.array([[0, 1, 3, 4]], dtype=np.int64).T
      expected = np.array([["NONE"], ["a"], ["cc"], ["ddd"]])
      self._check_ort(onx, {"X": x}, equal=True)
      sess = ReferenceEvaluator(onx)
      got = sess.run(None, {"X": x})[0]
      self.assertEqual(expected.tolist(), got.tolist())
  
imports: import unittest
  from functools import wraps
  from os import getenv
  import numpy
  from numpy.testing import assert_allclose
  from parameterized import parameterized
  from onnx import ONNX_ML, TensorProto, TypeProto, ValueInfoProto
  from onnx.checker import check_model
  from onnx.defs import onnx_opset_version
  from onnx.helper import make_graph, make_model_gen_version, make_node, make_opsetid, make_tensor, make_tensor_value_info
  from onnx.reference import ReferenceEvaluator
label_desc: Use image node_id 11 for calling the TestReferenceEvaluatorAiOnnxMl obj's underlying member method code with example usage: obj.test_label_encoder_int_string() without return types