code: def test_le_string_raises_rt_onnx(self):
      warnings.filterwarnings("ignore")
      model = LabelEncoder()
      data = [
          "paris",
          "milan",
          "amsterdam",
          "tokyo",
      ]
      model.fit(data)
  
      onnx_ml_model = convert_sklearn(
          model, initial_types=[("input", StringTensorType_onnx([4]))]
      )
  
      # Create ONNX model by calling converter, should raise error for strings
      self.assertRaises(
          RuntimeError, convert, onnx_ml_model, "onnx", data
      )
  
file_path: hummingbird/tests/test_onnxml_label_encoder_converter.py
imports: from packaging.version import Version, parse
  import unittest
  import warnings
  import numpy
  from sklearn.preprocessing import LabelEncoder
  import torch
  from hummingbird.ml._utils import onnx_ml_tools_installed, onnx_runtime_installed, lightgbm_installed
  from hummingbird.ml import convert
label_desc: Use image node_id 3 for calling the TestONNXLabelEncoder obj's underlying member method code with example usage: obj.test_le_string_raises_rt_onnx() without return types