code: def test_model_one_hot_encoder_string_not_mod4_len(self):
      model = OneHotEncoder()
      data = [
          ["a", "r", "x"],
          ["a", "r", "x"],
          ["aaaaa", "r", "x"],
          ["a", "r", "xx"],
      ]
      model.fit(data)
  
      pytorch_model = hummingbird.ml.convert(model, "pytorch")
      self.assertTrue(pytorch_model is not None)
  
      np.testing.assert_allclose(
          model.transform(data).todense(),
          pytorch_model.transform(data),
          rtol=1e-06,
          atol=1e-06,
      )
  
file_path: hummingbird/tests/test_sklearn_one_hot_encoder_converter.py
imports: import unittest
  import numpy
  import torch
  from sklearn.preprocessing import OneHotEncoder
  import hummingbird.ml
label_desc: Use image node_id 4 for calling the TestSklearnOneHotEncoderConverter obj's underlying member method code with example usage: obj.test_model_one_hot_encoder_string_not_mod4_len() without return types