code: def test_model_one_hot_encoder_ts_int(self):
      model = OneHotEncoder()
      data = np.array(
          [[1, 2, 3], [4, 3, 0], [0, 1, 4], [0, 5, 6]], dtype=np.int64
      )
      model.fit(data)
  
      pytorch_model = hummingbird.ml.convert(
          model, "torchscript", np.array([[4, 3, 1]], dtype=np.int64)
      )
  
      self.assertIsNotNone(pytorch_model)
      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 5 for calling the TestSklearnOneHotEncoderConverter obj's underlying member method code with example usage: obj.test_model_one_hot_encoder_ts_int() without return types