code: def test_binarizer_converter(self):
      data = np.array(
          [[1, 2, -3], [4, -3, 0], [0, 1, 4], [0, -5, 6]],
          dtype=np.float32,
      )
      data_tensor = torch.from_numpy(data)
  
      for threshold in [0.0, 1.0, -2.0]:
          model = Binarizer(threshold=threshold)
          model.fit(data)
  
          torch_model = hummingbird.ml.convert(model, "torch")
          self.assertIsNotNone(torch_model)
          np.testing.assert_allclose(
              model.transform(data),
              torch_model.transform(data_tensor),
              rtol=1e-06,
              atol=1e-06,
          )
  
file_path: hummingbird/tests/test_sklearn_discretizer_converters.py
imports: import unittest
  import warnings
  import numpy
  import torch
  from sklearn.preprocessing import Binarizer, KBinsDiscretizer
  from sklearn.datasets import load_breast_cancer
  import hummingbird.ml
label_desc: Use image node_id 1 for calling the TestSklearnDiscretizers obj's underlying member method code with example usage: obj.test_binarizer_converter() without return types