code: def _test_classifier(
      self, X, model, rtol=1e-06, atol=1e-06, extra_config={}
  ):
      for n in [2, len(X)]:
          onnx_ml_pred, onnx_pred, _ = self._test_lgbm(
              X[:n], model, extra_config
          )
  
          np.testing.assert_allclose(
              onnx_ml_pred[1], onnx_pred[1], rtol=rtol, atol=atol
          )  # labels
          np.testing.assert_allclose(
              list(map(lambda x: list(x.values()), onnx_ml_pred[0])),
              onnx_pred[0],
              rtol=rtol,
              atol=atol,
          )  # probs
  
          np.testing.assert_equal(n, len(onnx_pred[0]))
  
imports: import unittest
  import warnings
  import numpy
  from onnxconverter_common.data_types import FloatTensorType
  from hummingbird.ml import convert
  from hummingbird.ml import constants
  from hummingbird.ml._utils import onnx_ml_tools_installed, onnx_runtime_installed, lightgbm_installed
label_desc: Use image node_id 4 for calling the TestONNXLightGBMConverter obj's underlying member method code with example usage: obj._test_classifier(X, model, rtol, atol, extra_config) without return types