code: def test_lightgbm_booster_classifier(self):
      warnings.filterwarnings("ignore")
      X = [[0, 1], [1, 1], [2, 0], [1, 2]]
      X = np.array(X, dtype=np.float32)
      y = [0, 1, 0, 1]
      data = lgb.Dataset(X, label=y)
      model = lgb.train(
          {
              "boosting_type": "gbdt",
              "objective": "binary",
              "n_estimators": 3,
              "min_child_samples": 1,
          },
          data,
      )
      self._test_classifier(X, model)
  
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 15 for calling the TestONNXLightGBMConverter obj's underlying member method code with example usage: obj.test_lightgbm_booster_classifier() without return types