code: def test_lightgbm_classifier_multi(self):
      warnings.filterwarnings("ignore")
      model = lgb.LGBMClassifier(n_estimators=3, min_child_samples=1)
      X = [[0, 1], [1, 1], [2, 0], [0.5, 0.5], [1.1, 1.1], [2.1, 0.1]]
      X = np.array(X, dtype=np.float32)
      y = [0, 1, 2, 1, 1, 2]
      model.fit(X, y)
      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 18 for calling the TestONNXLightGBMConverter obj's underlying member method code with example usage: obj.test_lightgbm_classifier_multi() without return types