code: def test_run_xgb_classifier_converter(self):
      warnings.filterwarnings("ignore")
      for extra_config_param in ["tree_trav", "perf_tree_trav", "gemm"]:
          model = xgb.XGBClassifier(n_estimators=1, max_depth=1)
          np.random.seed(0)
          X = np.random.rand(1, 1)
          X = np.array(X, dtype=np.float32)
          y = np.array([0], dtype=int)
  
          model.fit(X, y)
  
          torch_model = hummingbird.ml.convert(
              model,
              "torch",
              [],
              extra_config={"tree_implementation": extra_config_param},
          )
          self.assertIsNotNone(torch_model)
          np.testing.assert_allclose(
              model.predict_proba(X),
              torch_model.predict_proba(X),
              rtol=1e-06,
              atol=1e-06,
          )
  
imports: import unittest
  import warnings
  import numpy
  from sklearn.datasets import fetch_california_housing
  from sklearn.model_selection import train_test_split
  import hummingbird.ml
  from hummingbird.ml._utils import xgboost_installed, tvm_installed, pandas_installed
  from hummingbird.ml import constants
  from tree_utils import gbdt_implementation_map
label_desc: Use image node_id 24 for calling the TestXGBoostConverter obj's underlying member method code with example usage: obj.test_run_xgb_classifier_converter() without return types