code: def _run_GB_trees_regressor_converter(self, extra_config={}):
      warnings.filterwarnings("ignore")
      for max_depth in [2, 3, 8, 10, 12, None]:
          model = HistGradientBoostingRegressor(
              max_iter=10, max_depth=max_depth
          )
          np.random.seed(0)
          X = np.random.rand(100, 200).astype(np.float32)
          y = np.random.normal(size=100)
  
          model.fit(X, y)
          torch_model = hummingbird.ml.convert(
              model, "torch", extra_config=extra_config
          )
          self.assertIsNotNone(torch_model)
          np.testing.assert_allclose(
              model.predict(X),
              torch_model.predict(X),
              rtol=1e-06,
              atol=1e-06,
          )
  
imports: import unittest
  import warnings
  import numpy
  import torch
  from sklearn.ensemble._hist_gradient_boosting.gradient_boosting import HistGradientBoostingClassifier, HistGradientBoostingRegressor
  import hummingbird.ml
  from tree_utils import gbdt_implementation_map
label_desc: Use image node_id 2 for calling the TestSklearnHistGradientBoostingClassifier obj's underlying member method code with example usage: obj._run_GB_trees_regressor_converter(extra_config) without return types