code: def test_xgb_classifier_converter_tvm(self):
      warnings.filterwarnings("ignore")
      import torch
  
      for max_depth in [1, 3, 8, 10, 12]:
          model = xgb.XGBClassifier(
              n_estimators=10, max_depth=max_depth
          )
          np.random.seed(0)
          X = np.random.rand(100, 200)
          X = np.array(X, dtype=np.float32)
          y = np.random.randint(2, size=100)
  
          model.fit(X, y)
  
          tvm_model = hummingbird.ml.convert(
              model,
              "tvm",
              X,
              extra_config={constants.TVM_MAX_FUSE_DEPTH: 30},
          )
          self.assertIsNotNone(tvm_model)
          np.testing.assert_allclose(
              model.predict_proba(X),
              tvm_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 29 for calling the TestXGBoostConverter obj's underlying member method code with example usage: obj.test_xgb_classifier_converter_tvm() without return types