code: def test_iforest_implementation(self):
      warnings.filterwarnings("ignore")
      np.random.seed(0)
      X = np.random.rand(10, 1)
      X = np.array(X, dtype=np.float32)
      model = IsolationForest(n_estimators=1, max_samples=2)
      for extra_config_param in ["tree_trav", "perf_tree_trav", "gemm"]:
          model.fit(X)
          torch_model = hummingbird.ml.convert(
              model,
              "torch",
              extra_config={"tree_implementation": extra_config_param},
          )
          self.assertIsNotNone(torch_model)
          self.assertEqual(
              str(type(list(torch_model.model._operators)[0])),
              iforest_implementation_map[extra_config_param],
          )
  
imports: import unittest
  import warnings
  import numpy
  import torch
  from sklearn.ensemble import IsolationForest
  import hummingbird.ml
  from hummingbird.ml import constants
  from hummingbird.ml._utils import onnx_runtime_installed, tvm_installed
  from tree_utils import iforest_implementation_map
label_desc: Use image node_id 1 for calling the TestIsolationForestConverter obj's underlying member method code with example usage: obj.test_iforest_implementation() without return types