code: def test_isolation_forest_onnx_converter(self):
      warnings.filterwarnings("ignore")
      for max_samples in [2**1, 2**3, 2**8, 2**10, 2**12]:
          model = IsolationForest(
              n_estimators=10, max_samples=max_samples
          )
          np.random.seed(0)
          X = np.random.rand(100, 200)
          X = np.array(X, dtype=np.float32)
          model.fit(X)
          onnx_model = hummingbird.ml.convert(
              model, "onnx", X, extra_config={}
          )
          self.assertIsNotNone(onnx_model)
          np.testing.assert_allclose(
              model.decision_function(X),
              onnx_model.decision_function(X),
              rtol=1e-06,
              atol=1e-06,
          )
          np.testing.assert_allclose(
              model.score_samples(X),
              onnx_model.score_samples(X),
              rtol=1e-06,
              atol=1e-06,
          )
          np.testing.assert_array_equal(
              model.predict(X), onnx_model.predict(X)
          )
  
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 9 for calling the TestIsolationForestConverter obj's underlying member method code with example usage: obj.test_isolation_forest_onnx_converter() without return types