code: def _convert_decision_tree(self, X, model, extra_config={}):
      onnx_ml_model, _ = convert_model(
          model,
          "model",
          input_types=[("input", FloatTensorType([None, X.shape[1]]))],
          target_opset=11,
      )
  
      onnx_model = convert(onnx_ml_model, "onnx", X, extra_config)
      return onnx_ml_model, onnx_model
  
imports: import unittest
  import warnings
  import numpy
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
  from onnxconverter_common.data_types import FloatTensorType
  from hummingbird.ml import convert
  from hummingbird.ml._utils import onnx_ml_tools_installed, onnx_runtime_installed, xgboost_installed
label_desc: Use image node_id 2 for calling the TestONNXDecisionTreeConverter obj's underlying member method code with example usage: obj._convert_decision_tree(X, model, extra_config) and returns: onnx_ml_model,  onnx_model