code: def convert_to_onnx_object(model, export_parameters=None, **kwargs):
      """
      Convert given CatBoost model to ONNX-ML model.
      Categorical Features are not supported.
  
      Parameters
      ----------
      model : CatBoost trained model
      export_parameters : dict [default=None]
          Parameters for ONNX-ML export:
              * onnx_graph_name : string
                  The name property of onnx Graph
              * onnx_domain : string
                  The domain component of onnx Model
              * onnx_model_version : int
                  The model_version component of onnx Model
              * onnx_doc_string : string
                  The doc_string component of onnx Model
      Returns
      -------
      onnx_object : ModelProto
          The model in ONNX format
      """
      try:
          import onnx
      except ImportError as e:
          warnings.warn(
              "To get working onnx model you should install onnx."
          )
          raise ImportError(str(e))
  
      import json
  
      if not model.is_fitted():
          raise CatBoostError(
              "There is no trained model to use save_model(). Use fit() to train model. Then use this method."
          )
  
      for name, value in kwargs.items():
          if name == "target_opset" and value not in [None, 2]:
              warnings.warn(
                  "target_opset argument is not supported. Default target_opset is 2 (ai.onnx.ml domain)"
              )
          elif name == "initial_types" and value is not None:
              warnings.warn("initial_types argument is not supported")
  
      params_string = ""
      if export_parameters:
          params_string = json.dumps(
              export_parameters, cls=_NumpyAwareEncoder
          )
  
      model_str = _get_onnx_model(model._object, params_string)
      onnx_model = onnx.load_model_from_string(model_str)
      return onnx_model
  
imports: from .None import _catboost
  from .core import Pool, CatBoostError, ARRAY_TYPES, PATH_TYPES, fspath, _update_params_quantize_part, _process_synonyms
  from collections import defaultdict
  from contextlib import contextmanager
  import sys
  import numpy
  import warnings
label_desc: Use image node_id 14 for calling a global function with example usage: convert_to_onnx_object(model, export_parameters) and returns: onnx_model