class_docstr: Igel is the base model to use the fit, evaluate and predict functions of the sklearn library
class_docstr_tok: ["Igel","is","the","base","model","to","use","the","fit",",","evaluate","and","predict","functions","of","the","sklearn","library"]
docstr: export a sklearn model to ONNX. This is used as a command from cli
  @return: None
docstr_tok: ["export","a","sklearn","model","to","ONNX",".","This","is","used","as","a","command","from","cli","@","return",":","None"]
code: def export(self):
      """
      export a sklearn model to ONNX. This is used as a command from cli
      @return: None
      """
      try:
          logger.info(
              f"Trying to load sklearn model from directory - {self.model_path} "
          )
          model = self._load_model(f=self.model_path)
          initial_type = [("float_input", FloatTensorType([None, 4]))]
          onx = convert_sklearn(model, initial_types=initial_type)
  
          # check if model_results folder is present and create if absent
          if not os.path.exists(self.results_path):
              logger.info(
                  f"creating model_results folder to save results...\n"
                  f"path of the results folder: {self.results_path}"
              )
              os.mkdir(self.results_path)
          else:
              logger.info(f"Folder {self.results_path} already exists")
              logger.warning(
                  f"data in the {self.results_path} folder will be overridden. If you don't "
                  f"want this, then move the current {self.results_path} to another path"
              )
  
          with open(self.default_onnx_model_path, "wb") as f:
              f.write(onx.SerializeToString())
          logger.info(
              f"Successfully saved exported onnx model at - {self.default_onnx_model_path} "
          )
      except Exception as e:
          logger.exception(f"Error while exporting model: {e}")
  
imports: import json
  import logging
  import os
  import warnings
  import joblib
  import numpy
  import pandas
  from sklearn.model_selection import cross_validate, train_test_split
  from sklearn.multioutput import MultiOutputClassifier, MultiOutputRegressor
  from skl2onnx import convert_sklearn
  from skl2onnx.common.data_types import FloatTensorType
label_desc: Use image node_id 15 for calling the Igel obj's underlying member method code with example usage: obj.export() without return types