code: def test_regressor_args():
      # load and parse external data file
      data_file = os.path.join(
          os.path.dirname(os.path.realpath(__file__)),
          "resources",
          "train.dat",
      )
      model = Workspace(
          oaa=3, data=data_file, passes=30, c=True, k=True
      )
      assert model.predict("| feature1:2.5") == 1
  
      # update model in memory
      for _ in range(10):
          model.learn("3 | feature1:2.5")
      assert model.predict("| feature1:2.5") == 3
  
      # save model
      model.save("tmp.model")
      del model
  
      # load initial regressor and confirm updated prediction
      new_model = Workspace(i="tmp.model", quiet=True)
      assert new_model.predict("| feature1:2.5") == 3
      del new_model
  
      # clean up
      os.remove("{}.cache".format(data_file))
      os.remove("tmp.model")
  
imports: import os
  from pathlib import Path
  import vowpalwabbit
  from vowpalwabbit import Workspace
  import pytest
  import warnings
  import filecmp
label_desc: Use image node_id 18 for calling a global function with example usage: test_regressor_args() without return types