code: def test_ner_standalone():
      requests_gag = mock.patch(
          "requests.Session.request",
          mock.Mock(
              side_effect=RuntimeError(
                  "Please use the `responses` library to mock HTTP in your tests."
              )
          ),
      )
      train_data = get_data()
      label_col = "entity_annotations"
      test_data = train_data.drop(label_col, axis=1)
  
      predictor = MultiModalPredictor(
          problem_type="ner", label=label_col
      )
  
      save_path = os.path.join(get_home_dir(), "standalone", "false")
      if os.path.exists(save_path):
          shutil.rmtree(save_path)
  
      predictor.fit(
          train_data=train_data,
          time_limit=40,
          hyperparameters={
              "model.ner_text.checkpoint_name": "google/electra-small-discriminator"
          },
          save_path=save_path,
      )
      save_path_standalone = os.path.join(
          get_home_dir(), "standalone", "true"
      )
  
      predictor.save(
          path=save_path_standalone,
          standalone=True,
      )
  
      del predictor
      torch.cuda.empty_cache()
  
      loaded_online_predictor = MultiModalPredictor.load(path=save_path)
      online_predictions = loaded_online_predictor.predict(
          test_data, as_pandas=False
      )
      del loaded_online_predictor
  
      with requests_gag:
          # No internet connection here. If any command require internet connection, a RuntimeError will be raised!
          with tempfile.TemporaryDirectory() as tmpdirname:
              torch.hub.set_dir(
                  tmpdirname
              )  # block reading files in `.cache`.
              loaded_offline_predictor = MultiModalPredictor.load(
                  path=save_path_standalone
              )
  
      offline_predictions = loaded_offline_predictor.predict(
          test_data, as_pandas=False
      )
      del loaded_offline_predictor
      npt.assert_equal(online_predictions[0], offline_predictions[0])
  
file_path: autogluon/multimodal/tests/unittests/others/test_ner.py
imports: import os
  import shutil
  import tempfile
  from unittest import mock
  import numpy.testing
  import pandas
  import pytest
  import torch
  from ray import tune
  from autogluon.multimodal import MultiModalPredictor
  from ..utils.utils import get_home_dir
label_desc: Use image node_id 4 for calling a global function with example usage: test_ner_standalone() without return types