code: def test_continuous_training_save_path():
      save_path = "a_tmp_path"
      abs_path = os.path.abspath(os.path.expanduser(save_path))
      if os.path.exists(abs_path):
          shutil.rmtree(abs_path)
  
      dataset = PetFinderDataset()
      predictor = MultiModalPredictor(
          label=dataset.label_columns[0],
          problem_type=dataset.problem_type,
          eval_metric=dataset.metric,
      )
  
      hyperparameters = {
          "env.num_workers": 0,
          "env.num_workers_evaluation": 0,
          "model.names": ["timm_image", "hf_text", "fusion_mlp"],
          "model.hf_text.checkpoint_name": "nlpaueb/legal-bert-small-uncased",
          "model.timm_image.checkpoint_name": "swin_tiny_patch4_window7_224",
      }
      predictor.fit(
          train_data=dataset.train_df,
          save_path=save_path,
          hyperparameters=hyperparameters,
          time_limit=10,
      )
  
      assert predictor.path == abs_path
  
      with pytest.raises(ValueError):
          predictor.fit(
              train_data=dataset.train_df,
              save_path=save_path,
              time_limit=10,
          )
  
      # continue training
      predictor.fit(train_data=dataset.train_df, time_limit=10)
      assert (
          predictor.path != abs_path
          and os.path.join("AutogluonModels", "ag-") in predictor.path
      )
  
      # load a saved predictor and continue training
      predictor_loaded = MultiModalPredictor.load(save_path)
      predictor_loaded.fit(train_data=dataset.train_df, time_limit=10)
      assert (
          predictor_loaded.path != abs_path
          and os.path.join("AutogluonModels", "ag-") in predictor.path
      )
  
file_path: autogluon/multimodal/tests/unittests/others/test_save_path.py
imports: import os
  import shutil
  import pytest
  from autogluon.multimodal import MultiModalPredictor
  from ..utils.unittest_datasets import PetFinderDataset
label_desc: Use image node_id 3 for calling a global function with example usage: test_continuous_training_save_path() without return types