code: def test_hyperparameters_in_terminal_format():
      download_dir = "./"
      train_df, tune_df = shopee_dataset(download_dir=download_dir)
      predictor = MultiModalPredictor(label="label")
      hyperparameters = [
          "model.names=[timm_image]",
          "model.timm_image.checkpoint_name=ghostnet_100",
          "env.num_workers=0",
          "env.num_workers_evaluation=0",
          "optimization.top_k_average_method=best",
          "optimization.val_check_interval=1.0",
      ]
      predictor.fit(
          train_data=train_df,
          tuning_data=tune_df,
          hyperparameters=hyperparameters,
          time_limit=2,
      )
  
file_path: autogluon/multimodal/tests/unittests/others_2/test_predictor_advanced.py
imports: import os
  import shutil
  import numpy.testing
  import pytest
  from datasets import load_dataset
  from autogluon.multimodal import MultiModalPredictor
  from autogluon.multimodal.constants import BIT_FIT, IA3, IA3_BIAS, IA3_LORA, LORA_BIAS, LORA_NORM, NORM_FIT
  from autogluon.multimodal.models.timm_image import TimmAutoModelForImagePrediction
  from autogluon.multimodal.utils.misc import shopee_dataset
  from ..utils.unittest_datasets import AmazonReviewSentimentCrossLingualDataset
label_desc: Use image node_id 3 for calling a global function with example usage: test_hyperparameters_in_terminal_format() without return types