code: def test_matcher_hyperparameters_consistency(hyperparameters):
      dataset = IDChangeDetectionDataset()
  
      # pass hyperparameters to init()
      predictor = MultiModalPredictor(
          query="Previous Image",
          response="Current Image",
          problem_type="image_similarity",
          label=dataset.label_columns[0]
          if dataset.label_columns
          else None,
          match_label=dataset.match_label,
          eval_metric=dataset.metric,
          hyperparameters=hyperparameters,
      )
      predictor.fit(dataset.train_df, time_limit=10)
  
      # pass hyperparameters to fit()
      predictor_2 = MultiModalPredictor(
          query="Previous Image",
          response="Current Image",
          problem_type="image_similarity",
          label=dataset.label_columns[0]
          if dataset.label_columns
          else None,
          match_label=dataset.match_label,
          eval_metric=dataset.metric,
      )
      predictor_2.fit(
          dataset.train_df,
          hyperparameters=hyperparameters,
          time_limit=10,
      )
      assert predictor._learner._config == predictor_2._learner._config
  
file_path: autogluon/multimodal/tests/unittests/others/test_matcher.py
imports: import copy
  import os
  import pickle
  import shutil
  import tempfile
  import numpy.testing
  import pytest
  from autogluon.multimodal import MultiModalPredictor
  from autogluon.multimodal.constants import BINARY, MULTICLASS, QUERY, RESPONSE, UNIFORM_SOUP
  from autogluon.multimodal.utils import convert_data_for_ranking, semantic_search
  from ..utils.unittest_datasets import Flickr30kDataset, IDChangeDetectionDataset
  from ..utils.utils import get_home_dir
label_desc: Use image node_id 8 for calling a global function with example usage: test_matcher_hyperparameters_consistency(hyperparameters) without return types