code: def evaluate_matcher_ranking(
      matcher,
      test_df,
      query_column,
      response_column,
      metric_name,
      symmetric=False,
  ):
      (
          test_df_with_label,
          test_query_text_data,
          test_response_image_data,
          test_label_column,
      ) = convert_data_for_ranking(
          data=test_df,
          query_column=query_column,
          response_column=response_column,
      )
      socre_1 = matcher.evaluate(
          data=test_df_with_label,
          query_data=test_query_text_data,
          response_data=test_response_image_data,
          metrics=[metric_name],
          label=test_label_column,
          cutoffs=[1, 5, 10],
      )
  
      if symmetric:
          (
              test_df_with_label,
              test_query_image_data,
              test_response_text_data,
              test_label_column,
          ) = convert_data_for_ranking(
              data=test_df,
              query_column=response_column,
              response_column=query_column,
          )
          socre_2 = matcher.evaluate(
              data=test_df_with_label,
              query_data=test_query_image_data,
              response_data=test_response_text_data,
              metrics=[metric_name],
              label=test_label_column,
              cutoffs=[1, 5, 10],
          )
  
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 3 for calling a global function with example usage: evaluate_matcher_ranking(matcher, test_df, query_column, response_column, metric_name, symmetric) without return types