code: def main():
      with open(TEST) as f:
          results = json.load(f)
  
      test_private_path = "jigsaw_data/jigsaw-unintended-bias-in-toxicity-classification/test_private_expanded.csv"
      test_private = pd.read_csv(test_private_path)
      test_private = convert_dataframe_to_bool(test_private)
  
      test_private[MODEL_NAME] = [s[0] for s in results["scores"]]
  
      bias_metrics_df = compute_bias_metrics_for_model(
          test_private, IDENTITY_COLUMNS, MODEL_NAME, TOXICITY_COLUMN
      )
      print(bias_metrics_df)
  
      final_metric = get_final_metric(
          bias_metrics_df,
          calculate_overall_auc(test_private, MODEL_NAME),
      )
      print(final_metric)
  
file_path: detoxify/model_eval/compute_bias_metric.py
imports: import argparse
  import json
  import numpy
  import pandas
  from sklearn.metrics import roc_auc_score
  from utils import compute_auc, compute_subgroup_auc
label_desc: Use image node_id 9 for calling a global function with example usage: main() without return types