code: def flush_report(self):
      if not is_main():
          # Empty report in all processes to avoid any leaks
          self.report = []
          return
  
      name = self.current_datamodule.dataset_name
      time_format = "%Y-%m-%dT%H:%M:%S"
      time = self.timer.get_time_hhmmss(None, format=time_format)
  
      filename = name + "_"
  
      if len(self.experiment_name) > 0:
          filename += self.experiment_name + "_"
  
      filename += self.dataset_type + "_"
      filename += time
  
      use_csv_writer = (
          self.config.evaluation.predict_file_format == "csv"
          or self.test_reporter_config.predict_file_format == "csv"
      )
  
      if use_csv_writer:
          filepath = os.path.join(self.report_folder, filename + ".csv")
          self.csv_dump(filepath)
      else:
          filepath = os.path.join(
              self.report_folder, filename + ".json"
          )
          self.json_dump(filepath)
  
      logger.info(
          f"Wrote predictions for {name} to {os.path.abspath(filepath)}"
      )
      self.report = []
  
imports: import csv
  import json
  import logging
  import os
  import warnings
  from dataclasses import dataclass, field
  from typing import List
  import pytorch_lightning
  from mmf.common.registry import registry
  from mmf.common.sample import convert_batch_to_sample_list
  from mmf.utils.configuration import get_mmf_env
  from mmf.utils.distributed import gather_tensor, is_main
  from mmf.utils.file_io import PathManager
  from mmf.utils.general import ckpt_name_from_core_args, foldername_from_config_override
  from mmf.utils.logger import log_class_usage
  from mmf.utils.timer import Timer
  from omegaconf import OmegaConf
  from torch.utils.data import Dataset
label_desc: Use image node_id 4 for calling the TestReporter obj's underlying member method code with example usage: obj.flush_report() without return types