class_docstr: Dump proposals pseudo metric.
  
  Args:
      output_dir (str): The root directory for ``proposals_file``.
          Defaults to ''.
      proposals_file (str): Proposals file path. Defaults to 'proposals.pkl'.
      num_max_proposals (int, optional): Maximum number of proposals to dump.
          If not specified, all proposals will be dumped.
      file_client_args (dict, optional): Arguments to instantiate the
          corresponding backend in mmdet <= 3.0.0rc6. Defaults to None.
      backend_args (dict, optional): Arguments to instantiate the
          corresponding backend. Defaults to None.
      collect_device (str): Device name used for collecting results from
          different ranks during distributed training. Must be 'cpu' or
          'gpu'. Defaults to 'cpu'.
      prefix (str, optional): The prefix that will be added in the metric
          names to disambiguate homonymous metrics of different evaluators.
          If prefix is not provided in the argument, self.default_prefix
          will be used instead. Defaults to None.
docstr: Dump the processed results.
  
  Args:
      results (list): The processed results of each batch.
  
  Returns:
      dict: An empty dict.
docstr_tok: ["Dump","the","processed","results",".","Args",":","results","(","list",")",":","The","processed","results","of","each","batch",".","Returns",":","dict",":","An","empty","dict","."]
code: def compute_metrics(self, results: list) -> dict:
      """Dump the processed results.
  
      Args:
          results (list): The processed results of each batch.
  
      Returns:
          dict: An empty dict.
      """
      logger: MMLogger = MMLogger.get_current_instance()
      dump_results = {}
      for result in results:
          dump_results.update(result)
      dump(
          dump_results,
          file=self.proposals_file,
          backend_args=self.backend_args,
      )
      logger.info(f"Results are saved at {self.proposals_file}")
      return {}
  
file_path: mmdetection/mmdet/evaluation/metrics/dump_proposals_metric.py
imports: import os
  import os.path
  from typing import Optional, Sequence
  from mmengine.dist import is_main_process
  from mmengine.evaluator import BaseMetric
  from mmengine.fileio import dump
  from mmengine.logging import MMLogger
  from mmengine.structures import InstanceData
  from mmdet.registry import METRICS
label_desc: Use image node_id 3 for calling the DumpProposals obj's underlying member method code with example usage: obj.compute_metrics(results) and returns: dict