class_docstr: Reporter implementations write reports about trained models. They should at least produce human readable reports,
  but can additionally produce reports that are easily machine-parsable.
docstr: do a global reporting for multiple experiment configurations
  :param aggregate_reports: the result of report() on each experiment config.
  :param report_dir: the directory in which to write the report
  :return: a global reporting of the key metric values along different configurations.
docstr_tok: ["do","a","global","reporting","for","multiple","experiment","configurations",":","param","aggregate_reports",":","the","result","of","report","(",")","on","each","experiment","config",".",":","param","report_dir",":","the","directory","in","which","to","write","the","report",":","return",":","a","global","reporting","of","the","key","metric","values","along","different","configurations","."]
code: def report_globally(aggregate_reports: Dict, report_dir: Path) -> Any:
      """
      do a global reporting for multiple experiment configurations
      :param aggregate_reports: the result of report() on each experiment config.
      :param report_dir: the directory in which to write the report
      :return: a global reporting of the key metric values along different configurations.
      """
      pass
  
imports: from abc import ABC
  from pathlib import Path
  from typing import Any, Dict
  from transfer_nlp.plugins.config import ExperimentConfig
label_desc: Use image node_id 2 for calling the ReporterABC obj's underlying member method code with example usage: obj.report_globally(aggregate_reports, report_dir) without return types