code: def report(
      self, name: str, experiment: ExperimentConfig, report_dir: Path
  ):
      with open(report_dir / "metrics_report.txt", "w") as reporting:
          reporting.write(f"Metrics reporting for experiment {name}\n")
          reporting.write("#" * 50 + "\n")
  
          for mode, metrics in experiment[
              "trainer"
          ].metrics_history.items():
              reporting.write(f"Reporting metrics in {mode} mode\n")
              for metric, values in metrics.items():
                  reporting.write(
                      f"{metric}: [{', '.join([str(value) for value in values])}]\n"
                  )
  
file_path: transfer-nlp/experiments/deep_learning_with_pytorch/mlp_parameter_tuning.py
imports: from datetime import datetime
  from pathlib import Path
  from smart_open import open
  from experiments.deep_learning_with_pytorch.surnames import *
  from transfer_nlp.plugins.config import register_plugin, ExperimentConfig
  from transfer_nlp.plugins.reporters import ReporterABC
  from transfer_nlp.runner.experiment_runner import ExperimentRunner
label_desc: Use image node_id 2 for calling the MyReporter obj's underlying member method code with example usage: obj.report(name, experiment, report_dir) without return types