code: def local_reporter(folder: str, job_name: str):
      """Returns a reporter implementation that persists metrics on the local
      filesystem in jsonl format.
  
      """
      local_path = fs.path.join(folder, job_name)
      return FSReporter(local_path).stepped()
  
imports: from __future__ import division, print_function
  import getpass
  from typing import Dict, Optional
  import fs
  import tensorflow
  import tensorflow_datasets
  import tqdm
  import uv
  import uv.tensorflow.reporter
  import uv.util
  from absl import app
  from uv.fs.reporter import FSReporter
  from uv.mlflow.reporter import MLFlowReporter
  from trainer import cli
label_desc: Use image node_id 10 for calling a global function with example usage: local_reporter(folder, job_name) and returns: FSReporter