code: def get_eval_metric_values(events, task_name=None):
      """Filter TensorBoard events to only include those for eval metrics.
  
      Args:
        events: dict of list of (step, value) tuples where keys are tags.
        task_name: string, if not provided, then the function will look for the
          task name in the events tags.
      Returns:
        Dict where key is task_name/metric_name and value is (step, value) tuple.
      """
      eval_values = {}
      for tag, event_values in events.items():
          if tag.startswith("eval"):
              if task_name:
                  _, metric_name = tag.split("/")
              else:
                  _, task_name_from_tag, metric_name = tag.split("/")
              eval_task_name = (
                  task_name if task_name else task_name_from_tag
              )
              eval_values[
                  "{}/{}".format(eval_task_name, metric_name)
              ] = event_values
      return eval_values
  
file_path: text-to-text-transfer-transformer/t5/evaluation/eval_utils.py
imports: import collections
  import os
  from absl import logging
  import numpy
  import pandas
  import tensorflow.compat.v1
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling a global function with example usage: get_eval_metric_values(events, task_name) and returns: eval_values