docstr: Parses wandb log for `section` and returns a dictionary of
  all items in that section. Section names are based on the
  output of `wandb sync --view --verbose` and items starting
  with "Record" in that result
code: def parse_log(log: str, section: str, record: bool = True):
      """
      Parses wandb log for `section` and returns a dictionary of
      all items in that section. Section names are based on the
      output of `wandb sync --view --verbose` and items starting
      with "Record" in that result
      """
      # Big thanks to the W&B team for helping us parse their logs
      pattern = rf"{section} ([\S\s]*?)\n\n"
      if record:
          pattern = rf"Record: {pattern}"
      cleaned_record = re.findall(pattern, log)[0]
      # A config
      if section == "config" or section == "history":
          cleaned_record = re.findall(
              r'"([a-zA-Z0-9_.,]+)', cleaned_record
          )
          return {
              key: val
              for key, val in zip(
                  cleaned_record[0::2], cleaned_record[1::2]
              )
          }
      # Everything else
      else:
          return dict(re.findall(r'(\w+): "([^\s]+)"', cleaned_record))
  
imports: import csv
  import json
  import logging
  import os
  import re
  import subprocess
  import tempfile
  import unittest
  import zipfile
  from pathlib import Path
  from typing import Optional
  from unittest import mock
  import numpy
  import torch
  from accelerate import Accelerator
  from accelerate.test_utils.testing import MockingTestCase, TempDirTestCase, require_clearml, require_comet_ml, require_dvclive, require_pandas, require_tensorboard, require_wandb, skip
  from accelerate.tracking import CometMLTracker, GeneralTracker
  from accelerate.utils import ProjectConfiguration, is_comet_ml_available, is_dvclive_available, is_tensorboard_available
label_desc: Use image node_id 2 for calling the WandBTrackingTest obj's underlying member method code with example usage: obj.parse_log(log, section, record) and returns: unknown, dict