code: def process_sorted_buckets(
      working_directory, move_dir, process_count
  ):
      bucket_file_paths = glob.glob(
          os.path.join(working_directory, f"*.bkt.txt.sorted")
      )
      processed_directory = os.path.join(working_directory, "processed")
      os.makedirs(processed_directory, exist_ok=True)
  
      pool = TqdmMultiProcessPool(process_count)
      tasks = [
          (process_bucket, (bucket_file, processed_directory, move_dir))
          for bucket_file in bucket_file_paths
      ]
  
      global_tqdm = tqdm(
          total=len(bucket_file_paths),
          dynamic_ncols=True,
          unit="bucket",
      )
  
      def on_done(_):
          return None
  
      def on_error(_):
          return None
  
      _ = pool.map(global_tqdm, tasks, on_error, on_done)
  
file_path: lm-evaluation-harness/scripts/clean_training_data/process_sorted_buckets.py
imports: import argparse
  import glob
  import os
  from pathlib import Path
  import re
  import shutil
  from tqdm import tqdm
  from tqdm_multiprocess import TqdmMultiProcessPool
  from scripts.clean_training_data.archiver import TextReader, TextArchive
  import logging
  from tqdm_multiprocess.logger import setup_logger_tqdm
label_desc: Use image node_id 2 for calling a global function with example usage: process_sorted_buckets(working_directory, move_dir, process_count) and returns: None, None