code: def merge_knn_files(knn_files: List[KNNIndex], output_file: str):
      """
      Merge a list of knn sharding index files into one.
      """
      files = [KNNIndex(f) for f in knn_files]
      sorted_files = sorted(files, key=lambda x: x.chunk_start_id)
      # consistence check
      start_id = sorted_files[0].chunk_start_id
      previous_end = sorted_files[0].chunk_end_id
      K = sorted_files[0].K
      for i in sorted_files[1:]:
          assert previous_end == i.chunk_start_id
          assert K == i.K
          previous_end = i.chunk_end_id
      with KNNIndex.writer(output_file, K, offset=start_id) as w:
          for i in sorted_files:
              w.write(i.knn_map)
      f = KNNIndex(output_file)
      logging.info(f"{output_file} index starts at {f.chunk_start_id}")
      logging.info(f"{output_file} index ends at {f.chunk_end_id}")
      logging.info(f"total len {f.len}")
      assert f.len == (f.chunk_end_id - f.chunk_start_id)
  
imports: import os
  import shutil
  import struct
  from functools import lru_cache
  from itertools import accumulate
  from typing import List
  import numpy
  import torch
  from nemo.utils import logging
label_desc: Use image node_id 5 for calling a global function with example usage: merge_knn_files(knn_files, output_file) without return types