class_docstr: This class is responsible for the search of the appropriate files to use
  as input based on the constraints given in the config file.
code: def __check_unique_names(self, file_list, id_list):
      uniq_dict = dict()
      for idx, subject_id in enumerate(id_list):
          if not subject_id:
              continue
          id_string = subject_id[0]
          if id_string in uniq_dict:
              tf.logging.fatal(
                  'extracted the same unique_id "%s" from '
                  'filenames "%s" and "%s", using matcher: %s',
                  id_string,
                  uniq_dict[id_string],
                  file_list[idx],
                  self,
              )
              raise ValueError
          uniq_dict[id_string] = file_list[idx]
  
file_path: NiftyNet/niftynet/utilities/filename_matching.py
imports: from __future__ import absolute_import, print_function
  import os
  import re
  import six
  import niftynet.io.misc_io
  import tensorflow
label_desc: Use image node_id 6 for calling the KeywordsMatching obj's underlying member method code with example usage: obj.__check_unique_names(file_list, id_list) without return types