code: def affix_constructor(train_sents, backoff=None):
      affixes = args.affix or [-3]
  
      for affix in affixes:
          if args.trace:
              print(
                  "training AffixTagger with affix %d and backoff %s"
                  % (affix, backoff)
              )
  
          backoff = nltk.tag.AffixTagger(
              train_sents,
              affix_length=affix,
              min_stem_length=min(affix, 2),
              backoff=backoff,
          )
  
      return backoff
  
file_path: nltk-trainer/train_tagger.py
imports: import argparse, math, itertools, os.path
  import nltk.corpus, nltk.data
  import nltk_trainer.classification.args
  from nltk.classify import DecisionTreeClassifier, MaxentClassifier, NaiveBayesClassifier
  from nltk.corpus.reader import SwitchboardCorpusReader, NPSChatCorpusReader, IndianCorpusReader
  from nltk.corpus.util import LazyCorpusLoader
  from nltk.tag import ClassifierBasedPOSTagger
  from nltk_trainer import dump_object, load_corpus_reader, simplify_wsj_tag
  from nltk_trainer.tagging import readers
  from nltk_trainer.tagging.training import train_brill_tagger
  from nltk_trainer.tagging.taggers import PhoneticClassifierBasedPOSTagger
label_desc: Use image node_id 1 for calling a global function with example usage: affix_constructor(train_sents, backoff) and returns: backoff