class_docstr: Naive lemmatizer for Old French.
  
  >>> lemmatizer = OldFrenchDictionaryLemmatizer()
  >>> lemmatizer.lemmatize_token('corant')
  'corant'
  >>> lemmatizer.lemmatize_token('corant', return_frequencies=True)
  ('corant', -9.319508628976836)
  >>> lemmatizer.lemmatize_token('corant', return_frequencies=True, best_guess=False)
  [('corir', 0), ('corant', -9.319508628976836)]
  >>> lemmatizer.lemmatize(['corant', '.', 'vult', 'premir'], return_frequencies=True, best_guess=False)
  [[('corir', 0), ('corant', -9.319508628976836)], [('PUNK', 0)], [('vout', -7.527749159748781)], [('premir', 0)]]
docstr: Load the table of frequency counts of word forms.
docstr_tok: ["Load","the","table","of","frequency","counts","of","word","forms","."]
code: def _load_unigram_counts(self):
      """Load the table of frequency counts of word forms."""
  
      rel_path = os.path.join(
          CLTK_DATA_DIR,
          "fro",
          "model",
          "fro_models_cltk",
          "fro_unigrams.txt",
      )
      path = os.path.expanduser(rel_path)
  
      type_counts = {}
  
      with open(path, "r") as infile:
          lines = infile.read().splitlines()
          for line in lines:
              count, word = line.split()
              type_counts[word] = int(count)
  
      return type_counts
  
file_path: cltk/src/cltk/lemmatize/fro.py
imports: import importlib.machinery
  import os
  from cltk.lemmatize.naive_lemmatizer import DictionaryRegexLemmatizer
  from cltk.utils import CLTK_DATA_DIR
label_desc: Use image node_id 2 for calling the OldFrenchDictionaryLemmatizer obj's underlying member method code with example usage: obj._load_unigram_counts() and returns: type_counts