code: def stem_token(token, resources):
      from snips_nlu_utils import normalize
  
      if token.stemmed_value:
          return token.stemmed_value
      if not token.normalized_value:
          token.normalized_value = normalize(token.value)
      token.stemmed_value = _stem(token.normalized_value, resources)
      return token.stemmed_value
  
file_path: snips-nlu/snips_nlu/preprocessing.py
imports: from __future__ import unicode_literals
  from builtins import object
  from snips_nlu.resources import get_stems
label_desc: Use image node_id 2 for calling a global function with example usage: stem_token(token, resources) and returns: token, token