  
  from spacy.scorer import Scorer
  
  
  def add_noise(c, noise_level):
      if random.random() >= noise_level:
          return c
      elif c == ' ':
          return '\n'
      elif c == '\n':
 
</s> remove                     tokens = nlp.tokenizer.tokens_from_list(annot_tuples[1])
 </s> add                     words = add_noise(annot_tuples[1], corruption_level)
                    tokens = nlp.tokenizer.tokens_from_list(words)
def _corrupt(c, noise_level):
  
  from spacy.scorer import Scorer
  
  
def _corrupt(c, noise_level):
      if random.random() >= noise_level:
          return c
      elif c == ' ':
          return '\n'
      elif c == '\n':
keep keep keep keep replace keep keep keep keep keep
 * Update input corruption method to work with lists as well as trings 
bin/parser/train.py