class_docstr: Convert source and target examples to doc level segments.
  
  It concatenates segments with a DefaultTokens.SEP
  until it reaches --doc_length tokens
class_docstr_tok: ["Convert","source","and","target","examples","to","doc","level","segments",".","It","concatenates","segments","with","a","DefaultTokens.SEP","until","it","reaches","--","doc_length","tokens"]
code: def warm_up(self, vocabs=None):
      super().warm_up(None)
      if self.stride != 1:
          assert (
              self.stride % (self.max_context + 1) == 0
          ), "(max_context+1) must be a multiple \
                   of num_workers * world_size"
  
file_path: OpenNMT-py/onmt/transforms/docify.py
imports: from onmt.constants import DefaultTokens
  from onmt.transforms import register_transform
  from .transform import Transform
  import copy
label_desc: Use image node_id 5 for calling the DocifyTransform obj's underlying member method code with example usage: obj.warm_up(vocabs) without return types