class_docstr: BytePairEncoder trains byte pair encoding and
  encodes words using trained encoding
class_docstr_tok: ["BytePairEncoder","trains","byte","pair","encoding","and","encodes","words","using","trained","encoding"]
docstr: Returns the cache cleanup period. The cache is used for Encode calls acceleration.
  The result of the encode call is cached and will be erased if 
  no call with the same word will occur among next 1-2 X cachePeriod calls.
  :rtype: int.
docstr_tok: ["Returns","the","cache","cleanup","period",".","The","cache","is","used","for","Encode","calls","acceleration",".","The","result","of","the","encode","call","is","cached","and","will","be","erased","if","no","call","with","the","same","word","will","occur","among","next","1-2","X","cachePeriod","calls",".",":","rtype",":","int","."]
code: def cache_period(self) -> int:
      """Returns the cache cleanup period. The cache is used for Encode calls acceleration.
      The result of the encode call is cached and will be erased if
      no call with the same word will occur among next 1-2 X cachePeriod calls.
      :rtype: int.
      """
      return self._internal.get_cache_period()
  
file_path: neoml/NeoML/Python/neoml/BytePairEncoder.py
imports: import neoml.PythonWrapper
  import typing
label_desc: Use image node_id 13 for calling the BytePairEncoder obj's underlying member method code with example usage: obj.cache_period() and returns: self