class_docstr: Base class for text encoders.
  Translates raw texts into structured token arrays
class_docstr_tok: ["Base","class","for","text","encoders",".","Translates","raw","texts","into","structured","token","arrays"]
code: def __init__(self, encoder_path, vocab_path):
      self.encoder_path = encoder_path
      self.vocab_path = vocab_path
  
      # Required public attributes -- consider refactor to prevent requiring direct
      # access of these attributes
      self.special_tokens = None
      self.start_token = None
      self.delimiter_token = None
      self.end_token = None
      self.encoder = None
      self.decoder = None
      self.cache = CacheDict()
  
imports: import warnings
  import functools
  from collections import namedtuple, Counter, OrderedDict
  import spacy
  import numpy
label_desc: Use image node_id 1 to create a new BaseEncoder object  with example: obj = BaseEncoder(encoder_path, vocab_path)