class_docstr: A simple regex-splitting tokenizer.
class_docstr_tok: ["A","simple","regex-splitting","tokenizer","."]
code: def decode(self, sentence: str):
      ## To be overridden by subword level tokenizers to convert to string
      return sentence
  
imports: import copy
  import json
  import re
  from collections import OrderedDict
  from typing import List, NamedTuple, Optional, Union
  import torch
  from fairseq.data.encoders.gpt2_bpe import get_encoder
  from fairseq.data.encoders.gpt2_bpe_utils import Encoder
  from pytext.config import ConfigBase
  from pytext.config.component import Component, ComponentType, create_component
  from pytext.data.pickleable_gpt2bpe_encoder import PickleableGPT2BPEEncoder
  from pytext.torchscript.tokenizer import ScriptDoNothingTokenizer, ScriptWordTokenizer
  from pytext.utils.file_io import PathManager
  from pytext.utils.usage import log_class_usage
  from transformers.tokenization_bert import BasicTokenizer, WordpieceTokenizer
label_desc: Use image node_id 7 for calling the Tokenizer obj's underlying member method code with example usage: obj.decode(sentence) and returns: sentence