class_docstr: Basic initial tokenization for BERT.  This is run prior to word piece, does
  white space tokenization in addition to lower-casing and accent removal
  if specified.
class_docstr_tok: ["Basic","initial","tokenization","for","BERT",".","This","is","run","prior","to","word","piece",",","does","white","space","tokenization","in","addition","to","lower-casing","and","accent","removal","if","specified","."]
code: def from_config(cls, config: Config):
      basic_tokenizer = BasicTokenizer(
          do_lower_case=config.lowercase,
          never_split=(
              "[UNK]",
              "[SEP]",
              "[PAD]",
              "[CLS]",
              "[MASK]",
          ),  # compatibility with HF v0.5
      )
      return cls(basic_tokenizer)
  
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 1 for calling the BERTInitialTokenizer obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls