class_docstr: Spacy tokenizer for `lang`
class_docstr_tok: ["Spacy","tokenizer","for","`","lang","`"]
code: def __init__(self, lang="en", special_toks=None, buf_sz=5000):
      import spacy
      from spacy.symbols import ORTH
  
      self.special_toks = ifnone(special_toks, defaults.text_spec_tok)
      nlp = spacy.blank(lang)
      for w in self.special_toks:
          nlp.tokenizer.add_special_case(w, [{ORTH: w}])
      self.pipe, self.buf_sz = nlp.pipe, buf_sz
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  import html
label_desc: Use image node_id 1 to create a new SpacyTokenizer object  with example: obj = SpacyTokenizer(lang, special_toks, buf_sz)