code: def tokenize_texts(
      texts, n_workers=defaults.cpus, rules=None, tok=None
  ):
      "Tokenize `texts` in parallel using `n_workers`"
      rules = L(ifnone(rules, defaults.text_proc_rules.copy()))
      outputs = (
          L(
              parallel_tokenize(
                  texts, tok=tok, rules=rules, n_workers=n_workers
              )
          )
          .sorted()
          .itemgot(1)
      )
      return outputs
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  import html
label_desc: Use image node_id 16 for calling a global function with example usage: tokenize_texts(texts, n_workers, rules, tok) and returns: outputs