class_docstr: A `TransformBlock` for texts
class_docstr_tok: ["A","`","TransformBlock","`","for","texts"]
code: def __init__(
      self,
      tok_tfm,
      vocab=None,
      is_lm=False,
      seq_len=72,
      backwards=False,
      **kwargs,
  ):
      type_tfms = [tok_tfm, Numericalize(vocab, **kwargs)]
      if backwards:
          type_tfms += [reverse_text]
      return super().__init__(
          type_tfms=type_tfms,
          dl_type=LMDataLoader if is_lm else SortedDL,
          dls_kwargs={"seq_len": seq_len}
          if is_lm
          else {"before_batch": Pad_Chunk(seq_len=seq_len)},
      )
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  from .core import *
label_desc: Use image node_id 1 to create a new TextBlock object from inherited base classes: TransformBlock with example: obj = TextBlock(tok_tfm, vocab, is_lm, seq_len, backwards)