code: def get_data(bs, sl):
      path = untar_data(URLs.WIKITEXT_TINY)
      train = LM_Dataset(
          read_file(path / "train.txt"), bs=bs, seq_len=sl, shuffle=True
      )
      valid = LM_Dataset(
          read_file(path / "valid.txt"), bs=bs, seq_len=sl
      )
      count = Counter([p for t in train.ds for p in t])
      vocab = make_vocab(count)
      train_ds = TfmdLists(
          train, tfms=Numericalize(vocab), as_item=False, wrap_l=False
      )
      valid_ds = TfmdLists(
          valid, tfms=Numericalize(vocab), as_item=False, wrap_l=False
      )
      train_dl = TfmdDL(
          train_ds, bs=bs, sampler=LM_Sampler(train), num_workers=8
      )
      valid_dl = TfmdDL(
          valid_ds, bs=bs, sampler=LM_Sampler(valid), num_workers=8
      )
      return DataLoaders(train_dl, valid_dl), vocab
  
imports: from fastai.basics import *
  from fastai.text.all import *
  from fastai.callback.all import *
  from fastcore.script import *
label_desc: Use image node_id 3 for calling a global function with example usage: get_data(bs, sl) and returns: DataLoaders,  vocab