class_docstr: Provides a consistent `Transform` interface to tokenizers operating on `DataFrame`s and folders
class_docstr_tok: ["Provides","a","consistent","`","Transform","`","interface","to","tokenizers","operating","on","`","DataFrame","`","s","and","folders"]
code: def setups(self, dsets):
      if not self.mode == "df" or not isinstance(
          dsets.items, pd.DataFrame
      ):
          return
      dsets.items, count = tokenize_df(
          dsets.items, self.text_cols, rules=self.rules, **self.kwargs
      )
      if self.counter is None:
          self.counter = count
      if self.lengths is None:
          self.lengths = dsets.items[
              f"{self.tok_text_col}_length"
          ].values
      return dsets
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  import html
label_desc: Use image node_id 4 for calling the Tokenizer obj's underlying member method code with example usage: obj.setups(dsets) and returns: dsets