class_docstr: A text dataset with one sequence as input and a label.
class_docstr_tok: ["A","text","dataset","with","one","sequence","as","input","and","a","label","."]
docstr: The padded shapes used by batching functions.
docstr_tok: ["The","padded","shapes","used","by","batching","functions","."]
code: def padded_shapes(self):
      """The padded shapes used by batching functions."""
      # None means variable length; pads to the longest sequence in the batch.
      return {"idx": [], "token_ids": [None], "label": [], "length": []}
  
imports: from typing import Any, Dict, Optional
  from absl import logging
  import numpy
  import tensorflow
  import tensorflow_datasets
  import tensorflow_text
  import vocabulary
label_desc: Use image node_id 2 for calling the TextDataset obj's underlying member method code with example usage: obj.padded_shapes() and returns: dict