docstr: This functions will be called to set a padding style.
  None - No padding
  List: first element 0, round seq length to the smallest list element larger than inputs
code: def set_padding_control(
      self, dimension: str, padding_control: Optional[List[int]]
  ):
      """
      This functions will be called to set a padding style.
      None - No padding
      List: first element 0, round seq length to the smallest list element larger than inputs
      """
      if not validate_padding_control(padding_control):
          raise RuntimeError("Malformed padding_control value")
      if dimension == "sequence_length":
          self.seq_padding_control = padding_control
      elif dimension == "batch_length":
          self.batch_padding_control = padding_control
      else:
          raise RuntimeError("Illegal padding dimension specified.")
  
imports: from typing import List, Optional, Tuple
  import torch
  from pytext.torchscript.utils import pad_2d_float, pad_3d_float, validate_padding_control
  from pytext.torchscript.vocab import ScriptVocabulary
  from pytorch.text.fb.utils.transform_utils import pad_2d
label_desc: Use image node_id 3 for calling the ScriptTensorizer obj's underlying member method code with example usage: obj.set_padding_control(dimension, padding_control) without return types