code: def _pad(self, batch):
      batch = copy.deepcopy(batch)
      longest = max(len(ids) for ids in batch["input_ids"])
      for i in range(len(batch["input_ids"])):
          length = len(batch["input_ids"][i])
          difference = longest - length
          batch["attention_mask"][i] = [1] * length + [0] * difference
          batch["input_ids"][i].extend([0] * difference)
          batch["token_type_ids"][i].extend([2] * difference)
      return batch
  
imports: from typing import Dict, List, Union
  import numpy
  import torch
  import copy
  from transformers.file_utils import ModelOutput
  from numpy.testing import assert_array_equal
  from spacy.tokens import Doc
  from thinc.api import Model, get_current_ops
  from ..data_classes import FullTransformerBatch, HFObjects
  from ..span_getters import get_doc_spans
  from ..layers.transformer_model import forward
label_desc: Use image node_id 5 for calling the DummyTokenizer obj's underlying member method code with example usage: obj._pad(batch) and returns: batch