code: def pad_sequence_to_length(
      sequence: Sequence,
      desired_length: int,
      default_value: Callable[[], Any] = lambda: 0,
      padding_on_right: bool = True,
  ) -> List:
      """
      Take a list of objects and pads it to the desired length, returning the padded list.  The
      original list is not modified.
  
      # Parameters
  
      sequence : `List`
          A list of objects to be padded.
  
      desired_length : `int`
          Maximum length of each sequence. Longer sequences are truncated to this length, and
          shorter ones are padded to it.
  
      default_value: `Callable`, optional (default=`lambda: 0`)
          Callable that outputs a default value (of any type) to use as padding values.  This is
          a lambda to avoid using the same object when the default value is more complex, like a
          list.
  
      padding_on_right : `bool`, optional (default=`True`)
          When we add padding tokens (or truncate the sequence), should we do it on the right or
          the left?
  
      # Returns
  
      padded_sequence : `List`
      """
      sequence = list(sequence)
      # Truncates the sequence to the desired length.
      if padding_on_right:
          padded_sequence = sequence[:desired_length]
      else:
          padded_sequence = sequence[-desired_length:]
      # Continues to pad with default_value() until we reach the desired length.
      pad_length = desired_length - len(padded_sequence)
      # This just creates the default value once, so if it's a list, and if it gets mutated
      # later, it could cause subtle bugs. But the risk there is low, and this is much faster.
      values_to_pad = [default_value()] * pad_length
      if padding_on_right:
          padded_sequence = padded_sequence + values_to_pad
      else:
          padded_sequence = values_to_pad + padded_sequence
      return padded_sequence
  
imports: import hashlib
  import io
  from datetime import timedelta
  import importlib
  import json
  import logging
  import os
  import pkgutil
  import random
  import sys
  import signal
  from contextlib import contextmanager
  from itertools import islice, zip_longest
  from pathlib import Path
  from typing import Any, Callable, Dict, Generator, Iterable, Iterator, List, Optional, Tuple, TypeVar, Union, Sequence, Set
  import dill
  import numpy
  import spacy
  import torch
  import torch.distributed
  from spacy.cli.download import download
  from spacy.language import Language
  import base58
  from allennlp.common.checks import log_pytorch_version_info
  from allennlp.common.params import Params
label_desc: Use image node_id 4 for calling a global function with example usage: pad_sequence_to_length(sequence, desired_length, default_value, padding_on_right) and returns: padded_sequence