code: def padded_collate(batch, padding_idx=0):
      x = pad_sequence(
          [elem["input_ids"] for elem in batch],
          batch_first=True,
          padding_value=padding_idx,
      )
      y = torch.stack([elem["label"] for elem in batch]).long()
      return x, y
  
imports: import argparse
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from datasets import load_dataset
  from opacus import PrivacyEngine
  from torch.nn.utils.rnn import pad_sequence
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from transformers import BertTokenizerFast
label_desc: Use image node_id 2 for calling a global function with example usage: padded_collate(batch, padding_idx) and returns: x,  y