def collate_function(batch: List[Tuple[List[int], List[int]]],
                     pad_token_id: int) -> Dict[str, torch.Tensor]:
    """Collect a list of masked token indices, and labels, and
    batch them, padding to max length in the batch.
    """
    max_length = max(len(token_ids) for token_ids, _ in batch)
    padded_token_ids = [
        token_ids +
        [pad_token_id for _ in range(0, max_length - len(token_ids))]
        for token_ids, _ in batch
    ]
    padded_labels = [
        labels + [pad_token_id for _ in range(0, max_length - len(labels))]
        for _, labels in batch
    ]
    src_tokens = torch.LongTensor(padded_token_ids)
    tgt_tokens = torch.LongTensor(padded_labels)
    attention_mask = src_tokens.ne(pad_token_id).type_as(src_tokens)
    return {
        "src_tokens": src_tokens,
        "tgt_tokens": tgt_tokens,
        "attention_mask": attention_mask,
    }
Collect a list of masked token indices, and labels, and
    batch them, padding to max length in the batch.
    
training/HelloDeepSpeed/train_bert_ds.py