code: def qa_s2s_generate(
      question_doc,
      qa_s2s_model,
      qa_s2s_tokenizer,
      num_answers=1,
      num_beams=None,
      min_len=64,
      max_len=256,
      do_sample=False,
      temp=1.0,
      top_p=None,
      top_k=None,
      max_input_length=512,
      device="cuda:0",
  ):
      model_inputs = make_qa_s2s_batch(
          [(question_doc, "A")],
          qa_s2s_tokenizer,
          max_input_length,
          device=device,
      )
      n_beams = (
          num_answers
          if num_beams is None
          else max(num_beams, num_answers)
      )
      generated_ids = qa_s2s_model.generate(
          input_ids=model_inputs["input_ids"],
          attention_mask=model_inputs["attention_mask"],
          min_length=min_len,
          max_length=max_len,
          do_sample=do_sample,
          early_stopping=True,
          num_beams=1 if do_sample else n_beams,
          temperature=temp,
          top_k=top_k,
          top_p=top_p,
          eos_token_id=qa_s2s_tokenizer.eos_token_id,
          no_repeat_ngram_size=3,
          num_return_sequences=num_answers,
          decoder_start_token_id=qa_s2s_tokenizer.bos_token_id,
      )
      return [
          qa_s2s_tokenizer.decode(
              ans_ids, skip_special_tokens=True
          ).strip()
          for ans_ids in generated_ids
      ]
  
imports: import functools
  import math
  import os
  from random import choice, randint
  from time import time
  import datasets
  import numpy
  import pandas
  import torch
  import torch.utils.checkpoint
  from elasticsearch import Elasticsearch
  from elasticsearch.helpers import bulk, streaming_bulk
  from torch import nn
  from torch.utils.data import DataLoader, Dataset, RandomSampler, SequentialSampler
  from tqdm import tqdm
  import faiss
  from transformers import AdamW, AutoModel, AutoModelForSeq2SeqLM, AutoTokenizer, get_linear_schedule_with_warmup
label_desc: Use image node_id 14 for calling a global function with example usage: qa_s2s_generate(question_doc, qa_s2s_model, qa_s2s_tokenizer, num_answers, num_beams, min_len, max_len, do_sample, temp, top_p, top_k, max_input_length, device) and returns: unknown