code: def ls_generate(model, tokenizer, inputs_id):
      print("=========lightseq=========")
      print("lightseq generating...")
      ls_res_ids, ls_time = ls_t5(model, inputs_id)
      # for line in ls_res_ids:
      #     print(line)
      ls_res_ids = [ids[0] for ids in ls_res_ids[0]]
      ls_res = tokenizer.batch_decode(
          ls_res_ids, skip_special_tokens=True
      )
      print(f"lightseq time: {ls_time}s")
      print("lightseq results:")
      for sent in ls_res:
          print(sent)
  
file_path: lightseq/examples/inference/python/test/ls_t5.py
imports: import time
  import argparse
  import torch
  import lightseq.inference
  from transformers import T5Tokenizer, T5ForConditionalGeneration
  import sentencepiece
label_desc: Use image node_id 3 for calling a global function with example usage: ls_generate(model, tokenizer, inputs_id) without return types