code: def warmup(tokenizer, ls_model, hf_model, sentences):
      inputs = tokenizer(sentences, return_tensors="pt", padding=True)
      inputs_id = inputs["input_ids"]
      attn_mask = inputs["attention_mask"]
  
      # ls_generate(ls_model, inputs_id, attn_mask)
      hf_generate(hf_model, inputs_id, attn_mask)
  
file_path: lightseq/examples/inference/python/test/ls_bert_bench.py
imports: import time
  import argparse
  import torch
  import lightseq.inference
  from transformers import BertTokenizer, BertForSequenceClassification, BertModel
label_desc: Use image node_id 5 for calling a global function with example usage: warmup(tokenizer, ls_model, hf_model, sentences) without return types