code: def hf_bert(model, inputs, attn_mask):
      torch.cuda.synchronize()
      start_time = time.perf_counter()
      hf_output = model(
          inputs.to("cuda:0"), attention_mask=attn_mask.to("cuda:0")
      )
      torch.cuda.synchronize()
      end_time = time.perf_counter()
      return hf_output, end_time - start_time
  
file_path: lightseq/examples/inference/python/test/ls_bert.py
imports: import time
  import argparse
  import torch
  import lightseq.inference
  from transformers import BertTokenizer, BertForSequenceClassification
label_desc: Use image node_id 2 for calling a global function with example usage: hf_bert(model, inputs, attn_mask) and returns: hf_output,  unknown