code: def hf_generate(model, inputs_id, attn_mask):
      print("=========huggingface=========")
      print("huggingface generating...")
      hf_output, hf_time = hf_bert(model, inputs_id, attn_mask)
      print(f"huggingface time: {hf_time}s")
      print("huggingface results (class predictions):")
      print(hf_output.logits.argmax(axis=1).detach().cpu().numpy())
  
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 4 for calling a global function with example usage: hf_generate(model, inputs_id, attn_mask) without return types