code: def hf_generate(model, inputs):
      print("=========huggingface=========")
      print("huggingface generating...")
      hf_output, hf_time = hf_vit(model, inputs)
      print(f"huggingface time: {hf_time}s")
      print("huggingface results (class predictions):")
      print(hf_output.last_hidden_state.size())
  
file_path: lightseq/examples/inference/python/test/ls_vit_bench.py
imports: import time
  import torch
  import lightseq.inference
  from transformers import ViTFeatureExtractor, ViTForImageClassification, ViTModel
  from PIL import Image
  import requests
label_desc: Use image node_id 4 for calling a global function with example usage: hf_generate(model, inputs) without return types