code: def hf_vit(model, inputs):
      for _ in range(10):
          hf_output = model(inputs.cuda())
      torch.cuda.synchronize()
      start_time = time.perf_counter()
      for _ in range(20):
          hf_output = model(inputs.cuda())
      torch.cuda.synchronize()
      end_time = time.perf_counter()
      return hf_output, (end_time - start_time) / 20
  
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 2 for calling a global function with example usage: hf_vit(model, inputs) and returns: hf_output,  unknown