code: def main():
      url = "http://images.cocodataset.org/val2017/000000039769.jpg"
      image = Image.open(requests.get(url, stream=True).raw)
      feature_extractor = ViTFeatureExtractor.from_pretrained(
          "google/vit-base-patch16-224-in21k"
      )
      inputs = feature_extractor(images=image, return_tensors="pt")
      inputs = inputs["pixel_values"]
  
      print("creating huggingface model...")
      hf_model = ViTForImageClassification.from_pretrained(
          "google/vit-base-patch16-224-in21k"
      ).cuda()
  
      print("creating lightseq model...")
      ls_model = LightseqVitClassification(
          "lightseq_vit.hdf5", hf_model
      )
  
      print("====================START warmup====================")
      one_infer(inputs, ls_model, hf_model)
      print("====================END warmup====================")
  
      one_infer(inputs, ls_model, hf_model)
  
file_path: lightseq/examples/inference/python/test/ls_vit.py
imports: import time
  import torch
  import lightseq.inference
  from transformers import ViTFeatureExtractor, ViTForImageClassification
  from PIL import Image
  import requests
label_desc: Use image node_id 6 for calling a global function with example usage: main() without return types