code: def get_args():
      parser = argparse.ArgumentParser(
          "Convert Data2VecVision to HF for image classification and pretraining",
          add_help=False,
      )
      parser.add_argument("--hf_checkpoint_name", type=str)
      parser.add_argument(
          "--input_size",
          default=224,
          type=int,
          help="images input size",
      )
      parser.add_argument(
          "--beit_checkpoint", default="", help="beit checkpoint"
      )
  
      return parser.parse_args()
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/data2vec/convert_data2vec_vision_original_pytorch_checkpoint_to_pytorch.py
imports: import argparse
  import json
  import torch
  from PIL import Image
  from huggingface_hub import hf_hub_download
  from timm.models import create_model
  from transformers import BeitFeatureExtractor, Data2VecVisionConfig, Data2VecVisionForImageClassification, Data2VecVisionModel
label_desc: Use image node_id 3 for calling a global function with example usage: get_args() and returns: parser