code: def get_parser():
      parser = argparse.ArgumentParser(
          description="convert beit checkpoint into data2vec - vision checkpoint"
      )
      # fmt: off
      parser.add_argument('checkpoint', help='checkpoint to convert')
      parser.add_argument('--output', required=True, metavar='PATH', help='where to output converted checkpoint')
      parser.add_argument('--type', type=str, choices=['vision', 'image_classification'], default='image_classification', help='type of model to upgrade')
      parser.add_argument('--inception_norms', action='store_true', default=False)
      # fmt: on
  
      return parser
  
file_path: fairseq/examples/data2vec/fb_convert_beit_cp.py
imports: import argparse
  import torch
  from omegaconf import OmegaConf
  from fairseq.criterions.model_criterion import ModelCriterionConfig
  from fairseq.dataclass.configs import FairseqConfig
  from tasks import ImageClassificationConfig, ImagePretrainingConfig
  from models.data2vec_image_classification import Data2VecImageClassificationConfig, Data2VecImageClassificationModel
  from models.data2vec_vision import Data2VecVisionConfig, Data2VecVisionModel
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser