code: def parser(self):
      if self.model.params is None:
          return None
      parser = self.model.params.parser(self.name)
      parser.add_argument(
          "--pretrained-from-file",
          default=None,
          type=str,
          metavar="PATH",
          help="load weights from local file",
      )
      if self.model.checkpoint_url is not None:
          parser.add_argument(
              "--pretrained",
              default=False,
              action="store_true",
              help="load pretrained weights from NGC",
          )
  
      return parser
  
file_path: DALI/docs/examples/use_cases/pytorch/efficientnet/image_classification/models/model.py
imports: from dataclasses import dataclass, asdict, replace
  from .common import SequentialSqueezeAndExcitationTRT, SequentialSqueezeAndExcitation, SqueezeAndExcitation, SqueezeAndExcitationTRT
  from typing import Optional, Callable
  import os
  import torch
  import argparse
  from functools import partial
label_desc: Use image node_id 4 for calling the EntryPoint obj's underlying member method code with example usage: obj.parser() and returns: parser, None