code: def torchhub_docstring(name: str):
      return f"""Constructs a {name} model.
      For detailed information on model input and output, training recipies, inference and performance
      visit: github.com/NVIDIA/DeepLearningExamples and/or ngc.nvidia.com
      Args:
          pretrained (bool, True): If True, returns a model pretrained on IMAGENET dataset.
      """
  
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 1 for calling a global function with example usage: torchhub_docstring(name) and returns: str, name, str