code: def parse_args():
      """parse arguments"""
      parser = argparse.ArgumentParser()
      parser.add_argument("--input", type=str, required=True)
      parser.add_argument(
          "--model_name",
          type=str,
          default="tf_efficientnet_b3_ns",
          required=False,
      )
      parser.add_argument(
          "--learning_rate", type=float, default=1e-3, required=False
      )
      parser.add_argument(
          "--batch_size", type=int, default=32, required=False
      )
      parser.add_argument(
          "--epochs", type=int, default=50, required=False
      )
      parser.add_argument(
          "--output", type=str, default="~/data/", required=False
      )
      parser.add_argument(
          "--accumulation_steps", type=int, default=1, required=False
      )
      parser.add_argument(
          "--image_size", type=int, default=512, required=False
      )
      return parser.parse_args()
  
imports: import argparse
  import os
  import albumentations
  import numpy
  import pandas
  import timm
  import torch
  import torch.nn
  from cv2 import dft
  from sklearn import metrics, model_selection
  from tqdm.auto import tqdm
  from tez import Tez, TezConfig
  from tez.callbacks import EarlyStopping
  from tez.datasets import ImageDataset
  from tez.utils import seed_everything
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: parser