code: def parse_args():
      import argparse
  
      parser = argparse.ArgumentParser(
          description="PyTorch Embedding Learning"
      )
  
      parser.add_argument(
          "--dataset-dir",
          default="/tmp/fmnist/",
          type=str,
          help="FashionMNIST dataset directory path",
      )
      parser.add_argument(
          "-p",
          "--labels-per-batch",
          default=8,
          type=int,
          help="Number of unique labels/classes per batch",
      )
      parser.add_argument(
          "-k",
          "--samples-per-label",
          default=8,
          type=int,
          help="Number of samples per label in a batch",
      )
      parser.add_argument(
          "--eval-batch-size",
          default=512,
          type=int,
          help="batch size for evaluation",
      )
      parser.add_argument(
          "--epochs",
          default=10,
          type=int,
          metavar="N",
          help="number of total epochs to run",
      )
      parser.add_argument(
          "-j",
          "--workers",
          default=4,
          type=int,
          metavar="N",
          help="number of data loading workers",
      )
      parser.add_argument(
          "--lr",
          default=0.0001,
          type=float,
          help="initial learning rate",
      )
      parser.add_argument(
          "--margin",
          default=0.2,
          type=float,
          help="Triplet loss margin",
      )
      parser.add_argument(
          "--print-freq", default=20, type=int, help="print frequency"
      )
      parser.add_argument(
          "--save-dir",
          default=".",
          type=str,
          help="Model save directory",
      )
      parser.add_argument(
          "--resume", default="", type=str, help="path of checkpoint"
      )
      parser.add_argument(
          "--test-only",
          dest="test_only",
          help="Only test the model",
          action="store_true",
      )
      parser.add_argument(
          "--use-deterministic-algorithms",
          action="store_true",
          help="Forces the use of deterministic algorithms only.",
      )
  
      return parser.parse_args()
  
file_path: vision/references/similarity/train.py
imports: import os
  import torch
  import torchvision.transforms
  from loss import TripletMarginLoss
  from model import EmbeddingNet
  from sampler import PKSampler
  from torch.optim import Adam
  from torch.utils.data import DataLoader
  from torchvision.datasets import FashionMNIST
label_desc: Use image node_id 6 for calling a global function with example usage: parse_args() and returns: parser