code: def parse_args():
      parser = argparse.ArgumentParser(
          description="OGBL-Citation2 (GraphBolt)"
      )
      parser.add_argument("--epochs", type=int, default=10)
      parser.add_argument("--lr", type=float, default=0.0005)
      parser.add_argument("--neg-ratio", type=int, default=1)
      parser.add_argument("--train-batch-size", type=int, default=512)
      parser.add_argument("--eval-batch-size", type=int, default=1024)
      parser.add_argument("--num-workers", type=int, default=0)
      parser.add_argument(
          "--early-stop",
          type=int,
          default=0,
          help="0 means no early stop, otherwise stop at the input-th step",
      )
      parser.add_argument(
          "--fanout",
          type=str,
          default="15,10,5",
          help="Fan-out of neighbor sampling. Default: 15,10,5",
      )
      parser.add_argument(
          "--exclude-edges",
          type=int,
          default=1,
          help="Whether to exclude reverse edges during sampling. Default: 1",
      )
      parser.add_argument(
          "--mode",
          default="pinned-cuda",
          choices=["cpu-cpu", "cpu-cuda", "pinned-cuda", "cuda-cuda"],
          help="Dataset storage placement and Train device: 'cpu' for CPU and RAM,"
          " 'pinned' for pinned memory in RAM, 'cuda' for GPU and GPU memory.",
      )
      return parser.parse_args()
  
imports: import argparse
  import time
  from functools import partial
  import dgl.graphbolt
  import dgl.nn
  import torch
  import torch.nn
  import torch.nn.functional
  import tqdm
  from ogb.linkproppred import Evaluator
label_desc: Use image node_id 5 for calling a global function with example usage: parse_args() and returns: parser