code: def run_all():
      data_names = "arxiv citeseer computers cora cs photo physics proteins pubmed".split()
      algos = "graphnas agnn".split()
      results = []
      for data_name in data_names:
          for algo in algos:
              print(f"data {data_name} algo {algo}")
              # metric=run(data_name,algo,2,2)
              if data_name == "proteins":
                  metric = run(data_name, algo, 8, 5)
              else:
                  metric = run(data_name, algo, 50, 10)
              results.append([data_name, algo, metric])
      return results
  
imports: import os
  import logging
  from autogl.backend import DependentBackend
  from autogl.datasets import build_dataset_from_name
  import torch
  from torch import nn
  import torch.nn.functional
  from autogl.module.nas.backend import bk_feat, bk_label
  from autogl.module.nas.algorithm import Darts, RL, GraphNasRL, Enas, RandomSearch, Spos
  from autogl.module.nas.estimator import BaseEstimator
  from autogl.module.train.evaluation import Acc
  import numpy
  from autogl.solver.utils import set_seed
  from autogl.module.nas.space import BaseSpace
  import typing
  from nas_bench_graph import light_read, gnn_list, gnn_list_proteins, Arch
  import pandas
  import argparse
  import os
  import os.path
label_desc: Use image node_id 2 for calling a global function with example usage: run_all() and returns: results