code: def __init__(self, data_name, loss_f="nll_loss", evaluation=[Acc()]):
      super().__init__(loss_f, evaluation)
      self.evaluation = evaluation
      self.bench = light_read(data_name)
  
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 1 to create a new BenchEstimator object from inherited base classes: BaseEstimator with example: obj = BenchEstimator(data_name, loss_f, evaluation)