code: def __init__(self, dataset, labels, indices):
      dataset = [dataset[idx] for idx in indices]
      labels = [labels[idx] for idx in indices]
      self.dataset, self.labels = [], []
      for i, g in enumerate(dataset):
          if g.num_nodes() > 5:
              self.dataset.append(g)
              self.labels.append(labels[i])
      self.len = len(self.dataset)
  
imports: import argparse
  import random
  import dgl
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from dgl.dataloading import GraphDataLoader
  from ogb.graphproppred import Evaluator
  from ogb.graphproppred.mol_encoder import AtomEncoder
  from preprocessing import prepare_dataset
  from torch.utils.data import Dataset
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new Subset object from inherited base classes: object with example: obj = Subset(dataset, labels, indices)