code: def filter_graphs():
      """
      Filter graphs by the min number of nodes
      :return: min number of nodes
      """
      if cfg.dataset.task == "graph":
          min_node = 0
      else:
          min_node = 5
      return min_node
  
imports: import logging
  import pickle
  import time
  import networkx
  import torch
  import torch_geometric.transforms
  from deepsnap.batch import Batch
  from deepsnap.dataset import GraphDataset
  from ogb.graphproppred import PygGraphPropPredDataset
  from torch.utils.data import DataLoader
  from torch_geometric.datasets import PPI, Amazon, Coauthor, KarateClub, MNISTSuperpixels, Planetoid, QM7b, TUDataset
  import graphgym.models.feature_augment
  import graphgym.register
  from graphgym.config import cfg
  from graphgym.models.transform import edge_nets, ego_nets, path_len, remove_node_feature
label_desc: Use image node_id 4 for calling a global function with example usage: filter_graphs() and returns: min_node