code: def get_num_nodes(avg_num_nodes: int, avg_degree: float) -> int:
      min_num_nodes = max(3 * avg_num_nodes // 4, int(avg_degree))
      max_num_nodes = 5 * avg_num_nodes // 4
      return random.randint(min_num_nodes, max_num_nodes)
  
file_path: pytorch_geometric/torch_geometric/datasets/fake.py
imports: import random
  from collections import defaultdict
  from itertools import product
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import torch
  from torch import Tensor
  from torch_geometric.data import Data, HeteroData, InMemoryDataset
  from torch_geometric.utils import coalesce, remove_self_loops, to_undirected
label_desc: Use image node_id 1 for calling a global function with example usage: get_num_nodes(avg_num_nodes, avg_degree) and returns: random