code: def get_num_channels(num_channels: int) -> int:
      min_num_channels = 3 * num_channels // 4
      max_num_channels = 5 * num_channels // 4
      return random.randint(min_num_channels, max_num_channels)
  
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 2 for calling a global function with example usage: get_num_channels(num_channels) and returns: random