code: def get_dataset(name, root, use_sparse_tensor=False, bf16=False):
      data, num_classes, _ = get_dataset_with_transformation(
          name, root, use_sparse_tensor, bf16
      )
      return data, num_classes
  
file_path: pytorch_geometric/benchmark/utils/utils.py
imports: import os
  import os.path
  from datetime import datetime
  import torch
  from ogb.nodeproppred import PygNodePropPredDataset
  from tqdm import tqdm
  import torch_geometric.transforms
  from torch_geometric.data import HeteroData
  from torch_geometric.datasets import OGB_MAG, Reddit
  from torch_geometric.nn import GAT, GCN, PNA, EdgeCNN, GraphSAGE
  from torch_geometric.utils import index_to_mask
  from .hetero_gat import HeteroGAT
  from .hetero_sage import HeteroGraphSAGE
label_desc: Use image node_id 2 for calling a global function with example usage: get_dataset(name, root, use_sparse_tensor, bf16) and returns: data,  num_classes