code: def get_products(root: str) -> Tuple[Data, int, int]:
      dataset = PygNodePropPredDataset(
          "ogbn-products",
          f"{root}/OGB",
          pre_transform=T.ToSparseTensor(),
      )
      data = dataset[0]
      data.y = data.y.view(-1)
      split_idx = dataset.get_idx_split()
      data.train_mask = index2mask(split_idx["train"], data.num_nodes)
      data.val_mask = index2mask(split_idx["valid"], data.num_nodes)
      data.test_mask = index2mask(split_idx["test"], data.num_nodes)
      return data, dataset.num_features, dataset.num_classes
  
file_path: DIG/dig/lsgraph/dataset/get_data.py
imports: from typing import Tuple
  import torch
  from torch import Tensor
  import torch_geometric.transforms
  from torch_geometric.data import Data, Batch
  from torch_geometric.datasets import GNNBenchmarkDataset, Yelp, Flickr, Reddit2
  from ogb.nodeproppred import PygNodePropPredDataset
label_desc: Use image node_id 3 for calling a global function with example usage: get_products(root) and returns: data,  dataset,  dataset