class_docstr: The PCQM4Mv2 dataset from the `"OGB-LSC: A Large-Scale Challenge for
  Machine Learning on Graphs" <https://arxiv.org/abs/2103.09430>`_ paper.
  :class:`PCQM4Mv2` is a quantum chemistry dataset originally curated under
  the `PubChemQC project
  <https://pubs.acs.org/doi/10.1021/acs.jcim.7b00083>`_.
  The task is to predict the DFT-calculated HOMO-LUMO energy gap of molecules
  given their 2D molecular graphs.
  
  .. note::
      This dataset uses the :class:`OnDiskDataset` base class to load data
      dynamically from disk.
  
  Args:
      root (str): Root directory where the dataset should be saved.
      split (str, optional): If :obj:`"train"`, loads the training dataset.
          If :obj:`"val"`, loads the validation dataset.
          If :obj:`"test"`, loads the test dataset.
          If :obj:`"holdout"`, loads the holdout dataset.
          (default: :obj:`"train"`)
      transform (callable, optional): A function/transform that takes in an
          :obj:`torch_geometric.data.Data` object and returns a transformed
          version. The data object will be transformed before every access.
          (default: :obj:`None`)
      backend (str): The :class:`Database` backend to use.
          (default: :obj:`"sqlite"`)
code: def serialize(self, data: BaseData) -> Dict[str, Any]:
      assert isinstance(data, Data)
      return dict(
          x=data.x,
          edge_index=data.edge_index,
          edge_attr=data.edge_attr,
          y=data.y,
          smiles=data.smiles,
      )
  
file_path: pytorch_geometric/torch_geometric/datasets/pcqm4m.py
imports: import os
  import os.path
  from typing import Any, Callable, Dict, List, Optional
  import torch
  from tqdm import tqdm
  from torch_geometric.data import Data, OnDiskDataset, download_url, extract_zip
  from torch_geometric.data.data import BaseData
  from torch_geometric.utils import from_smiles
label_desc: Use image node_id 5 for calling the PCQM4Mv2 obj's underlying member method code with example usage: obj.serialize(data) and returns: dict