code: def test_datapipe_parse_smiles():
      smiles = "F/C=C/F"
  
      dp = DatasetAdapter([smiles])
      dp = dp.parse_smiles()
      assert to_smiles(next(iter(dp))) == smiles
  
      dp = DatasetAdapter([{"abc": smiles, "cba": "1.0"}])
      dp = dp.parse_smiles(smiles_key="abc", target_key="cba")
      assert to_smiles(next(iter(dp))) == smiles
  
file_path: pytorch_geometric/test/data/test_datapipes.py
imports: import pytest
  import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import DatasetAdapter
  from torch_geometric.loader import DataLoader
  from torch_geometric.testing import withPackage
  from torch_geometric.utils import to_smiles
label_desc: Use image node_id 5 for calling a global function with example usage: test_datapipe_parse_smiles() without return types