code: def __iter__(self) -> Iterator:
      for d in self.dp:
          if isinstance(d, str):
              data = from_smiles(d)
          elif isinstance(d, dict):
              data = from_smiles(d[self.smiles_key])
              if self.target_key is not None:
                  y = d.get(self.target_key, None)
                  if y is not None:
                      y = float(y) if len(y) > 0 else float("NaN")
                      data.y = torch.tensor([y], dtype=torch.float)
          else:
              raise ValueError(
                  f"'{self.__class__.__name__}' expected either a string or "
                  f"a dict as input (got '{type(d)}')"
              )
  
          yield data
  
imports: import copy
  from typing import Any, Callable, Iterator, Optional, Sequence
  import torch
  from torch_geometric.data import Batch
  from torch_geometric.utils import from_smiles
label_desc: Use image node_id 2 for calling the SMILESParser obj's underlying member method code with example usage: obj.__iter__() without return types