code: def to_pyg_dataset(
      dataset: _typing.Union[
          Dataset, _typing.Iterable[GeneralStaticGraph]
      ]
  ) -> Dataset[torch_geometric.data.Data]:
      transformed_datalist: _typing.MutableSequence[
          torch_geometric.data.Data
      ] = []
      for item in dataset:
          if isinstance(item, torch_geometric.data.Data):
              transformed_datalist.append(item)
          elif isinstance(item, GeneralStaticGraph):
              transformed_datalist.append(
                  conversion.static_graph_to_pyg_data(item)
              )
          elif isinstance(item, _typing.Mapping) and all(
              [
                  (isinstance(k, str) and isinstance(v, torch.Tensor))
                  for k, v in item.items()
              ]
          ):
              transformed_datalist.append(
                  torch_geometric.data.Data(**item)
              )
          else:
              raise NotImplementedError(
                  f"Unsupported data item {type(item)}<{item}> to convert as "
                  f"{torch_geometric.data.Data}"
              )
      return (
          InMemoryDataset(
              transformed_datalist,
              dataset.train_index,
              dataset.val_index,
              dataset.test_index,
              dataset.schema,
          )
          if isinstance(dataset, InMemoryDataset)
          else InMemoryDataset(transformed_datalist)
      )
  
imports: import typing
  import torch
  import torch_geometric
  from autogl.data import Dataset, InMemoryDataset
  from autogl.data.graph import GeneralStaticGraph
  from autogl.data.graph.utils import conversion
label_desc: Use image node_id 1 for calling a global function with example usage: to_pyg_dataset(dataset) and returns: unknown