class_docstr: A subclass to aid in serialization. This allows us to save only the name of the
  dataset and reload it from TorchVision at deserialization time.
class_docstr_tok: ["A","subclass","to","aid","in","serialization",".","This","allows","us","to","save","only","the","name","of","the","dataset","and","reload","it","from","TorchVision","at","deserialization","time","."]
code: def serialize_init_args(cls, obj: Any) -> Dict[str, Any]:
      pytorch_cnn_runner = checked_cast(PyTorchCNNRunner, obj)
  
      return {"name": pytorch_cnn_runner.name}
  
file_path: Ax/ax/benchmark/problems/hpo/torchvision.py
imports: import os
  from typing import Any, Dict, Optional
  from ax.benchmark.problems.hpo.pytorch_cnn import PyTorchCNNBenchmarkProblem, PyTorchCNNRunner
  from ax.exceptions.core import UserInputError
  from ax.utils.common.serialization import TClassDecoderRegistry, TDecoderRegistry
  from ax.utils.common.typeutils import checked_cast
  from torch.utils.data import TensorDataset
label_desc: Use image node_id 1 for calling the PyTorchCNNTorchvisionRunner obj's underlying member method code with example usage: obj.serialize_init_args(cls, obj) and returns: dict