code: def from_dataset_name(
      cls,
      name: str,
      num_trials: int,
      infer_noise: bool = True,
  ) -> "PyTorchCNNTorchvisionBenchmarkProblem":
      if name not in _REGISTRY:
          raise UserInputError(
              f"Unrecognized torchvision dataset {name}. Please ensure it is listed"
              "in PyTorchCNNTorchvisionBenchmarkProblem registry."
          )
      dataset_fn = _REGISTRY[name]
  
      train_set = dataset_fn(
          root="./data",
          train=True,
          download=True,
          transform=transforms.ToTensor(),
      )
  
      test_set = dataset_fn(
          root="./data",
          train=False,
          download=True,
          transform=transforms.ToTensor(),
      )
  
      problem = cls.from_datasets(
          name=name,
          num_trials=num_trials,
          train_set=train_set,
          test_set=test_set,
          infer_noise=infer_noise,
      )
      runner = PyTorchCNNTorchvisionRunner(
          name=name, train_set=train_set, test_set=test_set
      )
  
      return cls(
          name=f"HPO_PyTorchCNN_Torchvision::{name}",
          search_space=problem.search_space,
          optimization_config=problem.optimization_config,
          runner=runner,
          num_trials=num_trials,
          infer_noise=infer_noise,
          optimal_value=problem.optimal_value,
      )
  
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 PyTorchCNNTorchvisionBenchmarkProblem obj's underlying member method code with example usage: obj.from_dataset_name(cls, name, num_trials, infer_noise) and returns: cls