code: def oneshot1(
      seed: tp.Optional[int] = None,
  ) -> tp.Iterator[Experiment]:
      """Comparing one-shot optimizers as initializers for Bayesian Optimization."""
      seedg = create_seed_generator(seed)
      for budget in [
          25,
          31,
          37,
          43,
          50,
          60,
      ]:  # , 4000, 8000, 16000, 32000]:
          for optim in sorted(
              x for x, y in optimizers.registry.items() if "BO" in x
          ):
              for rotation in [False]:
                  for d in [20]:
                      for name in [
                          "sphere",
                          "cigar",
                          "hm",
                          "ellipsoid",
                      ]:  # , "hm"]:
                          for u in [0]:
                              function = ArtificialFunction(
                                  name=name,
                                  rotation=rotation,
                                  block_dimension=d,
                                  useless_variables=d * u,
                                  translation_factor=1.0,
                              )
                              yield Experiment(
                                  function,
                                  optim,
                                  budget=budget,
                                  seed=next(seedg),
                              )
  
imports: import typing
  import numpy
  from nevergrad import optimizers
  from nevergrad.optimization.base import ConfiguredOptimizer
  from nevergrad.optimization import experimentalvariants
  from nevergrad.functions import ArtificialFunction
  from .xpbase import registry
  from .xpbase import create_seed_generator
  from .xpbase import Experiment
label_desc: Use image node_id 13 for calling a global function with example usage: oneshot1(seed) without return types