code: def __init__(
      self,
      dimension: int,
      budget: tp.Optional[int] = None,
      scrambling: bool = False,
      random_state: tp.Optional[RandomState] = None,
  ) -> None:
      super().__init__(dimension, budget, random_state=random_state)
      self.permgen = HaltonPermutationGenerator(
          dimension, scrambling, random_state=random_state
      )
  
imports: import numpy
  from numpy.random import RandomState
  import nevergrad.common.typing
  from nevergrad.common.decorators import Registry
label_desc: Use image node_id 1 to create a new HaltonSampler object from inherited base classes: Sampler with example: obj = HaltonSampler(dimension, budget, scrambling, random_state)