class_docstr: Random search on the search space.
  
  Parameters
  ----------
  dedup
      Do not try the same configuration twice.
  seed
      Random seed.
class_docstr_tok: ["Random","search","on","the","search","space",".","Parameters","--","--","--","--","--","dedup","Do","not","try","the","same","configuration","twice",".","seed","Random","seed","."]
code: def __init__(
      self, *, dedup: bool = True, seed: int | None = None, **kwargs
  ):
      super().__init__()
  
      if "variational" in kwargs or "model_filter" in kwargs:
          warnings.warn(
              "Variational and model filter are no longer supported in random search and will be removed in future releases.",
              DeprecationWarning,
          )
  
      self._dedup_helper = (
          DeduplicationHelper(raise_on_dup=True) if dedup else None
      )
      self._retry_helper = RetrySamplingHelper(self._duplicate_retry)
  
      self._random_state = RandomState(seed)
  
imports: from __future__ import annotations
  import logging
  import warnings
  from typing import Iterator, Any
  from numpy.random import RandomState
  from nni.mutable import Sample
  from nni.nas.space import ExecutableModelSpace
  from .base import Strategy
  from .utils import DeduplicationHelper, RetrySamplingHelper
label_desc: Use image node_id 1 to create a new Random object from inherited base classes: Strategy with example: obj = Random()