class_docstr: An algorithm that samples randomly from the problem's space.
  
  Parameters
  ----------
  space: `orion.algo.space.Space`
      Optimisation space with priors for each dimension.
  seed: None, int or sequence of int
      Seed for the random number generator used to sample new trials.
      Default: ``None``
docstr: Seed the state of the random number generator.
  
  :param seed: Integer seed for the random number generator.
code: def seed_rng(self, seed: int | Sequence[int] | None):
      """Seed the state of the random number generator.
  
      :param seed: Integer seed for the random number generator.
      """
      self.rng = numpy.random.RandomState(seed)
  
file_path: orion/src/orion/algo/random/random.py
imports: from __future__ import annotations
  from typing import Sequence
  import numpy
  from orion.algo.base import BaseAlgorithm
  from orion.algo.space import Space
label_desc: Use image node_id 2 for calling the Random obj's underlying member method code with example usage: obj.seed_rng(seed) without return types