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: Reset the state of the algorithm based on the given state_dict
  
  :param state_dict: Dictionary representing state of an algorithm
code: def set_state(self, state_dict):
      """Reset the state of the algorithm based on the given state_dict
  
      :param state_dict: Dictionary representing state of an algorithm
      """
      super().set_state(state_dict)
      self.seed_rng(0)
      self.rng.set_state(state_dict["rng_state"])
  
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 4 for calling the Random obj's underlying member method code with example usage: obj.set_state(state_dict) without return types