class_docstr: A naive tuner that generates fully random hyperparameters.
  
  Examples
  --------
  
  .. code-block::
  
      config.tuner.name = 'Random'
      config.tuner.class_args = {
          'seed': 100
      }
  
  Parameters
  ----------
  seed
      The random seed.
class_docstr_tok: ["A","naive","tuner","that","generates","fully","random","hyperparameters",".","Examples","--","--","--","--","..","code-block",":",":","config.tuner.name","=","'Random'","config.tuner.class_args","=","{","'seed","'",":","100","}","Parameters","--","--","--","--","--","seed","The","random","seed","."]
code: def update_search_space(self, space):
      self.space = format_search_space(space)
      self.dedup = Deduplicator(self.space)
  
file_path: nni/nni/algorithms/hpo/random_tuner.py
imports: from __future__ import annotations
  import logging
  import numpy
  import schema
  from nni import ClassArgsValidator
  from nni.common.hpo_utils import Deduplicator, format_search_space, deformat_parameters
  from nni.tuner import Tuner
label_desc: Use image node_id 2 for calling the RandomTuner obj's underlying member method code with example usage: obj.update_search_space(space) without return types