class_docstr: Test suite for algorithm AxOptimizer
class_docstr_tok: ["Test","suite","for","algorithm","AxOptimizer"]
docstr: Test that the seeding gives reproducibile results.
docstr_tok: ["Test","that","the","seeding","gives","reproducibile","results","."]
code: def test_seed_rng_init(self):
      """Test that the seeding gives reproducibile results."""
      config = self.config.copy()
      config["seed"] = 1
      algo = self.create_algo(config=config)
      state = algo.state_dict
  
      first_trial = algo.suggest(1)[0]
      second_trial = algo.suggest(1)[0]
      assert first_trial != second_trial
  
      config = self.config.copy()
      config["seed"] = 2
      new_algo = self.create_algo(config=config)
      new_algo_state = new_algo.state_dict
  
      different_seed_trial = new_algo.suggest(1)[0]
      assert different_seed_trial != first_trial
  
      config = self.config.copy()
      config["seed"] = 1
      new_algo = self.create_algo(config=config)
      same_seed_trial = new_algo.suggest(1)[0]
      assert same_seed_trial == first_trial
  
      numpy.testing.assert_allclose(
          numpy.array(list(first_trial.params.values())).astype(float),
          numpy.array(list(same_seed_trial.params.values())).astype(
              float
          ),
          atol=TOL,
          rtol=TOL,
      )
  
imports: import statistics
  from typing import ClassVar, List
  import pytest
  from orion.algo.axoptimizer import import_optional
  from orion.benchmark.task.base import BenchmarkTask
  from orion.core.utils import backward
  from orion.testing.algo import BaseAlgoTests, TestPhase, first_phase_only
  import numpy
  from botorch.test_functions.multi_objective import BraninCurrin
  from torch import Tensor
label_desc: Use image node_id 4 for calling the TestAxOptimizer obj's underlying member method code with example usage: obj.test_seed_rng_init() without return types