code: def test_float_optimization(tmp_path):
      class PolynomialTuner(keras_tuner.engine.base_tuner.BaseTuner):
          def run_trial(self, trial):
              hp = trial.hyperparameters
              return (
                  -1 * hp["a"] ** 3
                  + hp["b"] ** 3
                  + hp["c"]
                  - abs(hp["d"])
              )
  
      hps = hp_module.HyperParameters()
      hps.Float("a", -1, 1)
      hps.Float("b", -1, 1)
      hps.Float("c", -1, 1)
      hps.Float("d", -1, 1)
  
      tuner = PolynomialTuner(
          oracle=keras_tuner.oracles.BayesianOptimizationOracle(
              objective=keras_tuner.Objective("score", "max"),
              hyperparameters=hps,
              max_trials=50,
          ),
          directory=tmp_path,
      )
  
      tuner.search()
  
      atol, rtol = 1e-1, 1e-1
      best_trial = tuner.oracle.get_best_trials()[0]
      best_hps = best_trial.hyperparameters
  
      assert np.isclose(best_trial.score, 3, atol=atol, rtol=rtol)
      assert np.isclose(best_hps["a"], -1, atol=atol, rtol=rtol)
      assert np.isclose(best_hps["b"], 1, atol=atol, rtol=rtol)
      assert np.isclose(best_hps["c"], 1, atol=atol, rtol=rtol)
      assert np.isclose(best_hps["d"], 0, atol=atol, rtol=rtol)
  
imports: import math
  import numpy
  import pytest
  import keras_tuner
  from keras_tuner.backend import keras
  from keras_tuner.engine import hyperparameters
  from keras_tuner.engine import trial
  from keras_tuner.tuners import bayesian
label_desc: Use image node_id 14 for calling a global function with example usage: test_float_optimization(tmp_path) and returns: unknown