def test_hyperparameter_tuning_objective(): obj = hpo_job.HyperparameterTuningObjective( objective_type=hpo_job.HyperparameterTuningObjectiveType.MAXIMIZE, metric_name="test_metric" ) obj2 = hpo_job.HyperparameterTuningObjective.from_flyte_idl(obj.to_flyte_idl()) assert obj == obj2
def test_hyperparameter_job_config(): jc = hpo_job.HyperparameterTuningJobConfig( hyperparameter_ranges=parameter_ranges.ParameterRanges( parameter_range_map={ "a": parameter_ranges.CategoricalParameterRange(values=["1", "2"]), "b": parameter_ranges.IntegerParameterRange( min_value=0, max_value=10, scaling_type=parameter_ranges.HyperparameterScalingType. LINEAR), }), tuning_strategy=hpo_job.HyperparameterTuningStrategy.BAYESIAN, tuning_objective=hpo_job.HyperparameterTuningObjective( objective_type=hpo_job.HyperparameterTuningObjectiveType.MAXIMIZE, metric_name="test_metric"), training_job_early_stopping_type=hpo_job.TrainingJobEarlyStoppingType. AUTO, ) jc2 = hpo_job.HyperparameterTuningJobConfig.from_flyte_idl( jc.to_flyte_idl()) assert jc2.hyperparameter_ranges == jc.hyperparameter_ranges assert jc2.tuning_strategy == jc.tuning_strategy assert jc2.tuning_objective == jc.tuning_objective assert jc2.training_job_early_stopping_type == jc.training_job_early_stopping_type
def test_hyperparameter_job_config(): jc = hpo_job.HyperparameterTuningJobConfig( tuning_strategy=hpo_job.HyperparameterTuningStrategy.BAYESIAN, tuning_objective=hpo_job.HyperparameterTuningObjective( objective_type=hpo_job.HyperparameterTuningObjectiveType.MAXIMIZE, metric_name="test_metric" ), training_job_early_stopping_type=hpo_job.TrainingJobEarlyStoppingType.AUTO, ) jc2 = hpo_job.HyperparameterTuningJobConfig.from_flyte_idl(jc.to_flyte_idl()) assert jc2.tuning_strategy == jc.tuning_strategy assert jc2.tuning_objective == jc.tuning_objective assert jc2.training_job_early_stopping_type == jc.training_job_early_stopping_type