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