def test_marketplace_tuning_job(sagemaker_session, cpu_instance_type):
data_path = os.path.join(DATA_DIR, "marketplace", "training")
region = sagemaker_session.boto_region_name
account = REGION_ACCOUNT_MAP[region]
algorithm_arn = ALGORITHM_ARN % (region, account)
mktplace = AlgorithmEstimator(
algorithm_arn=algorithm_arn,
role="SageMakerRole",
train_instance_count=1,
train_instance_type=cpu_instance_type,
sagemaker_session=sagemaker_session,
base_job_name="test-marketplace",
)
train_input = mktplace.sagemaker_session.upload_data(
path=data_path, key_prefix="integ-test-data/marketplace/train")
mktplace.set_hyperparameters(max_leaf_nodes=10)
hyperparameter_ranges = {"max_leaf_nodes": IntegerParameter(1, 100000)}
tuner = HyperparameterTuner(
estimator=mktplace,
base_tuning_job_name="byo",
objective_metric_name="validation:accuracy",
hyperparameter_ranges=hyperparameter_ranges,
max_jobs=2,
max_parallel_jobs=2,
)
tuner.fit({"training": train_input}, include_cls_metadata=False)
time.sleep(15)
tuner.wait()
def test_marketplace_tuning_job(sagemaker_session):
data_path = os.path.join(DATA_DIR, 'marketplace', 'training')
region = sagemaker_session.boto_region_name
account = REGION_ACCOUNT_MAP[region]
algorithm_arn = ALGORITHM_ARN % (region, account)
mktplace = AlgorithmEstimator(algorithm_arn=algorithm_arn,
role='SageMakerRole',
train_instance_count=1,
train_instance_type='ml.c4.xlarge',
sagemaker_session=sagemaker_session,
base_job_name='test-marketplace')
train_input = mktplace.sagemaker_session.upload_data(
path=data_path, key_prefix='integ-test-data/marketplace/train')
mktplace.set_hyperparameters(max_leaf_nodes=10)
hyperparameter_ranges = {'max_leaf_nodes': IntegerParameter(1, 100000)}
tuner = HyperparameterTuner(estimator=mktplace,
base_tuning_job_name='byo',
objective_metric_name='validation:accuracy',
hyperparameter_ranges=hyperparameter_ranges,
max_jobs=2,
max_parallel_jobs=2)
tuner.fit({'training': train_input}, include_cls_metadata=False)
time.sleep(15)
tuner.wait()
