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()