def test_marketplace_transform_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.format(partition=_aws_partition(region), region=region, account=account) algo = 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 = algo.sagemaker_session.upload_data( path=data_path, key_prefix="integ-test-data/marketplace/train") shape = pandas.read_csv(data_path + "/iris.csv", header=None).drop([0], axis=1) transform_workdir = DATA_DIR + "/marketplace/transform" shape.to_csv(transform_workdir + "/batchtransform_test.csv", index=False, header=False) transform_input = algo.sagemaker_session.upload_data( transform_workdir, key_prefix="integ-test-data/marketplace/transform") algo.fit({"training": train_input}) transformer = algo.transformer(1, cpu_instance_type) transformer.transform(transform_input, content_type="text/csv") transformer.wait()
def test_marketplace_transform_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) algo = 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 = algo.sagemaker_session.upload_data( path=data_path, key_prefix='integ-test-data/marketplace/train') shape = pandas.read_csv(data_path + '/iris.csv', header=None).drop([0], axis=1) transform_workdir = DATA_DIR + '/marketplace/transform' shape.to_csv(transform_workdir + '/batchtransform_test.csv', index=False, header=False) transform_input = algo.sagemaker_session.upload_data( transform_workdir, key_prefix='integ-test-data/marketplace/transform') algo.fit({'training': train_input}) transformer = algo.transformer(1, 'ml.m4.xlarge') transformer.transform(transform_input, content_type='text/csv') transformer.wait()