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()
