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fix: use unique job name in hyperparameter tuning test #829

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Jun 5, 2019
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7 changes: 4 additions & 3 deletions tests/integ/test_tuner.py
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# Copyright 2017-2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
Expand Down Expand Up @@ -60,7 +60,7 @@ def kmeans_train_set(sagemaker_session):
def kmeans_estimator(sagemaker_session):
kmeans = KMeans(role='SageMakerRole', train_instance_count=1,
train_instance_type='ml.c4.xlarge',
k=10, sagemaker_session=sagemaker_session, base_job_name='tk',
k=10, sagemaker_session=sagemaker_session,
output_path='s3://{}/'.format(sagemaker_session.default_bucket()))
# set kmeans specific hp
kmeans.init_method = 'random'
Expand Down Expand Up @@ -137,8 +137,9 @@ def test_tuning_kmeans(sagemaker_session,
kmeans_train_set,
kmeans_estimator,
hyperparameter_ranges):
job_name = unique_name_from_base('test-tune-kmeans')
_tune_and_deploy(kmeans_estimator, kmeans_train_set, sagemaker_session,
hyperparameter_ranges=hyperparameter_ranges)
hyperparameter_ranges=hyperparameter_ranges, job_name=job_name)


def test_tuning_kmeans_identical_dataset_algorithm_tuner_raw(sagemaker_session,
Expand Down