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fix: create auto ml job for tests that based on existing job #1151

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Merged
merged 3 commits into from
Dec 5, 2019
Merged

fix: create auto ml job for tests that based on existing job #1151

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b751d74
fix: create auto ml job for integ tests that based on existing auto m…
Dec 5, 2019
f8b3c37
skip automl tests in unavailable regions
Dec 5, 2019
48ae377
Merge branch 'master' into auto_ml
chuyang-deng Dec 5, 2019
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42 changes: 42 additions & 0 deletions tests/integ/auto_ml_utils.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,42 @@
# Copyright 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
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import os

from sagemaker import AutoML
from tests.integ import DATA_DIR, AUTO_ML_DEFAULT_TIMEMOUT_MINUTES
from tests.integ.timeout import timeout

ROLE = "SageMakerRole"
DATA_DIR = os.path.join(DATA_DIR, "automl", "data")
PREFIX = "sagemaker/beta-automl-xgboost"
TRAINING_DATA = os.path.join(DATA_DIR, "iris_training.csv")
TARGET_ATTRIBUTE_NAME = "virginica"


def create_auto_ml_job_if_not_exist(sagemaker_session):
auto_ml_job_name = "python-sdk-integ-test-base-job"
auto_ml = AutoML(
role=ROLE,
target_attribute_name=TARGET_ATTRIBUTE_NAME,
sagemaker_session=sagemaker_session,
max_candidates=3,
)

try:
auto_ml.describe_auto_ml_job(job_name=auto_ml_job_name)
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Don't fix it as part of this PR, but we should have a session method for this if the base object isn't needed. Feel free to chat in person if I'm missing something.

i.e.:
session.describe_auto_ml_job(job_name)

Meaning that, if we don't need anything from the object, we should just use a session method.

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@chuyang-deng chuyang-deng Dec 5, 2019 •
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Got it! Thanks! Yes a session method doing that makes more sense!

except Exception as e: # noqa: F841
inputs = sagemaker_session.upload_data(path=TRAINING_DATA, key_prefix=PREFIX + "/input")
with timeout(minutes=AUTO_ML_DEFAULT_TIMEMOUT_MINUTES):
auto_ml.fit(inputs, job_name=auto_ml_job_name)
9 changes: 7 additions & 2 deletions tests/integ/test_auto_ml.py
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Expand Up @@ -20,7 +20,7 @@

from sagemaker.exceptions import UnexpectedStatusException
from sagemaker.utils import unique_name_from_base
from tests.integ import DATA_DIR, AUTO_ML_DEFAULT_TIMEMOUT_MINUTES
from tests.integ import DATA_DIR, AUTO_ML_DEFAULT_TIMEMOUT_MINUTES, auto_ml_utils
from tests.integ.timeout import timeout

DEV_ACCOUNT = 142577830533
Expand All @@ -38,7 +38,7 @@
JOB_NAME = "auto-ml-{}".format(time.strftime("%y%m%d-%H%M%S"))

# use a succeeded AutoML job to test describe and list candidates method, otherwise tests will run too long
AUTO_ML_JOB_NAME = "sagemaker-auto-gamma-ml-test"
AUTO_ML_JOB_NAME = "python-sdk-integ-test-base-job"

EXPECTED_DEFAULT_INPUT_CONFIG = [
{
Expand All @@ -62,6 +62,11 @@
}


@pytest.fixture(scope="module", autouse=True)
def create_auto_ml_job_if_not_exist(sagemaker_session):
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what test is using this fixture?

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@chuyang-deng chuyang-deng Dec 5, 2019 •
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This fixture is autouse, all test methods in the class will use this fixture without a need to state it in the test function signature. But now a second thought made me realized not all tests in the class are using this fixture, I will apply it to individual tests.

auto_ml_utils.create_auto_ml_job_if_not_exist(sagemaker_session)


def test_auto_ml_fit(sagemaker_session):
auto_ml = AutoML(
role=ROLE,
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