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Merged
merged 2 commits into from
May 4, 2018
Merged

Mark tests for continuous testing #167

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06e4eb7
Mark tests for continuous testing
laurenyu May 4, 2018
94643d7
Switch which MXNet test to run for continuous testing
laurenyu May 4, 2018
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1 change: 1 addition & 0 deletions tests/integ/test_byo_estimator.py
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Expand Up @@ -42,6 +42,7 @@ def fm_serializer(data):
return json.dumps(js)


@pytest.mark.continuous_testing
def test_byo_estimator(sagemaker_session, region):
"""Use Factorization Machines algorithm as an example here.

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3 changes: 3 additions & 0 deletions tests/integ/test_factorization_machines.py
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Expand Up @@ -16,12 +16,15 @@
import sys
import time

import pytest

from sagemaker import FactorizationMachines, FactorizationMachinesModel
from sagemaker.utils import name_from_base
from tests.integ import DATA_DIR
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name


@pytest.mark.continuous_testing
def test_factorization_machines(sagemaker_session):
with timeout(minutes=15):
data_path = os.path.join(DATA_DIR, 'one_p_mnist', 'mnist.pkl.gz')
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3 changes: 3 additions & 0 deletions tests/integ/test_kmeans.py
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Expand Up @@ -16,12 +16,15 @@
import sys
import time

import pytest

from sagemaker import KMeans, KMeansModel
from sagemaker.utils import name_from_base
from tests.integ import DATA_DIR
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name


@pytest.mark.continuous_testing
def test_kmeans(sagemaker_session):
with timeout(minutes=15):
data_path = os.path.join(DATA_DIR, 'one_p_mnist', 'mnist.pkl.gz')
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2 changes: 2 additions & 0 deletions tests/integ/test_lda.py
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Expand Up @@ -13,6 +13,7 @@
import os

import numpy as np
import pytest

from sagemaker import LDA, LDAModel
from sagemaker.amazon.common import read_records
Expand All @@ -22,6 +23,7 @@
from tests.integ.record_set import prepare_record_set_from_local_files


@pytest.mark.continuous_testing
def test_lda(sagemaker_session):
with timeout(minutes=15):
data_path = os.path.join(DATA_DIR, 'lda')
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2 changes: 2 additions & 0 deletions tests/integ/test_linear_learner.py
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Expand Up @@ -17,13 +17,15 @@
import time

import numpy as np
import pytest

from sagemaker.amazon.linear_learner import LinearLearner, LinearLearnerModel
from sagemaker.utils import name_from_base, sagemaker_timestamp
from tests.integ import DATA_DIR
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name


@pytest.mark.continuous_testing
def test_linear_learner(sagemaker_session):
with timeout(minutes=15):
data_path = os.path.join(DATA_DIR, 'one_p_mnist', 'mnist.pkl.gz')
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1 change: 1 addition & 0 deletions tests/integ/test_mxnet_train.py
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Expand Up @@ -52,6 +52,7 @@ def test_attach_deploy(mxnet_training_job, sagemaker_session):
predictor.predict(data)


@pytest.mark.continuous_testing
def test_deploy_model(mxnet_training_job, sagemaker_session):
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@nadiaya nadiaya May 4, 2018

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why that one?

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@laurenyu laurenyu May 4, 2018

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I think it tests a more straightforward code path than test_attach_deploy, though I could be persuaded to pick the other one since our TF test already tests the "straightforward" approach.

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@laurenyu laurenyu May 4, 2018

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talked offline - will switch to test_attach_deploy since deploying through the estimator rather than creating a separate model object is probably more common

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@nadiaya nadiaya May 4, 2018

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It doesn't really matter, i just find this test to be more unnatural, that's why was curious about the choice process :)
Approved.

endpoint_name = 'test-mxnet-deploy-model-{}'.format(sagemaker_timestamp())

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2 changes: 2 additions & 0 deletions tests/integ/test_ntm.py
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Expand Up @@ -13,6 +13,7 @@
import os

import numpy as np
import pytest

from sagemaker import NTM, NTMModel
from sagemaker.amazon.common import read_records
Expand All @@ -22,6 +23,7 @@
from tests.integ.record_set import prepare_record_set_from_local_files


@pytest.mark.continuous_testing
def test_ntm(sagemaker_session):
with timeout(minutes=15):
data_path = os.path.join(DATA_DIR, 'ntm')
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3 changes: 3 additions & 0 deletions tests/integ/test_pca.py
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Expand Up @@ -16,12 +16,15 @@
import sys
import time

import pytest

import sagemaker.amazon.pca
from sagemaker.utils import name_from_base
from tests.integ import DATA_DIR
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name


@pytest.mark.continuous_testing
def test_pca(sagemaker_session):
with timeout(minutes=15):
data_path = os.path.join(DATA_DIR, 'one_p_mnist', 'mnist.pkl.gz')
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2 changes: 2 additions & 0 deletions tests/integ/test_randomcutforest.py
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Expand Up @@ -11,12 +11,14 @@
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
import numpy as np
import pytest

from sagemaker import RandomCutForest, RandomCutForestModel
from sagemaker.utils import name_from_base
from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name


@pytest.mark.continuous_testing
def test_randomcutforest(sagemaker_session):
with timeout(minutes=15):
# Generate a thousand 14-dimensional datapoints.
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1 change: 1 addition & 0 deletions tests/integ/test_tf.py
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Expand Up @@ -22,6 +22,7 @@
DATA_PATH = os.path.join(DATA_DIR, 'iris', 'data')


@pytest.mark.continuous_testing
def test_tf(sagemaker_session, tf_full_version):
with timeout(minutes=15):
script_path = os.path.join(DATA_DIR, 'iris', 'iris-dnn-classifier.py')
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