add canary tests for tf serving container (#478)

* add canary tests for tf serving container

Author: jesterhazy

tests/integ/__init__.py

@@ -25,5 +25,9 @@
 PYTHON_VERSION = 'py' + str(sys.version_info.major)
 REGION = boto3.session.Session().region_name
 
+HOSTING_P2_UNAVAILABLE_REGIONS = ['ca-central-1', 'us-west-1', 'eu-west-2']
+HOSTING_P3_UNAVAILABLE_REGIONS = ['ap-southeast-1', 'ap-southeast-2', 'ap-south-1', 'ca-central-1',
+                                  'us-west-1']
+
 logging.getLogger('boto3').setLevel(logging.INFO)
 logging.getLogger('botocore').setLevel(logging.INFO)

tests/integ/test_tfs.py

@@ -17,8 +17,9 @@
 import sagemaker
 import sagemaker.predictor
 import sagemaker.utils
+import tests.integ
+import tests.integ.timeout
 from sagemaker.tensorflow.serving import Model, Predictor
-from tests.integ.timeout import timeout_and_delete_endpoint_by_name
 
 
 @pytest.fixture(scope='session', params=['ml.c5.xlarge', 'ml.p3.2xlarge'])
@@ -32,17 +33,21 @@ def tfs_predictor(instance_type, sagemaker_session, tf_full_version):
     model_data = sagemaker_session.upload_data(
         path='tests/data/tensorflow-serving-test-model.tar.gz',
         key_prefix='tensorflow-serving/models')
-    with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
+    with tests.integ.timeout.timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
         model = Model(model_data=model_data, role='SageMakerRole',
                       framework_version=tf_full_version,
                       sagemaker_session=sagemaker_session)
         predictor = model.deploy(1, instance_type, endpoint_name=endpoint_name)
         yield predictor
 
 
-# @pytest.mark.continuous_testing
-# @pytest.mark.regional_testing
-def test_predict(tfs_predictor):
+@pytest.mark.continuous_testing
+@pytest.mark.regional_testing
+def test_predict(tfs_predictor, instance_type):
+    if ('p3' in instance_type) and (
+            tests.integ.REGION in tests.integ.HOSTING_P3_UNAVAILABLE_REGIONS):
+        pytest.skip('no ml.p3 instances in this region')
+
     input_data = {'instances': [1.0, 2.0, 5.0]}
     expected_result = {'predictions': [3.5, 4.0, 5.5]}