Do not run tensorflow integ tests when running python 3 since we do not have python 3 image for tensorflow.

Author: nadiaya

tests/integ/__init__.py

@@ -14,10 +14,12 @@
 
 import logging
 import os
+import sys
 
 DATA_DIR = os.path.join(os.path.dirname(__file__), '..', 'data')
 TRAINING_DEFAULT_TIMEOUT_MINUTES = 20
 TUNING_DEFAULT_TIMEOUT_MINUTES = 20
+PYTHON_VERSION = 'py' + str(sys.version_info.major)
 
 logging.getLogger('boto3').setLevel(logging.INFO)
 logging.getLogger('botocore').setLevel(logging.INFO)

tests/integ/test_tf.py

@@ -18,7 +18,7 @@
 import pytest
 
 from sagemaker.tensorflow import TensorFlow
-from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
+from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES, PYTHON_VERSION
 from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
 from tests.integ.vpc_utils import get_or_create_subnet_and_security_group
 
@@ -27,6 +27,7 @@
 
 
 @pytest.mark.continuous_testing
+@pytest.mark.skipif(PYTHON_VERSION != 'py2', reason="TensorFlow image supports only python 2.")
 def test_tf(sagemaker_session, tf_full_version):
     with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
         script_path = os.path.join(DATA_DIR, 'iris', 'iris-dnn-classifier.py')
@@ -60,6 +61,7 @@ def test_tf(sagemaker_session, tf_full_version):
         assert dict_result == list_result
 
 
+@pytest.mark.skipif(PYTHON_VERSION != 'py2', reason="TensorFlow image supports only python 2.")
 def test_tf_async(sagemaker_session):
     with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
         script_path = os.path.join(DATA_DIR, 'iris', 'iris-dnn-classifier.py')
@@ -89,6 +91,7 @@ def test_tf_async(sagemaker_session):
         print('predict result: {}'.format(result))
 
 
+@pytest.mark.skipif(PYTHON_VERSION != 'py2', reason="TensorFlow image supports only python 2.")
 def test_failed_tf_training(sagemaker_session, tf_full_version):
     with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
         script_path = os.path.join(DATA_DIR, 'iris', 'failure_script.py')

tests/integ/test_tf_cifar.py

@@ -19,7 +19,7 @@
 import pytest
 
 from sagemaker.tensorflow import TensorFlow
-from tests.integ import DATA_DIR
+from tests.integ import DATA_DIR, PYTHON_VERSION
 from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
 
 PICKLE_CONTENT_TYPE = 'application/python-pickle'
@@ -34,6 +34,7 @@ def __call__(self, data):
 
 
 @pytest.mark.continuous_testing
+@pytest.mark.skipif(PYTHON_VERSION != 'py2', reason="TensorFlow image supports only python 2.")
 def test_cifar(sagemaker_session, tf_full_version):
     with timeout(minutes=45):
         script_path = os.path.join(DATA_DIR, 'cifar_10', 'source')

tests/integ/test_tf_keras.py

@@ -18,11 +18,12 @@
 import pytest
 
 from sagemaker.tensorflow import TensorFlow
-from tests.integ import DATA_DIR
+from tests.integ import DATA_DIR, PYTHON_VERSION
 from tests.integ.timeout import timeout_and_delete_endpoint_by_name, timeout
 
 
 @pytest.mark.continuous_testing
+@pytest.mark.skipif(PYTHON_VERSION != 'py2', reason="TensorFlow image supports only python 2.")
 def test_keras(sagemaker_session, tf_full_version):
     script_path = os.path.join(DATA_DIR, 'cifar_10', 'source')
     dataset_path = os.path.join(DATA_DIR, 'cifar_10', 'data')

tests/unit/test_pytorch.py

@@ -24,15 +24,14 @@
 from sagemaker.pytorch import PyTorch
 from sagemaker.pytorch import PyTorchPredictor, PyTorchModel
 
+from tests.integ import DATA_DIR, PYTHON_VERSION
 
-DATA_DIR = os.path.join(os.path.dirname(__file__), '..', 'data')
 SCRIPT_PATH = os.path.join(DATA_DIR, 'dummy_script.py')
 TIMESTAMP = '2017-11-06-14:14:15.672'
 TIME = 1507167947
 BUCKET_NAME = 'mybucket'
 INSTANCE_COUNT = 1
 INSTANCE_TYPE = 'ml.c4.4xlarge'
-PYTHON_VERSION = 'py' + str(sys.version_info.major)
 IMAGE_NAME = 'sagemaker-pytorch'
 JOB_NAME = '{}-{}'.format(IMAGE_NAME, TIMESTAMP)
 IMAGE_URI_FORMAT_STRING = "520713654638.dkr.ecr.{}.amazonaws.com/{}:{}-{}-{}"