allow ei versions to be configurable in integ test (#639)

Author: ChoiByungWook

tests/conftest.py

@@ -37,13 +37,15 @@ def pytest_addoption(parser):
     parser.addoption('--boto-config', action='store', default=None)
     parser.addoption('--chainer-full-version', action='store', default=Chainer.LATEST_VERSION)
     parser.addoption('--mxnet-full-version', action='store', default=MXNet.LATEST_VERSION)
+    parser.addoption('--ei-mxnet-full-version', action='store', default=MXNet.LATEST_VERSION)
     parser.addoption('--pytorch-full-version', action='store', default=PyTorch.LATEST_VERSION)
     parser.addoption('--rl-coach-full-version', action='store',
                      default=RLEstimator.COACH_LATEST_VERSION)
     parser.addoption('--rl-ray-full-version', action='store',
                      default=RLEstimator.RAY_LATEST_VERSION)
     parser.addoption('--sklearn-full-version', action='store', default=SKLEARN_VERSION)
     parser.addoption('--tf-full-version', action='store', default=TensorFlow.LATEST_VERSION)
+    parser.addoption('--ei-tf-full-version', action='store', default=TensorFlow.LATEST_VERSION)
 
 
 def pytest_configure(config):
@@ -109,11 +111,6 @@ def mxnet_version(request):
     return request.param
 
 
-@pytest.fixture(scope='module', params=['1.3', '1.3.0'])
-def ei_mxnet_version(request):
-    return request.param
-
-
 @pytest.fixture(scope='module', params=['0.4', '0.4.0', '1.0', '1.0.0'])
 def pytorch_version(request):
     return request.param
@@ -131,11 +128,6 @@ def tf_version(request):
     return request.param
 
 
-@pytest.fixture(scope='module', params=['1.12', '1.12.0'])
-def ei_tf_version(request):
-    return request.param
-
-
 @pytest.fixture(scope='module', params=['0.10.1', '0.10.1', '0.11', '0.11.0'])
 def rl_coach_tf_version(request):
     return request.param
@@ -161,6 +153,11 @@ def mxnet_full_version(request):
     return request.config.getoption('--mxnet-full-version')
 
 
+@pytest.fixture(scope='module')
+def ei_mxnet_full_version(request):
+    return request.config.getoption('--ei-mxnet-full-version')
+
+
 @pytest.fixture(scope='module')
 def pytorch_full_version(request):
     return request.config.getoption('--pytorch-full-version')
@@ -184,3 +181,8 @@ def sklearn_full_version(request):
 @pytest.fixture(scope='module')
 def tf_full_version(request):
     return request.config.getoption('--tf-full-version')
+
+
+@pytest.fixture(scope='module')
+def ei_tf_full_version(request):
+    return request.config.getoption('--ei-tf-full-version')

tests/integ/test_mxnet_train.py

@@ -121,15 +121,15 @@ def test_deploy_model_with_update_non_existing_endpoint(mxnet_training_job, sage
 @pytest.mark.regional_testing
 @pytest.mark.skipif(tests.integ.test_region() not in tests.integ.EI_SUPPORTED_REGIONS,
                     reason="EI isn't supported in that specific region.")
-def test_deploy_model_with_accelerator(mxnet_training_job, sagemaker_session, ei_mxnet_version):
+def test_deploy_model_with_accelerator(mxnet_training_job, sagemaker_session, ei_mxnet_full_version):
     endpoint_name = 'test-mxnet-deploy-model-ei-{}'.format(sagemaker_timestamp())
 
     with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
         desc = sagemaker_session.sagemaker_client.describe_training_job(TrainingJobName=mxnet_training_job)
         model_data = desc['ModelArtifacts']['S3ModelArtifacts']
         script_path = os.path.join(DATA_DIR, 'mxnet_mnist', 'mnist.py')
         model = MXNetModel(model_data, 'SageMakerRole', entry_point=script_path,
-                           framework_version=ei_mxnet_version, py_version=PYTHON_VERSION,
+                           framework_version=ei_mxnet_full_version, py_version=PYTHON_VERSION,
                            sagemaker_session=sagemaker_session)
         predictor = model.deploy(1, 'ml.m4.xlarge', endpoint_name=endpoint_name, accelerator_type='ml.eia1.medium')
 

tests/integ/test_tf.py

@@ -83,7 +83,7 @@ def test_deploy_model(sagemaker_session, tf_training_job):
 @pytest.mark.skipif(tests.integ.test_region() not in tests.integ.EI_SUPPORTED_REGIONS,
                     reason="EI isn't supported in that specific region.")
 @pytest.mark.skipif(PYTHON_VERSION != 'py2', reason="TensorFlow image supports only python 2.")
-def test_deploy_model_with_accelerator(sagemaker_session, tf_training_job, ei_tf_version):
+def test_deploy_model_with_accelerator(sagemaker_session, tf_training_job, ei_tf_full_version):
     endpoint_name = 'test-tf-deploy-model-ei-{}'.format(sagemaker_timestamp())
 
     with timeout_and_delete_endpoint_by_name(endpoint_name, sagemaker_session):
@@ -92,7 +92,7 @@ def test_deploy_model_with_accelerator(sagemaker_session, tf_training_job, ei_tf
 
         script_path = os.path.join(DATA_DIR, 'iris', 'iris-dnn-classifier.py')
         model = TensorFlowModel(model_data, 'SageMakerRole', entry_point=script_path,
-                                framework_version=ei_tf_version, sagemaker_session=sagemaker_session)
+                                framework_version=ei_tf_full_version, sagemaker_session=sagemaker_session)
 
         json_predictor = model.deploy(initial_instance_count=1, instance_type='ml.c4.xlarge',
                                       endpoint_name=endpoint_name, accelerator_type='ml.eia1.medium')