infra: use fixture for Chainer and XGBoost Python version, clean up remaining version fixtures (#1631)

Author: laurenyu

tests/conftest.py

@@ -44,21 +44,6 @@ def pytest_addoption(parser):
     parser.addoption("--sagemaker-client-config", action="store", default=None)
     parser.addoption("--sagemaker-runtime-config", action="store", default=None)
     parser.addoption("--boto-config", action="store", default=None)
-    parser.addoption("--chainer-full-version", action="store", default="5.0.0")
-    parser.addoption("--ei-mxnet-full-version", action="store", default="1.5.1")
-    parser.addoption(
-        "--rl-coach-mxnet-full-version",
-        action="store",
-        default=RLEstimator.COACH_LATEST_VERSION_MXNET,
-    )
-    parser.addoption(
-        "--rl-coach-tf-full-version", action="store", default=RLEstimator.COACH_LATEST_VERSION_TF
-    )
-    parser.addoption(
-        "--rl-ray-full-version", action="store", default=RLEstimator.RAY_LATEST_VERSION
-    )
-    parser.addoption("--ei-tf-full-version", action="store")
-    parser.addoption("--xgboost-full-version", action="store", default="1.0-1")
 
 
 def pytest_configure(config):
@@ -248,8 +233,13 @@ def rl_ray_version(request):
 
 
 @pytest.fixture(scope="module")
-def chainer_full_version(request):
-    return request.config.getoption("--chainer-full-version")
+def chainer_full_version():
+    return "5.0.0"
+
+
+@pytest.fixture(scope="module")
+def chainer_full_py_version():
+    return "py3"
 
 
 @pytest.fixture(scope="module")
@@ -263,8 +253,8 @@ def mxnet_full_py_version():
 
 
 @pytest.fixture(scope="module")
-def ei_mxnet_full_version(request):
-    return request.config.getoption("--ei-mxnet-full-version")
+def ei_mxnet_full_version():
+    return "1.5.1"
 
 
 @pytest.fixture(scope="module")
@@ -283,18 +273,18 @@ def pytorch_full_ei_version():
 
 
 @pytest.fixture(scope="module")
-def rl_coach_mxnet_full_version(request):
-    return request.config.getoption("--rl-coach-mxnet-full-version")
+def rl_coach_mxnet_full_version():
+    return RLEstimator.COACH_LATEST_VERSION_MXNET
 
 
 @pytest.fixture(scope="module")
-def rl_coach_tf_full_version(request):
-    return request.config.getoption("--rl-coach-tf-full-version")
+def rl_coach_tf_full_version():
+    return RLEstimator.COACH_LATEST_VERSION_TF
 
 
 @pytest.fixture(scope="module")
-def rl_ray_full_version(request):
-    return request.config.getoption("--rl-ray-full-version")
+def rl_ray_full_version():
+    return RLEstimator.RAY_LATEST_VERSION
 
 
 @pytest.fixture(scope="module")
@@ -347,13 +337,19 @@ def tf_full_py_version(tf_full_version):
     return "py37"
 
 
-@pytest.fixture(scope="module", params=["1.15.0", "2.0.0"])
-def ei_tf_full_version(request):
-    tf_ei_version = request.config.getoption("--ei-tf-full-version")
-    if tf_ei_version is None:
-        return request.param
-    else:
-        tf_ei_version
+@pytest.fixture(scope="module")
+def ei_tf_full_version():
+    return "2.0.0"
+
+
+@pytest.fixture(scope="module")
+def xgboost_full_version():
+    return "1.0-1"
+
+
+@pytest.fixture(scope="module")
+def xgboost_full_py_version():
+    return "py3"
 
 
 @pytest.fixture(scope="session")
@@ -409,8 +405,3 @@ def pytest_generate_tests(metafunc):
         ):
             params.append("ml.p2.xlarge")
         metafunc.parametrize("instance_type", params, scope="session")
-
-
-@pytest.fixture(scope="module")
-def xgboost_full_version(request):
-    return request.config.getoption("--xgboost-full-version")

tests/integ/__init__.py

@@ -14,7 +14,6 @@
 
 import logging
 import os
-import sys
 
 import boto3
 
@@ -23,7 +22,6 @@
 TUNING_DEFAULT_TIMEOUT_MINUTES = 20
 TRANSFORM_DEFAULT_TIMEOUT_MINUTES = 20
 AUTO_ML_DEFAULT_TIMEMOUT_MINUTES = 60
-PYTHON_VERSION = "py{}".format(sys.version_info.major)
 
 # these regions have some p2 and p3 instances, but not enough for continuous testing
 HOSTING_NO_P2_REGIONS = [

tests/integ/test_airflow_config.py

@@ -45,7 +45,7 @@
 from sagemaker.utils import sagemaker_timestamp
 from sagemaker.workflow import airflow as sm_airflow
 from sagemaker.xgboost import XGBoost
-from tests.integ import datasets, DATA_DIR, PYTHON_VERSION
+from tests.integ import datasets, DATA_DIR
 from tests.integ.record_set import prepare_record_set_from_local_files
 from tests.integ.timeout import timeout
 
@@ -404,7 +404,7 @@ def test_rcf_airflow_config_uploads_data_source_to_s3(sagemaker_session, cpu_ins
 
 @pytest.mark.canary_quick
 def test_chainer_airflow_config_uploads_data_source_to_s3(
-    sagemaker_local_session, cpu_instance_type, chainer_full_version
+    sagemaker_local_session, cpu_instance_type, chainer_full_version, chainer_full_py_version
 ):
     with timeout(seconds=AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS):
         script_path = os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")
@@ -416,7 +416,7 @@ def test_chainer_airflow_config_uploads_data_source_to_s3(
             train_instance_count=SINGLE_INSTANCE_COUNT,
             train_instance_type="local",
             framework_version=chainer_full_version,
-            py_version=PYTHON_VERSION,
+            py_version=chainer_full_py_version,
             sagemaker_session=sagemaker_local_session,
             hyperparameters={"epochs": 1},
             use_mpi=True,
@@ -545,20 +545,19 @@ def test_tf_airflow_config_uploads_data_source_to_s3(
 
 
 @pytest.mark.canary_quick
-@pytest.mark.skipif(PYTHON_VERSION == "py2", reason="XGBoost container does not support Python 2.")
 def test_xgboost_airflow_config_uploads_data_source_to_s3(
-    sagemaker_session, cpu_instance_type, xgboost_full_version
+    sagemaker_session, cpu_instance_type, xgboost_full_version, xgboost_full_py_version
 ):
     with timeout(seconds=AIRFLOW_CONFIG_TIMEOUT_IN_SECONDS):
         xgboost = XGBoost(
             entry_point=os.path.join(DATA_DIR, "dummy_script.py"),
             framework_version=xgboost_full_version,
+            py_version=xgboost_full_py_version,
             role=ROLE,
             sagemaker_session=sagemaker_session,
             train_instance_type=cpu_instance_type,
             train_instance_count=SINGLE_INSTANCE_COUNT,
             base_job_name="XGBoost job",
-            py_version=PYTHON_VERSION,
         )
 
         training_config = _build_airflow_workflow(

tests/integ/test_chainer_train.py

@@ -20,22 +20,32 @@
 from sagemaker.chainer.estimator import Chainer
 from sagemaker.chainer.model import ChainerModel
 from sagemaker.utils import unique_name_from_base
-from tests.integ import DATA_DIR, PYTHON_VERSION, TRAINING_DEFAULT_TIMEOUT_MINUTES
+from tests.integ import DATA_DIR, TRAINING_DEFAULT_TIMEOUT_MINUTES
 from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
 
 
 @pytest.fixture(scope="module")
-def chainer_local_training_job(sagemaker_local_session, chainer_full_version):
-    return _run_mnist_training_job(sagemaker_local_session, "local", 1, chainer_full_version)
+def chainer_local_training_job(
+    sagemaker_local_session, chainer_full_version, chainer_full_py_version
+):
+    return _run_mnist_training_job(
+        sagemaker_local_session, "local", 1, chainer_full_version, chainer_full_py_version
+    )
 
 
 @pytest.mark.local_mode
-def test_distributed_cpu_training(sagemaker_local_session, chainer_full_version):
-    _run_mnist_training_job(sagemaker_local_session, "local", 2, chainer_full_version)
+def test_distributed_cpu_training(
+    sagemaker_local_session, chainer_full_version, chainer_full_py_version
+):
+    _run_mnist_training_job(
+        sagemaker_local_session, "local", 2, chainer_full_version, chainer_full_py_version
+    )
 
 
 @pytest.mark.local_mode
-def test_training_with_additional_hyperparameters(sagemaker_local_session, chainer_full_version):
+def test_training_with_additional_hyperparameters(
+    sagemaker_local_session, chainer_full_version, chainer_full_py_version
+):
     script_path = os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")
     data_path = os.path.join(DATA_DIR, "chainer_mnist")
 
@@ -45,7 +55,7 @@ def test_training_with_additional_hyperparameters(sagemaker_local_session, chain
         train_instance_count=1,
         train_instance_type="local",
         framework_version=chainer_full_version,
-        py_version=PYTHON_VERSION,
+        py_version=chainer_full_py_version,
         sagemaker_session=sagemaker_local_session,
         hyperparameters={"epochs": 1},
         use_mpi=True,
@@ -62,7 +72,9 @@ def test_training_with_additional_hyperparameters(sagemaker_local_session, chain
 
 @pytest.mark.canary_quick
 @pytest.mark.regional_testing
-def test_attach_deploy(sagemaker_session, chainer_full_version, cpu_instance_type):
+def test_attach_deploy(
+    sagemaker_session, chainer_full_version, chainer_full_py_version, cpu_instance_type
+):
     with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
         script_path = os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")
         data_path = os.path.join(DATA_DIR, "chainer_mnist")
@@ -71,7 +83,7 @@ def test_attach_deploy(sagemaker_session, chainer_full_version, cpu_instance_typ
             entry_point=script_path,
             role="SageMakerRole",
             framework_version=chainer_full_version,
-            py_version=PYTHON_VERSION,
+            py_version=chainer_full_py_version,
             train_instance_count=1,
             train_instance_type=cpu_instance_type,
             sagemaker_session=sagemaker_session,
@@ -100,7 +112,12 @@ def test_attach_deploy(sagemaker_session, chainer_full_version, cpu_instance_typ
 
 
 @pytest.mark.local_mode
-def test_deploy_model(chainer_local_training_job, sagemaker_local_session, chainer_full_version):
+def test_deploy_model(
+    chainer_local_training_job,
+    sagemaker_local_session,
+    chainer_full_version,
+    chainer_full_py_version,
+):
     script_path = os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")
 
     model = ChainerModel(
@@ -109,7 +126,7 @@ def test_deploy_model(chainer_local_training_job, sagemaker_local_session, chain
         entry_point=script_path,
         sagemaker_session=sagemaker_local_session,
         framework_version=chainer_full_version,
-        py_version=PYTHON_VERSION,
+        py_version=chainer_full_py_version,
     )
 
     predictor = model.deploy(1, "local")
@@ -120,7 +137,7 @@ def test_deploy_model(chainer_local_training_job, sagemaker_local_session, chain
 
 
 def _run_mnist_training_job(
-    sagemaker_session, instance_type, instance_count, chainer_full_version, wait=True
+    sagemaker_session, instance_type, instance_count, chainer_version, py_version
 ):
     script_path = (
         os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")
@@ -133,8 +150,8 @@ def _run_mnist_training_job(
     chainer = Chainer(
         entry_point=script_path,
         role="SageMakerRole",
-        framework_version=chainer_full_version,
-        py_version=PYTHON_VERSION,
+        framework_version=chainer_version,
+        py_version=py_version,
         train_instance_count=instance_count,
         train_instance_type=instance_type,
         sagemaker_session=sagemaker_session,
@@ -147,7 +164,7 @@ def _run_mnist_training_job(
     test_input = "file://" + os.path.join(data_path, "test")
 
     job_name = unique_name_from_base("test-chainer-training")
-    chainer.fit({"train": train_input, "test": test_input}, wait=wait, job_name=job_name)
+    chainer.fit({"train": train_input, "test": test_input}, job_name=job_name)
     return chainer
 
 

tests/integ/test_rl.py

@@ -19,12 +19,11 @@
 
 from sagemaker.rl import RLEstimator, RLFramework, RLToolkit
 from sagemaker.utils import sagemaker_timestamp, unique_name_from_base
-from tests.integ import DATA_DIR, PYTHON_VERSION
+from tests.integ import DATA_DIR
 from tests.integ.timeout import timeout, timeout_and_delete_endpoint_by_name
 
 
 @pytest.mark.canary_quick
-@pytest.mark.skipif(PYTHON_VERSION != "py3", reason="RL images supports only Python 3.")
 def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version, cpu_instance_type):
     estimator = _test_coach(
         sagemaker_session, RLFramework.MXNET, rl_coach_mxnet_full_version, cpu_instance_type
@@ -52,7 +51,6 @@ def test_coach_mxnet(sagemaker_session, rl_coach_mxnet_full_version, cpu_instanc
     assert 0 < action[0][1] < 1
 
 
-@pytest.mark.skipif(PYTHON_VERSION != "py3", reason="RL images supports only Python 3.")
 def test_coach_tf(sagemaker_session, rl_coach_tf_full_version, cpu_instance_type):
     estimator = _test_coach(
         sagemaker_session, RLFramework.TENSORFLOW, rl_coach_tf_full_version, cpu_instance_type
@@ -98,7 +96,6 @@ def _test_coach(sagemaker_session, rl_framework, rl_coach_version, cpu_instance_
 
 
 @pytest.mark.canary_quick
-@pytest.mark.skipif(PYTHON_VERSION != "py3", reason="RL images supports only Python 3.")
 def test_ray_tf(sagemaker_session, rl_ray_full_version, cpu_instance_type):
     source_dir = os.path.join(DATA_DIR, "ray_cartpole")
     cartpole = "train_ray.py"

tests/integ/test_tuner.py

@@ -45,7 +45,6 @@
     datasets,
     vpc_test_utils,
     DATA_DIR,
-    PYTHON_VERSION,
     TUNING_DEFAULT_TIMEOUT_MINUTES,
 )
 from tests.integ.record_set import prepare_record_set_from_local_files
@@ -687,7 +686,9 @@ def test_tuning_tf_vpc_multi(
 
 
 @pytest.mark.canary_quick
-def test_tuning_chainer(sagemaker_session, chainer_full_version, cpu_instance_type):
+def test_tuning_chainer(
+    sagemaker_session, chainer_full_version, chainer_full_py_version, cpu_instance_type
+):
     with timeout(minutes=TUNING_DEFAULT_TIMEOUT_MINUTES):
         script_path = os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")
         data_path = os.path.join(DATA_DIR, "chainer_mnist")
@@ -696,7 +697,7 @@ def test_tuning_chainer(sagemaker_session, chainer_full_version, cpu_instance_ty
             entry_point=script_path,
             role="SageMakerRole",
             framework_version=chainer_full_version,
-            py_version=PYTHON_VERSION,
+            py_version=chainer_full_py_version,
             train_instance_count=1,
             train_instance_type=cpu_instance_type,
             sagemaker_session=sagemaker_session,