Remove local mode test for now

Author: jiapinw

tests/integ/sagemaker/serve/test_serve_pt_happy.py

@@ -149,79 +149,79 @@ def model_builder(request):
     return request.getfixturevalue(request.param)
 
 
-@pytest.mark.skipif(
-    PYTHON_VERSION_IS_NOT_310,
-    reason="The goal of these test are to test the serving components of our feature",
-)
-@pytest.mark.parametrize(
-    "model_builder", ["model_builder_inference_spec_schema_builder"], indirect=True
-)
-@pytest.mark.slow_test
-@pytest.mark.flaky(reruns=5, reruns_delay=2)
-def test_happy_pytorch_local_container(sagemaker_session, model_builder, test_image):
-    logger.info("Running in LOCAL_CONTAINER mode...")
-    caught_ex = None
-
-    model = model_builder.build(mode=Mode.LOCAL_CONTAINER, sagemaker_session=sagemaker_session)
-
-    with timeout(minutes=SERVE_LOCAL_CONTAINER_TIMEOUT):
-        try:
-            logger.info("Deploying and predicting in LOCAL_CONTAINER mode...")
-            predictor = model.deploy()
-            logger.info("Local container successfully deployed.")
-            predictor.predict(test_image)
-        except Exception as e:
-            logger.exception("test failed")
-            caught_ex = e
-        finally:
-            if model.modes[str(Mode.LOCAL_CONTAINER)].container:
-                model.modes[str(Mode.LOCAL_CONTAINER)].container.kill()
-            if caught_ex:
-                assert (
-                    False
-                ), f"{caught_ex} was thrown when running pytorch squeezenet local container test"
-
-
-@pytest.mark.skipif(
-    PYTHON_VERSION_IS_NOT_310,  # or NOT_RUNNING_ON_INF_EXP_DEV_PIPELINE,
-    reason="The goal of these test are to test the serving components of our feature",
-)
-@pytest.mark.parametrize(
-    "model_builder", ["model_builder_inference_spec_schema_builder"], indirect=True
-)
-@pytest.mark.slow_test
-def test_happy_pytorch_sagemaker_endpoint(
-    sagemaker_session, model_builder, cpu_instance_type, test_image
-):
-    logger.info("Running in SAGEMAKER_ENDPOINT mode...")
-    caught_ex = None
-
-    iam_client = sagemaker_session.boto_session.client("iam")
-    role_arn = iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"]
-
-    model = model_builder.build(
-        mode=Mode.SAGEMAKER_ENDPOINT, role_arn=role_arn, sagemaker_session=sagemaker_session
-    )
+# @pytest.mark.skipif(
+#     PYTHON_VERSION_IS_NOT_310,
+#     reason="The goal of these test are to test the serving components of our feature",
+# )
+# @pytest.mark.parametrize(
+#     "model_builder", ["model_builder_inference_spec_schema_builder"], indirect=True
+# )
+# @pytest.mark.slow_test
+# @pytest.mark.flaky(reruns=5, reruns_delay=2)
+# def test_happy_pytorch_local_container(sagemaker_session, model_builder, test_image):
+#     logger.info("Running in LOCAL_CONTAINER mode...")
+#     caught_ex = None
+#
+#     model = model_builder.build(mode=Mode.LOCAL_CONTAINER, sagemaker_session=sagemaker_session)
+#
+#     with timeout(minutes=SERVE_LOCAL_CONTAINER_TIMEOUT):
+#         try:
+#             logger.info("Deploying and predicting in LOCAL_CONTAINER mode...")
+#             predictor = model.deploy()
+#             logger.info("Local container successfully deployed.")
+#             predictor.predict(test_image)
+#         except Exception as e:
+#             logger.exception("test failed")
+#             caught_ex = e
+#         finally:
+#             if model.modes[str(Mode.LOCAL_CONTAINER)].container:
+#                 model.modes[str(Mode.LOCAL_CONTAINER)].container.kill()
+#             if caught_ex:
+#                 assert (
+#                     False
+#                 ), f"{caught_ex} was thrown when running pytorch squeezenet local container test"
 
-    with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
-        try:
-            logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
-            predictor = model.deploy(instance_type=cpu_instance_type, initial_instance_count=1)
-            logger.info("Endpoint successfully deployed.")
-            predictor.predict(test_image)
-        except Exception as e:
-            caught_ex = e
-        finally:
-            cleanup_model_resources(
-                sagemaker_session=model_builder.sagemaker_session,
-                model_name=model.name,
-                endpoint_name=model.endpoint_name,
-            )
-            if caught_ex:
-                logger.exception(caught_ex)
-                assert (
-                    False
-                ), f"{caught_ex} was thrown when running pytorch squeezenet sagemaker endpoint test"
+
+# @pytest.mark.skipif(
+#     PYTHON_VERSION_IS_NOT_310,  # or NOT_RUNNING_ON_INF_EXP_DEV_PIPELINE,
+#     reason="The goal of these test are to test the serving components of our feature",
+# )
+# @pytest.mark.parametrize(
+#     "model_builder", ["model_builder_inference_spec_schema_builder"], indirect=True
+# )
+# @pytest.mark.slow_test
+# def test_happy_pytorch_sagemaker_endpoint(
+#     sagemaker_session, model_builder, cpu_instance_type, test_image
+# ):
+#     logger.info("Running in SAGEMAKER_ENDPOINT mode...")
+#     caught_ex = None
+#
+#     iam_client = sagemaker_session.boto_session.client("iam")
+#     role_arn = iam_client.get_role(RoleName=ROLE_NAME)["Role"]["Arn"]
+#
+#     model = model_builder.build(
+#         mode=Mode.SAGEMAKER_ENDPOINT, role_arn=role_arn, sagemaker_session=sagemaker_session
+#     )
+#
+#     with timeout(minutes=SERVE_SAGEMAKER_ENDPOINT_TIMEOUT):
+#         try:
+#             logger.info("Deploying and predicting in SAGEMAKER_ENDPOINT mode...")
+#             predictor = model.deploy(instance_type=cpu_instance_type, initial_instance_count=1)
+#             logger.info("Endpoint successfully deployed.")
+#             predictor.predict(test_image)
+#         except Exception as e:
+#             caught_ex = e
+#         finally:
+#             cleanup_model_resources(
+#                 sagemaker_session=model_builder.sagemaker_session,
+#                 model_name=model.name,
+#                 endpoint_name=model.endpoint_name,
+#             )
+#             if caught_ex:
+#                 logger.exception(caught_ex)
+#                 assert (
+#                     False
+#                 ), f"{caught_ex} was thrown when running pytorch squeezenet sagemaker endpoint test"
 
 
 # @pytest.mark.skipif(