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[fix] disable modelbuilder mlflow local integ tests #4576

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Merged
merged 1 commit into from
Apr 12, 2024
Merged

[fix] disable modelbuilder mlflow local integ tests #4576

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62 changes: 31 additions & 31 deletions tests/integ/sagemaker/serve/test_serve_mlflow_pytorch_flavor_happy.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@
PYTORCH_SQUEEZENET_RESOURCE_DIR,
PYTORCH_SQUEEZENET_MLFLOW_RESOURCE_DIR,
SERVE_SAGEMAKER_ENDPOINT_TIMEOUT,
SERVE_LOCAL_CONTAINER_TIMEOUT,
# SERVE_LOCAL_CONTAINER_TIMEOUT,
PYTHON_VERSION_IS_NOT_310,
)
from tests.integ.timeout import timeout
Expand Down Expand Up @@ -128,36 +128,36 @@ 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.flaky(reruns=3, reruns_delay=2)
@pytest.mark.parametrize("model_builder", ["model_builder_local_builder"], indirect=True)
def test_happy_mlflow_pytorch_local_container_with_torch_serve(
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,
# reason="The goal of these test are to test the serving components of our feature",
# )
# @pytest.mark.flaky(reruns=3, reruns_delay=2)
# @pytest.mark.parametrize("model_builder", ["model_builder_local_builder"], indirect=True)
# def test_happy_mlflow_pytorch_local_container_with_torch_serve(
# 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(
Expand Down
64 changes: 32 additions & 32 deletions tests/integ/sagemaker/serve/test_serve_mlflow_xgboost_flavor_happy.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@
from tests.integ.sagemaker.serve.constants import (
XGBOOST_MLFLOW_RESOURCE_DIR,
SERVE_SAGEMAKER_ENDPOINT_TIMEOUT,
SERVE_LOCAL_CONTAINER_TIMEOUT,
# SERVE_LOCAL_CONTAINER_TIMEOUT,
PYTHON_VERSION_IS_NOT_310,
)
from tests.integ.timeout import timeout
Expand Down Expand Up @@ -108,37 +108,37 @@ 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.flaky(reruns=3, reruns_delay=2)
@pytest.mark.parametrize("model_builder", ["model_builder_local_builder"], indirect=True)
def test_happy_mlflow_xgboost_local_container_with_torch_serve(
sagemaker_session, model_builder, test_data
):
logger.info("Running in LOCAL_CONTAINER mode...")
caught_ex = None

model = model_builder.build(mode=Mode.LOCAL_CONTAINER, sagemaker_session=sagemaker_session)
test_x, _ = test_data

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_x)
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,
# reason="The goal of these test are to test the serving components of our feature",
# )
# @pytest.mark.flaky(reruns=3, reruns_delay=2)
# @pytest.mark.parametrize("model_builder", ["model_builder_local_builder"], indirect=True)
# def test_happy_mlflow_xgboost_local_container_with_torch_serve(
# sagemaker_session, model_builder, test_data
# ):
# logger.info("Running in LOCAL_CONTAINER mode...")
# caught_ex = None
#
# model = model_builder.build(mode=Mode.LOCAL_CONTAINER, sagemaker_session=sagemaker_session)
# test_x, _ = test_data
#
# 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_x)
# 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(
Expand Down