def test_sklearn(self, namespace):
spec = "../../servers/sklearnserver/samples/iris.yaml"
retry_run(f"kubectl apply -f {spec} -n {namespace}")
wait_for_status("sklearn", namespace)
wait_for_rollout("sklearn", namespace)
time.sleep(1)
logging.warning("Initial request")
r = initial_rest_request("sklearn",
namespace,
data=[[0.1, 0.2, 0.3, 0.4]],
dtype="ndarray")
assert r.status_code == 200
r = rest_request_ambassador("sklearn", namespace, method="metadata")
assert r.status_code == 200
res = r.json()
logging.warning(res)
assert res["name"] == "iris"
assert res["versions"] == ["iris/v1"]
r = grpc_request_ambassador("sklearn",
namespace,
data=np.array([[0.1, 0.2, 0.3, 0.4]]))
res = json.loads(json_format.MessageToJson(r))
logging.info(res)
logging.warning("Success for test_prepack_sklearn")
run(f"kubectl delete -f {spec} -n {namespace}", shell=True)
def test_model_combiner_grpc(self, namespace, s2i_python_version):
create_push_s2i_image(s2i_python_version, "one", "grpc")
create_push_s2i_image(s2i_python_version, "two", "grpc")
create_push_s2i_image(s2i_python_version, "combiner", "grpc")
retry_run(
f"kubectl apply -f ../resources/tags_combiner_grpc.json -n {namespace}"
)
wait_for_status("mymodel-tags-combiner", namespace)
wait_for_rollout("mymodel-tags-combiner", namespace)
r = initial_grpc_request("mymodel-tags-combiner", namespace)
arr = np.array([[1, 2, 3]])
r = grpc_request_ambassador("mymodel-tags-combiner",
namespace,
API_AMBASSADOR,
data=arr)
res = json.loads(json_format.MessageToJson(r))
logging.info(res)
# assert r.status_code == 200
assert res["data"]["ndarray"] == [["model-1"], ["model-2"]]
assert res["meta"]["tags"] == {
"combiner": "yes",
"common": 2,
"model-1": "yes",
"model-2": "yes",
}
run(
f"kubectl delete -f ../resources/tags_combiner_grpc.json -n {namespace}",
shell=True,
)