def test_deploy_yaml():
rt = SeldonDeployRuntime()
config = EnterpriseRuntimeOptions(
host="https://34.78.44.92/seldon-deploy/api/v1alpha1",
user="******",
password="******",
oidc_server="https://34.78.44.92/auth/realms/deploy-realm",
oidc_client_id="sd-api",
verify_ssl=False,
auth_type=EnterpriseRuntimeAuthType.oidc,
)
rt.authenticate(settings=config)
options = KubernetesRuntimeOptions(
namespace="seldon",
ingress_options=IngressOptions(ssl=True, verify_ssl=False),
)
sklearn_model = Model(
name="test-iris-sklearn",
platform=ModelFramework.SKLearn,
uri="gs://seldon-models/sklearn/iris",
protocol=SeldonProtocol(),
runtime_options=options,
)
spec = rt.manifest(sklearn_model)
rtk = SeldonKubernetesRuntime()
expected = rtk.manifest(sklearn_model)
assert spec == expected
def test_deploy_yaml():
rt = SeldonDeployRuntime(
host="http://34.78.44.92/seldon-deploy/api/v1alpha1",
user="******",
oidc_server="https://34.78.44.92/auth/realms/deploy-realm",
password="******",
oidc_client_id="sd-api",
verify_ssl=False,
)
options = RuntimeOptions(
runtime="tempo.seldon.SeldonKubernetesRuntime",
k8s_options=KubernetesOptions(namespace="seldon"),
ingress_options=IngressOptions(ssl=True, verify_ssl=False),
)
sklearn_model = Model(
name="test-iris-sklearn",
platform=ModelFramework.SKLearn,
uri="gs://seldon-models/sklearn/iris",
protocol=SeldonProtocol(),
runtime_options=options,
)
spec = rt.to_k8s_yaml(sklearn_model)
rtk = SeldonKubernetesRuntime()
expected = rtk.to_k8s_yaml(sklearn_model)
assert spec == expected
def test_seldon_sklearn_model_yaml(expected):
m = Model(
name="test-iris-sklearn",
platform=ModelFramework.SKLearn,
uri="gs://seldon-models/sklearn/iris",
local_folder="/tmp/model",
protocol=SeldonProtocol(),
)
runtime = SeldonKubernetesRuntime()
assert runtime.to_k8s_yaml(m) == expected
def test_seldon_xgboost_model_yaml(expected):
m = Model(
name="test-iris-xgboost",
protocol=SeldonProtocol(),
platform=ModelFramework.XGBoost,
uri="gs://seldon-models/xgboost/iris",
local_folder="/tmp/model",
)
runtime = SeldonKubernetesRuntime()
print(runtime.to_k8s_yaml(m))
assert runtime.to_k8s_yaml(m) == expected
def test_seldon_model_yaml_auth():
m = Model(
name="test-iris-xgboost",
protocol=SeldonProtocol(),
platform=ModelFramework.XGBoost,
uri="gs://seldon-models/xgboost/iris",
local_folder="/tmp/model",
)
runtime = SeldonKubernetesRuntime(
runtime_options=RuntimeOptions(k8s_options=KubernetesOptions(authSecretName="auth"))
)
print(runtime.to_k8s_yaml(m))
def test_seldon_xgboost_model_yaml(expected):
m = Model(
name="test-iris-xgboost",
protocol=SeldonProtocol(),
platform=ModelFramework.XGBoost,
uri="gs://seldon-models/xgboost/iris",
local_folder="/tmp/model",
)
runtime = SeldonKubernetesRuntime()
yaml_str = runtime.manifest(m)
yaml_obj = yaml.safe_load(yaml_str)
yaml_obj_expected = yaml.safe_load(expected)
del yaml_obj["metadata"]["annotations"]["seldon.io/tempo-model"]
assert yaml_obj == yaml_obj_expected
def test_seldon_sklearn_model_yaml(expected):
m = Model(
name="test-iris-sklearn",
platform=ModelFramework.SKLearn,
uri="gs://seldon-models/sklearn/iris",
local_folder="/tmp/model",
protocol=SeldonProtocol(),
)
runtime = SeldonKubernetesRuntime()
yaml_str = runtime.manifest(m)
yaml_obj = yaml.safe_load(yaml_str)
yaml_obj_expected = yaml.safe_load(expected)
del yaml_obj["metadata"]["annotations"]["seldon.io/tempo-model"]
print("\n\n" + str(yaml_obj))
print("\n\n" + str(yaml_obj_expected))
assert yaml_obj == yaml_obj_expected
def test_seldon_model_yaml_auth(expected):
m = Model(
name="test-iris-xgboost",
protocol=SeldonProtocol(),
platform=ModelFramework.XGBoost,
uri="gs://seldon-models/xgboost/iris",
local_folder="/tmp/model",
)
runtime = SeldonKubernetesRuntime(runtime_options=KubernetesRuntimeOptions(
authSecretName="auth"))
yaml_str = runtime.manifest(m)
yaml_obj = yaml.safe_load(yaml_str)
yaml_obj_expected = yaml.safe_load(expected)
del yaml_obj["metadata"]["annotations"]["seldon.io/tempo-model"]
print("\n\n" + str(yaml_obj))
print("\n\n" + str(yaml_obj_expected))
assert yaml_obj == yaml_obj_expected
def test_seldon_xgboost_model_yaml(expected):
m = Model(
name="test-iris-xgboost",
runtime=SeldonKubernetesRuntime(),
platform=ModelFramework.XGBoost,
uri="gs://seldon-models/xgboost/iris",
local_folder="",
)
assert m.to_k8s_yaml() == expected
def test_seldon_sklearn_model_yaml(expected):
m = Model(
name="test-iris-sklearn",
runtime=SeldonKubernetesRuntime(),
platform=ModelFramework.SKLearn,
uri="gs://seldon-models/sklearn/iris",
local_folder="",
)
assert m.to_k8s_yaml() == expected
def test_deploy_yaml():
rt = SeldonDeployRuntime(
host="http://34.105.136.157/seldon-deploy/api/v1alpha1",
user="******",
password="******",
k8s_options=KubernetesOptions(namespace="seldon"),
)
sklearn_model = Model(
name="test-iris-sklearn",
runtime=rt,
platform=ModelFramework.SKLearn,
uri="gs://seldon-models/sklearn/iris",
local_folder=os.getcwd() + "/sklearn",
)
srt = SeldonKubernetesRuntime(k8s_options=KubernetesOptions(namespace="seldon"))
sklearn_model.set_runtime(srt)
expected = sklearn_model.to_k8s_yaml()
sklearn_model.set_runtime(rt)
assert sklearn_model.to_k8s_yaml() == expected
def test_create_k8s_runtime():
rto = RuntimeOptions()
rt = SeldonKubernetesRuntime(rto)
assert rt.runtime_options.runtime == "tempo.seldon.SeldonKubernetesRuntime"
def k8s_runtime_v2(k8s_namespace: str) -> SeldonKubernetesRuntime:
return SeldonKubernetesRuntime(
k8s_options=KubernetesOptions(namespace=k8s_namespace),
protocol=KFServingV2Protocol(),
)
def k8s_runtime(k8s_namespace: str) -> SeldonKubernetesRuntime:
return SeldonKubernetesRuntime(k8s_options=KubernetesOptions(
namespace=k8s_namespace))
def k8s_runtime(k8s_namespace: str) -> SeldonKubernetesRuntime:
return SeldonKubernetesRuntime(k8s_namespace)
def to_k8s_yaml_spec(self, model_spec: ModelSpec) -> str:
srt = SeldonKubernetesRuntime()
return srt.to_k8s_yaml_spec(model_spec)
def remote(self, model_spec: ModelSpec, *args, **kwargs) -> Any:
self._create_api_client()
srt = SeldonKubernetesRuntime()
srt.remote(model_spec, *args, **kwargs)
def to_k8s_yaml(self, model_details: ModelDetails) -> str:
srt = SeldonKubernetesRuntime(k8s_options=self._k8s_options,
protocol=self.protocol)
return srt.to_k8s_yaml(model_details)