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_kubernetes_spec(sklearn_model: Model):
options = KubernetesOptions(namespace="production", replicas=1)
k8s_object = KubernetesSpec(sklearn_model.details, SeldonProtocol(),
options)
expected = {
"apiVersion": "machinelearning.seldon.io/v1",
"kind": "SeldonDeployment",
"metadata": {
"name": sklearn_model.details.name,
"namespace": options.namespace,
},
"spec": {
"protocol":
"seldon",
"predictors": [{
"graph": {
"modelUri":
sklearn_model.details.uri,
"name":
"classifier",
"type":
"MODEL",
"implementation":
KubernetesSpec.Implementations[
sklearn_model.details.platform],
},
"name": "default",
"replicas": options.replicas,
}],
},
}
assert k8s_object.spec == expected
def test_deploy():
rt = SeldonDeployRuntime()
config = SeldonDeployConfig(
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=SeldonDeployAuthType.oidc,
)
rt.authenticate(settings=config)
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,
)
rt.deploy(sklearn_model)
rt.wait_ready(sklearn_model)
print(sklearn_model(np.array([[4.9, 3.1, 1.5, 0.2]])))
rt.undeploy(sklearn_model)
def __init__(self, k8s_options: KubernetesOptions = None, protocol=None):
if k8s_options is None:
k8s_options = KubernetesOptions()
self.k8s_options = k8s_options
self.create_k8s_client()
if protocol is None:
self.protocol = SeldonProtocol()
else:
self.protocol = protocol
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_tensorflow_spec():
md = ModelDetails(
name="test",
local_folder="",
uri="",
platform=ModelFramework.Tensorflow,
inputs=ModelDataArgs(args=[]),
outputs=ModelDataArgs(args=[]),
)
protocol = SeldonProtocol()
options = KubernetesOptions(namespace="production", replicas=1)
runtime_options = RuntimeOptions(k8s_options=options)
model_spec = ModelSpec(model_details=md,
protocol=protocol,
runtime_options=runtime_options)
spec = get_container_spec(model_spec)
assert "image" in spec
assert "command" in spec
def __init__(
self,
host: str,
user: str,
password: str,
auth_type: SeldonDeployAuthType = SeldonDeployAuthType.session_cookie,
k8s_options: KubernetesOptions = None,
_protocol=None,
):
if k8s_options is None:
k8s_options = KubernetesOptions()
self._k8s_options = k8s_options
self._host = host
self._user = user
self._password = password
self._auth_type = auth_type
if _protocol is None:
self.protocol = SeldonProtocol()
else:
self.protocol = _protocol
def __init__(self, protocol=None):
if protocol is None:
self.protocol = SeldonProtocol()
else:
self.protocol = protocol
