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_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 test_deploy():
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",
)
# sklearn_model.deploy()
sklearn_model(np.array([[4.9, 3.1, 1.5, 0.2]]))
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