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 _run_container(self, model_details: ModelSpec):
docker_client = docker.from_env()
uid = os.getuid()
container_index = self._get_port_index()
model_folder = model_details.model_details.local_folder
container_spec = get_container_spec(model_details)
create_network(docker_client)
docker_client.containers.run(
name=self._get_container_name(model_details),
ports={container_index: self._get_available_port()},
volumes={model_folder: {"bind": DefaultModelsPath, "mode": "ro"}},
detach=True,
network=DefaultNetworkName,
user=uid,
**container_spec,
)
def deploy(self, model_details: ModelDetails):
docker_client = docker.from_env()
protocol = self.get_protocol()
container_index = self._get_port_index()
model_folder = model_details.local_folder
container_spec = get_container_spec(model_details, protocol)
self._create_network(docker_client)
docker_client.containers.run(
name=self._get_container_name(model_details),
ports={container_index: self._get_available_port()},
volumes={model_folder: {
"bind": DefaultModelsPath,
"mode": "ro"
}},
detach=True,
network=DefaultNetworkName,
**container_spec,
)