def _create_model_server_runner(
model_path: Text,
serving_binary: serving_bins.ServingBinary,
serving_spec: infra_validator_pb2.ServingSpec):
"""Create a ModelServerRunner from a model, a ServingBinary and a ServingSpec.
Args:
model_path: An IV-flavored model path. (See model_path_utils.py)
serving_binary: One of ServingBinary instances parsed from the
`serving_spec`.
serving_spec: A ServingSpec instance of this infra validation.
Returns:
A ModelServerRunner.
"""
platform = serving_spec.WhichOneof('serving_platform')
if platform == 'local_docker':
return local_docker_runner.LocalDockerRunner(
model_path=model_path,
serving_binary=serving_binary,
serving_spec=serving_spec
)
elif platform == 'kubernetes':
return kubernetes_runner.KubernetesRunner(
model_path=model_path,
serving_binary=serving_binary,
serving_spec=serving_spec
)
else:
raise NotImplementedError('Invalid serving_platform {}'.format(platform))
def _CreateKubernetesRunner(self, k8s_config_dict=None):
self._serving_spec = infra_validator_pb2.ServingSpec()
json_format.ParseDict({
'tensorflow_serving': {
'tags': ['1.15.0']},
'kubernetes': k8s_config_dict or {},
'model_name': self._model_name,
}, self._serving_spec)
serving_binary = serving_bins.parse_serving_binaries(self._serving_spec)[0]
return kubernetes_runner.KubernetesRunner(
model_path=path_utils.serving_model_path(self._model.uri),
serving_binary=serving_binary,
serving_spec=self._serving_spec)