mirror of
https://github.com/hanzo-ml/kserve.git
synced 2026-10-30 20:53:49 +00:00
0cc7b33d97
Signed-off-by: ZabinskiMichal <[email protected]> Signed-off-by: Michał Żabiński <[email protected]> Signed-off-by: Spolti <[email protected]> Co-authored-by: Spolti <[email protected]>
97 lines
2.9 KiB
Python
97 lines
2.9 KiB
Python
# Copyright 2026 The KServe Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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import logging
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import os
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from contextlib import asynccontextmanager
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from typing import AsyncIterator
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from kubernetes import client
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from kserve import (
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KServeClient,
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V1beta1InferenceService,
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V1beta1InferenceServiceSpec,
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V1beta1PredictorSpec,
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constants,
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)
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from ..common.utils import (
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AUTOGLUON_ISVC_WAIT_TIMEOUT,
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KSERVE_TEST_NAMESPACE,
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predict_isvc,
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)
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def create_autogluon_isvc(
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service_name: str, predictor: V1beta1PredictorSpec
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) -> V1beta1InferenceService:
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return V1beta1InferenceService(
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api_version=constants.KSERVE_V1BETA1,
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kind=constants.KSERVE_KIND_INFERENCESERVICE,
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metadata=client.V1ObjectMeta(
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name=service_name, namespace=KSERVE_TEST_NAMESPACE
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),
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spec=V1beta1InferenceServiceSpec(predictor=predictor),
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)
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def _kserve_client() -> KServeClient:
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return KServeClient(config_file=os.environ.get("KUBECONFIG", "~/.kube/config"))
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def _log_predictor_pods(kserve_client: KServeClient, service_name: str) -> None:
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pods = kserve_client.core_api.list_namespaced_pod(
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KSERVE_TEST_NAMESPACE,
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label_selector=f"serving.kserve.io/inferenceservice={service_name}",
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)
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for pod in pods.items:
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logging.info(pod)
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@asynccontextmanager
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async def autogluon_isvc(
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service_name: str,
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predictor: V1beta1PredictorSpec,
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timeout_seconds: int = AUTOGLUON_ISVC_WAIT_TIMEOUT,
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) -> AsyncIterator[KServeClient]:
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"""Create an InferenceService, wait until ready, then delete it on exit."""
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kserve_client = _kserve_client()
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kserve_client.create(create_autogluon_isvc(service_name, predictor))
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try:
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try:
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kserve_client.wait_isvc_ready(
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service_name,
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namespace=KSERVE_TEST_NAMESPACE,
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timeout_seconds=timeout_seconds,
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)
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except RuntimeError as e:
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_log_predictor_pods(kserve_client, service_name)
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raise e
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yield kserve_client
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finally:
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kserve_client.delete(service_name, KSERVE_TEST_NAMESPACE)
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async def deploy_and_predict(
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service_name: str,
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predictor: V1beta1PredictorSpec,
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rest_client,
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input_path: str,
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timeout_seconds: int = AUTOGLUON_ISVC_WAIT_TIMEOUT,
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):
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async with autogluon_isvc(service_name, predictor, timeout_seconds):
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return await predict_isvc(rest_client, service_name, input_path)
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