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60 lines
1.9 KiB
60 lines
1.9 KiB
#
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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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import os
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from kubernetes import client
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from kubernetes.client import V1ResourceRequirements
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from kserve import (
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constants,
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KServeClient,
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V1beta1InferenceService,
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V1beta1InferenceServiceSpec,
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V1beta1PredictorSpec,
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V1beta1SKLearnSpec,
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)
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from utils import KSERVE_TEST_NAMESPACE
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from utils import predict
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def test_sklearn_kserve():
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service_name = "isvc-sklearn"
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predictor = V1beta1PredictorSpec(
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min_replicas=1,
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sklearn=V1beta1SKLearnSpec(
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storage_uri="gs://kfserving-examples/models/sklearn/1.0/model",
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resources=V1ResourceRequirements(
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requests={"cpu": "50m", "memory": "128Mi"},
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limits={"cpu": "100m", "memory": "256Mi"},
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),
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),
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)
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isvc = V1beta1InferenceService(
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api_version=constants.KSERVE_V1BETA1,
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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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kserve_client = KServeClient(
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config_file=os.environ.get("KUBECONFIG", "~/.kube/config")
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)
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kserve_client.create(isvc)
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kserve_client.wait_isvc_ready(service_name, namespace=KSERVE_TEST_NAMESPACE)
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res = predict(service_name, "./data/iris_input.json")
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assert res["predictions"] == [1, 1]
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kserve_client.delete(service_name, KSERVE_TEST_NAMESPACE)
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