mirror of
https://github.com/hanzo-ml/kserve.git
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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]>
122 lines
4.0 KiB
Python
122 lines
4.0 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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import os
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import pytest
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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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V1beta1ModelFormat,
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V1beta1ModelSpec,
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V1beta1PredictorSpec,
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)
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from ..common.utils import predict_isvc
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from .autogluon_helpers import autogluon_isvc, deploy_and_predict
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AUTOGLUON_STORAGE_URI = os.getenv(
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"AUTOGLUON_STORAGE_URI", "gs://test-project-frog-ml-artifacts/predictor/"
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)
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AUTOGLUON_RESOURCES = V1ResourceRequirements(
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requests={"cpu": "100m", "memory": "1Gi"},
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limits={"cpu": "1", "memory": "2Gi"},
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)
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def _create_predictor(
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service_name: str, protocol_version: str = None, storage_uri: str = None
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):
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model = V1beta1ModelSpec(
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model_format=V1beta1ModelFormat(name="autogluon"),
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runtime="kserve-autogluonserver",
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storage_uri=storage_uri or AUTOGLUON_STORAGE_URI,
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resources=AUTOGLUON_RESOURCES,
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)
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if protocol_version:
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model.protocol_version = protocol_version
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model.readiness_probe = client.V1Probe(
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http_get=client.V1HTTPGetAction(
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path=f"/v2/models/{service_name}/ready", port=8080
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),
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initial_delay_seconds=90,
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)
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return V1beta1PredictorSpec(min_replicas=1, model=model)
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@pytest.mark.predictor
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@pytest.mark.asyncio(scope="session")
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async def test_autogluon_runtime_kserve_v1(rest_v1_client):
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service_name = "isvc-autogluon-v1"
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predictor = _create_predictor(service_name)
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response = await deploy_and_predict(
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service_name,
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predictor,
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rest_v1_client,
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"./data/autogluon_titanic_input.json",
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)
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assert "predictions" in response
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assert len(response["predictions"]) > 0
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@pytest.mark.predictor
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@pytest.mark.asyncio(scope="session")
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async def test_autogluon_runtime_kserve_v2(rest_v2_client):
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service_name = "isvc-autogluon-v2"
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predictor = _create_predictor(service_name, protocol_version="v2")
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response = await deploy_and_predict(
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service_name,
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predictor,
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rest_v2_client,
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"./data/autogluon_titanic_input_v2.json",
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)
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assert len(response.outputs) > 0
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assert len(response.outputs[0].data) > 0
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@pytest.mark.predictor
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@pytest.mark.asyncio(scope="session")
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async def test_autogluon_runtime_kserve_v2_input_variants(rest_v2_client):
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service_name = "isvc-autogluon-v2-variants"
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predictor = _create_predictor(service_name, protocol_version="v2")
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async with autogluon_isvc(service_name, predictor):
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for input_path in [
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"./data/autogluon_titanic_input_v2.json",
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"./data/autogluon_titanic_input_v2_binary.json",
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"./data/autogluon_titanic_input_v2_all_binary.json",
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]:
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response = await predict_isvc(rest_v2_client, service_name, input_path)
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assert len(response.outputs) > 0
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assert len(response.outputs[0].data) > 0
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@pytest.mark.predictor
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@pytest.mark.asyncio(scope="session")
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async def test_autogluon_runtime_kserve_v2_storage_uri_without_trailing_slash(
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rest_v2_client,
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):
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service_name = "isvc-autogluon-v2-noslash"
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storage_uri = AUTOGLUON_STORAGE_URI.rstrip("/")
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predictor = _create_predictor(
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service_name, protocol_version="v2", storage_uri=storage_uri
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)
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response = await deploy_and_predict(
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service_name,
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predictor,
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rest_v2_client,
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"./data/autogluon_titanic_input_v2.json",
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)
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assert len(response.outputs) > 0
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assert len(response.outputs[0].data) > 0
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