pipelines/samples/core/artifact_location/artifact_location.py

52 lines
1.9 KiB
Python

#!/usr/bin/env python3
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import kfp
from kfp import dsl
from kubernetes.client import V1SecretKeySelector
@dsl.pipeline(
name="custom_artifact_location_pipeline",
description="""A pipeline to demonstrate how to configure the artifact
location for all the ops in the pipeline.""",
)
def custom_artifact_location(
secret_name: str = "mlpipeline-minio-artifact",
tag: str = '1.31.0',
namespace: str = "kubeflow",
bucket: str = "mlpipeline"
):
# configures artifact location
pipeline_artifact_location = dsl.ArtifactLocation.s3(
bucket=bucket,
endpoint="minio-service.%s:9000" % namespace, # parameterize minio-service endpoint
insecure=True,
access_key_secret=V1SecretKeySelector(name=secret_name, key="accesskey"),
secret_key_secret={"name": secret_name, "key": "secretkey"}, # accepts dict also
)
# set pipeline level artifact location
dsl.get_pipeline_conf().set_artifact_location(pipeline_artifact_location)
# artifacts in this op are stored to endpoint `minio-service.<namespace>:9000`
op = dsl.ContainerOp(name="foo", image="busybox:%s" % tag,
command=['sh', '-c', 'echo hello > /tmp/output.txt'],
file_outputs={'output': '/tmp/output.txt'})
if __name__ == '__main__':
kfp.compiler.Compiler().compile(custom_artifact_location, __file__ + '.zip')