pipelines/sdk/python/tests/compiler/testdata/artifact_passing_using_volu...

47 lines
1.6 KiB
Python

from pathlib import Path
import kfp
from kfp.components import load_component_from_file
test_data_dir = Path(__file__).parent / 'test_data'
producer_op = load_component_from_file(
str(test_data_dir / 'produce_2.component.yaml'))
processor_op = load_component_from_file(
str(test_data_dir / 'process_2_2.component.yaml'))
consumer_op = load_component_from_file(
str(test_data_dir / 'consume_2.component.yaml'))
@kfp.dsl.pipeline()
def artifact_passing_pipeline():
producer_task = producer_op()
processor_task = processor_op(producer_task.outputs['output_1'],
producer_task.outputs['output_2'])
consumer_task = consumer_op(processor_task.outputs['output_1'],
processor_task.outputs['output_2'])
# This line is only needed for compiling using dsl-compile to work
kfp.dsl.get_pipeline_conf(
).data_passing_method = volume_based_data_passing_method
from kubernetes.client.models import V1Volume, V1PersistentVolumeClaimVolumeSource
from kfp.dsl import data_passing_methods
volume_based_data_passing_method = data_passing_methods.KubernetesVolume(
volume=V1Volume(
name='data',
persistent_volume_claim=V1PersistentVolumeClaimVolumeSource(
claim_name='data-volume',),
),
path_prefix='artifact_data/',
)
if __name__ == '__main__':
pipeline_conf = kfp.dsl.PipelineConf()
pipeline_conf.data_passing_method = volume_based_data_passing_method
kfp.compiler.Compiler().compile(
artifact_passing_pipeline,
__file__ + '.yaml',
pipeline_conf=pipeline_conf)