kfp-tekton/sdk/python/tests/compiler/testdata/pipeline_transformers.py

53 lines
1.6 KiB
Python

# Copyright 2020 kubeflow.org
#
# 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.
from kfp import dsl, components
def print_op(msg: str):
"""Print a message."""
return components.load_component_from_text("""
name: print
description: print out msg
inputs:
- {name: msg, type: String}
implementation:
container:
image: alpine:3.6
command:
- echo
- {inputValue: msg}
""")(msg=msg)
def add_annotation_and_label(op):
op.add_pod_annotation(name='hobby', value='football')
op.add_pod_label(name='hobby', value='football')
return op
@dsl.pipeline(
name='pipeline-transformer',
description='The pipeline shows how to apply functions to all ops in the pipeline by pipeline transformers'
)
def transform_pipeline():
op1 = print_op('hey, what are you up to?')
op2 = print_op('train my model.')
dsl.get_pipeline_conf().add_op_transformer(add_annotation_and_label)
if __name__ == '__main__':
from kfp_tekton.compiler import TektonCompiler
TektonCompiler().compile(transform_pipeline, __file__.replace('.py', '.yaml'))