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feat(sdk): Support loading pipeline from yaml #8209

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merged 4 commits into from
Aug 31, 2022

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chensun
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@chensun chensun commented Aug 30, 2022

Description of your changes:

  • Support loading pipeline from yaml to use as a component.
  • Fix bug where InputSpec ignores artifacts inputs from IR.
  • Fix bug where executor label and component name may not be merged correctly due to name collision.

Checklist:

@google-oss-prow google-oss-prow bot requested a review from zijianjoy August 30, 2022 09:43
@chensun chensun removed the request for review from zijianjoy August 30, 2022 09:43
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chensun commented Aug 30, 2022

/test kubeflow-pipelines-samples-v2

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Thanks Chen! /lgtm

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chensun commented Aug 30, 2022

/test kubeflow-pipelines-samples-v2

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chensun commented Aug 30, 2022

/test kubeflow-pipelines-samples-v2

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chensun commented Aug 30, 2022

/test kubeflow-pipelines-samples-v2

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Reviewing this 👀

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Thanks, @chensun. I think this there may be an idempotency issue or at least something I have a question about.

This implementation results in changing PipelineSpec when you reload the pipeline. Try appending the following to one of the pipeline files, running it, then inspecting the one.yaml and two.yaml files. They are different.

if __name__ == '__main__':
    compiler.Compiler().compile(
        pipeline_func=my_pipeline,
        package_path='one.yaml')

    from kfp import components
    with open('one.yaml', 'r') as f:
        reloaded_pipeline = components.load_component_from_text(f.read())
    compiler.Compiler().compile(
        reloaded_pipeline, package_path='two.yaml')

I don't think this is desired, correct? Even if the underlying pipeline logic is itself correct. WDYT?

If I am correct, the read/write tests will be very helpful for validating correctness across a diversity of pipelines if you switch the .pipelines.config.read flag to True, plus make a few other changes (see this commit for the additional changes needed: connor-mccarthy@746d787). If I am not correct, we probably still want to use the read/write tests to validate correctness, but they will need more attention in order to do so.

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chensun commented Aug 31, 2022

Thanks, @chensun. I think this there may be an idempotency issue or at least something I have a question about.

This implementation results in changing PipelineSpec when you reload the pipeline. Try appending the following to one of the pipeline files, running it, then inspecting the one.yaml and two.yaml files. They are different.

if __name__ == '__main__':
    compiler.Compiler().compile(
        pipeline_func=my_pipeline,
        package_path='one.yaml')

    from kfp import components
    with open('one.yaml', 'r') as f:
        reloaded_pipeline = components.load_component_from_text(f.read())
    compiler.Compiler().compile(
        reloaded_pipeline, package_path='two.yaml')

I don't think this is desired, correct? Even if the underlying pipeline logic is itself correct. WDYT?

If I am correct, the read/write tests will be very helpful for validating correctness across a diversity of pipelines if you switch the .pipelines.config.read flag to True, plus make a few other changes (see this commit for the additional changes needed: connor-mccarthy@746d787). If I am not correct, we probably still want to use the read/write tests to validate correctness, but they will need more attention in order to do so.

That's a good point. Although the changed PipelineSpec is still correct, agree that it is ideal to maintain consistency across read and write. Made the change.

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chensun commented Aug 31, 2022

All test passed. Merging this to unblock my next PR.
@connor-mccarthy please feel free to add additional comments, I'll address them in a follow up PR if needed. Thanks!

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@google-oss-prow google-oss-prow bot merged commit 410e99c into kubeflow:master Aug 31, 2022
@chensun chensun deleted the load-pipeline branch August 31, 2022 12:10
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This looks great, @chensun. Thank you for updating the tests!

/lgtm

def from_deployment_spec_dict(cls, deployment_spec_dict: Dict[str, Any],
component_name: str) -> 'Implementation':
def from_pipeline_spec_dict(cls, pipeline_spec_dict: Dict[str, Any],
component_name: str) -> 'Implementation':
"""Creates an Implmentation object from a deployment spec message in
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I think docstrings are out of date

else:
pipeline_spec = json_format.ParseDict(
pipeline_spec_dict, pipeline_spec_pb2.PipelineSpec())
return Implementation(graph=pipeline_spec)
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👍🏻



class YamlComponent(components.BaseComponent):
"""A component loaded from a YAML file.

**Note:** ``YamlComponent`` is not intended to be used to construct components directly. Use ``kfp.components.load_component_from_*()`` instead.

Args:
Artribute:
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Suggested change
Artribute:
Attributes:

@@ -511,18 +523,16 @@ def transform_outputs(self) -> None:
def validate_placeholders(self):
"""Validates that input/output placeholders refer to an existing
input/output."""
implementation = self.implementation
if getattr(implementation, 'container', None) is None:
if self.implementation.container is None:
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👍🏻

@@ -1470,12 +1488,11 @@ def _rename_component_refs(
sub_pipeline_spec.root)


def create_pipeline_spec_and_deployment_config(
def create_pipeline_spec(
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I like this change

jlyaoyuli pushed a commit to jlyaoyuli/pipelines that referenced this pull request Jan 5, 2023
* support loading pipeline from yaml

* release note

* cleanup

* maintain read/write consistency with component/pipeline compilation.
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3 participants