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Added configArtifactRepository method into sdk/python/kfp/compiler/compiler.py
#765
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[APPROVALNOTIFIER] This PR is NOT APPROVED This pull-request has been approved by: If they are not already assigned, you can assign the PR to them by writing The full list of commands accepted by this bot can be found here. The pull request process is described here
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Hi @DmitryBe. Thanks for your PR. I'm waiting for a kubeflow member to verify that this patch is reasonable to test. If it is, they should reply with Once the patch is verified, the new status will be reflected by the I understand the commands that are listed here. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. |
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Hi @DmitryBe. Thanks for your PR. I'm waiting for a kubeflow member to verify that this patch is reasonable to test. If it is, they should reply with Once the patch is verified, the new status will be reflected by the I understand the commands that are listed here. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. |
/assign @gaoning777 |
Hi @Ark-kun, Thank you for your review. To make it clear, in order to add AWS S3 support for storing artifacts, I have made 3 PR in total:
To extend python DSL, i have added |
sdk/python/kfp/compiler/compiler.py
Hi @Ark-kun, |
def configArtifactRepository(self, endpoint='minio-service.kubeflow:9000', bucket='mlpipeline', keyPrefix='runs', accessKey='accesskey', secretKey='secretkey', insecure=True): | ||
"""Config artifact repository | ||
""" | ||
self.artifactRepositoryConfig = Compiler.ArtifactRepositoryConfig( |
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Can you make this field private (leading underscore)?
@@ -557,6 +584,19 @@ def _compile(self, pipeline_func): | |||
workflow = self._create_pipeline_workflow(args_list_with_defaults, p) | |||
return workflow | |||
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def configArtifactRepository(self, endpoint='minio-service.kubeflow:9000', bucket='mlpipeline', keyPrefix='runs', accessKey='accesskey', secretKey='secretkey', insecure=True): |
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Python uses snake_case
for function names. def set_artifact_repository(...)
@IronPan @DmitryBe Do you think that it would be better to configure this at the cluster level and not bake this information into the pipeline file? I think a better solution would be for the backend to read the default artifact repository information from cluster's ConfigMap and add it to the workflow at submission time. WDYT? |
I've also noticed that this configuration is S3-only while Argo supports more artifact storage solutions. We can either indicate that the config is S3-only in the name or make a more generic solution. /ok-to-test |
BTW, I had a PR where I've made the artifact storage configurable on the cluster level and made the compiled pipelines portable: #513 |
@DmitryBe: The following tests failed, say
Full PR test history. Your PR dashboard. Please help us cut down on flakes by linking to an open issue when you hit one in your PR. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here. |
The support for setting the artifact storage options was merged in different PRs. |
This functionality has already been merged. |
Added configArtifactRepository method into
sdk/python/kfp/compiler/compiler.py
Example:
This change is