Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Adds job_id parameter. #3850

Conversation

AndrewLeach
Copy link
Contributor

Adds job_id parameter to ml_engine train component.

  • job_id parameter takes precedence over job_id_prefix when defined.
  • When set, job_id is known before task creation and can be consumed by other tasks while running.
  • Does not interfere with current job_id_prefix when unset to avoid breaking pipelines which depend on it.
  • Does not modify for predict jobs which use the same pattern.

…dence over job_id generated from job_id_prefix.
@review-notebook-app
Copy link

Check out this pull request on  ReviewNB

Review Jupyter notebook visual diffs & provide feedback on notebooks.


Powered by ReviewNB

@kubeflow-bot
Copy link

This change is Reviewable

@k8s-ci-robot
Copy link
Contributor

Hi @AndrewLeach. 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 /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.

Once the patch is verified, the new status will be reflected by the ok-to-test label.

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.

@AndrewLeach AndrewLeach marked this pull request as ready for review May 29, 2020 21:23
@Ark-kun Ark-kun removed the request for review from gaoning777 June 1, 2020 09:18
@Ark-kun
Copy link
Contributor

Ark-kun commented Jun 1, 2020

/ok-to-test

@Ark-kun
Copy link
Contributor

Ark-kun commented Jun 1, 2020

/test kubeflow-pipeline-frontend-test

@Ark-kun
Copy link
Contributor

Ark-kun commented Jun 1, 2020

/approve

@k8s-ci-robot
Copy link
Contributor

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: Ark-kun

The full list of commands accepted by this bot can be found here.

The pull request process is described here

Needs approval from an approver in each of these files:

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

@Ark-kun
Copy link
Contributor

Ark-kun commented Jun 1, 2020

/lgtm

@Ark-kun
Copy link
Contributor

Ark-kun commented Jun 1, 2020

/retest

@k8s-ci-robot k8s-ci-robot merged commit 58f1d13 into kubeflow:master Jun 1, 2020
RedbackThomson pushed a commit to RedbackThomson/pipelines that referenced this pull request Jun 17, 2020
* Adds job_id parameter to ml_engine train component, which takes precedence over job_id generated from job_id_prefix.

* Restores ipynb config.

Co-authored-by: andrewleach <andrewleach@google.com>
Ark-kun added a commit to Ark-kun/pipelines that referenced this pull request Aug 29, 2020
Fixes kubeflow#4430
The issue was introduced in kubeflow#3850. That PR has added a new parameter in the middle of the the create_job function signature which can cause breaking changes as the parameter ordering changes.
k8s-ci-robot pushed a commit that referenced this pull request Sep 3, 2020
…ixes #4430 (#4432)

* Components - Fixed the GCP - ML Engine - Batch predict component

Fixes #4430
The issue was introduced in #3850. That PR has added a new parameter in the middle of the the create_job function signature which can cause breaking changes as the parameter ordering changes.

* Fixed test
Jeffwan pushed a commit to Jeffwan/pipelines that referenced this pull request Dec 9, 2020
* Adds job_id parameter to ml_engine train component, which takes precedence over job_id generated from job_id_prefix.

* Restores ipynb config.

Co-authored-by: andrewleach <andrewleach@google.com>
Jeffwan pushed a commit to Jeffwan/pipelines that referenced this pull request Dec 9, 2020
…ixes kubeflow#4430 (kubeflow#4432)

* Components - Fixed the GCP - ML Engine - Batch predict component

Fixes kubeflow#4430
The issue was introduced in kubeflow#3850. That PR has added a new parameter in the middle of the the create_job function signature which can cause breaking changes as the parameter ordering changes.

* Fixed test
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

Successfully merging this pull request may close these issues.

6 participants