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Improve TFX Taxi Sample and Components. #512

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@qimingj qimingj commented Dec 11, 2018

  • Confusion matrix and ROC components support flexible target.
  • Use single mode instead of 4 different modes for TFDV, TFMA, TFT, Predicton.
  • TFDV output's schema path directly.
  • Add Confusion Matrix and ROC components to tf taxi sample.

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if args.target_lambda:
df['target'] = df.apply(eval(args.target_lambda), axis=1)

# Convert "True" to "True_" and "False" to "False_" for frontend to work.
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This looks very hacky. Could you add a bug ID here to explain why it's needed?

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We are still investigating. #446. Will add that to comments

parser.add_argument('--target_lambda', type=str,
help='a lambda function as a string to determine positive or negative.' +
'For example, "lambda x: x[\'a\'] and x[\'b\']". If missing, ' +
'trueclass must be set.')
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and input must have a target column.

'--output', '%s/{{workflow.name}}/roc' % output,
'--predictions', predictions,
'--target_lambda', """lambda x: 1 if (x['target'] > x['fare'] * 0.2) else 0""",
'--trueclass', 'true',
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Is it still needed?

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Linchin pushed a commit to Linchin/pipelines that referenced this pull request Apr 11, 2023
…and E2E clusters (kubeflow#512)

* cleanup_ci needs to use different expiration times for auto deployed and E2E clusters

* The auto deployed clusters are now using unique names rather than being
  recycled and we rely on cleanup_ci.py to GC old auto-deployments (kubeflow#444)

* To support this we need to use variable expiration times.

  * Deployments created by tests should expire as soon as the test is done (so 1-2 hours)

  * But auto-deployed clusters need to live longer

    * There are only refreshed periodically by a cron job (~8 hours) we don't
      want to delete the cluster before a new one is deployed because we need
      a cluster for the example tests

    * We want to leave the clusters up as long as we can to facilitate debugging
      by people working on example tests.

Related to kubeflow#444

* Address reviewer comments.
magdalenakuhn17 pushed a commit to magdalenakuhn17/pipelines that referenced this pull request Oct 22, 2023
* Fix typo in resources

* Allow number of workers to be specified for Tornando

* remove comment
HumairAK pushed a commit to red-hat-data-services/data-science-pipelines that referenced this pull request Mar 11, 2024
…p CRs for the users (kubeflow#512)

* add auto apply custom task CRs before pipelineRun creation

* fix lint

* store loop resource in ordered dict

* Update kfp-admin-guide.md

* sorted pipeline params to avoid randomness

* sorted pipeline params to avoid randomness

* regenerate tests

* convert template string from yaml to json

* regenerate tests

* clean up unnecessary helper function

* resolve merge conflicts

* resolve merge conflicts

* remove unnecessary go mod package

* only opt-in to embed the recursion loop annotations

* only opt-in to embed the recursion loop annotations

* enable opt-in only via package variable

* add example for how to inline recursive loops

* resolve conflicts

* regenerate tests

* make auto generate and apply recursive pipelineloop in annotations as default

* move parameter sorting to the end

* add parameter sorting for recursion loops

* sort recursive task parameters

* add more details on how to opt-out auto apply custom resource
HumairAK pushed a commit to red-hat-data-services/data-science-pipelines that referenced this pull request Mar 11, 2024
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3 participants