Add additional step to pipeline to generate a metrics report #241
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tumido
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@tumido updated the PR to use PVC's instead of interim output artifacts. |
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Signed-off-by: Michael Clifford <[email protected]>
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| @@ -463,6 +484,21 @@ def pipeline( | |||
| model_pvc_delete_task = DeletePVC(pvc_name=model_pvc_task.output) | |||
| model_pvc_delete_task.after(final_eval_task) | |||
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| generate_metrics_report_task = generate_metrics_report_op() | |||
| generate_metrics_report_task.after(output_mt_bench_task, final_eval_task) | |||
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I don't think this requires to be run after output_mt_bench_task. That task only uploads artifacts. In fact both output_mt_bench_task and generate_metrics_report_task can run in parallel, they only read the same data.
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This PR adds a new step to the end of the pipeline,
generate_metrics_report_op. The purpose of this step is to create a number of kfpMerticartifacts that can help users easily compare the performance between different runs using thecompare runsfeature of the Data Science Pipeline UI.