pythongoogle-cloud-platformgoogle-cloud-vertex-aikubeflow-pipelinesvertex-ai-pipeline

Custom Labels in Vertex AI Pipeline PipelineJobSchedule

I would like to know the steps involved in adding custom labels to a Vertex AI pipeline’s PipelineJobSchedule. Can anyone please provide me with the necessary guidance as it's not working when I am adding inside the Pipelinejob parameters?

# https://cloud.google.com/vertex-ai/docs/pipelines/schedule-pipeline-run#create-a-schedule
pipeline_job = aiplatform.PipelineJob(
  template_path="COMPILED_PIPELINE_PATH",
  pipeline_root="PIPELINE_ROOT_PATH",
  display_name="DISPLAY_NAME",
  labels="{"name":"test_xx"}"
)
pipeline_job_schedule = aiplatform.PipelineJobSchedule(
  pipeline_job=pipeline_job,
  display_name="SCHEDULE_NAME"
)

pipeline_job_schedule.create(
  cron="TZ=CRON",
  max_concurrent_run_count=MAX_CONCURRENT_RUN_COUNT,
  max_run_count=MAX_RUN_COUNT,
)
Solution

  • There was a bug in the Vertex AI platform SDK which has been discussed in the Github issue ticket below. It has been fixed in SDK versions 1.37.0 (released on December 5th, 2023).

    GitHub Issue ticket