feat: update the samples of hyperparameter tuning in the public doc #1600
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| hpt_job = aiplatform.HyperparameterTuningJob( | ||
| display_name=display_name, | ||
| custom_job=custom_job, | ||
| metric_spec={ |
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We usually pass in some of these as parameters to the function but I'm not sure how to include things like parameter specs without cluttering the parameter space with all possible parameters to CustomJob and HyperparameterTuningJob.
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@dizcology do you have guidance or is this okay?
| }, | ||
| "replica_count": 1, | ||
| "container_spec": { | ||
| "image_uri": container_uri, |
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Seems weird to pass in container_uri when it's not used in the tuning job.
@dizcology thoughts?
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Hptuning job creates sub jobs(trials) using the container image uri, it's actually used by the vertex hptuning jobs.
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In the future, please have one PR per sample. |
| }, | ||
| "replica_count": 1, | ||
| "container_spec": { | ||
| "image_uri": container_uri, |
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Hptuning job creates sub jobs(trials) using the container image uri, it's actually used by the vertex hptuning jobs.
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Fixes #240582178 🦕