GoogleCloudPlatform / GoogleCloudPlatform/cloudml-hypertune
Stable release
- Dominant language
- Python
- Stars
- 40
- Forks
- 18
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Description
Even though this is the recommended way to use hyperparameter tuning jobs on Vertex AI [according to the documentation](https://cloud.google.com/vertex-ai/docs/training/using-hyperparameter-tuning#report-metrics) the latest release is an alpha-quality release (`v0.1.0.dev6`), from 2019, which only declares to be compatible with python `3.5` (hasn't been supported for a year and a half now), and has failing CI on `main`.
The current state of affairs makes it so that the only reliable path to using hyperparameter tuning in Vertex AI I find is creating my own implementation, which is simple enough as it's just writing a json to a specific location on disk, but seems a bit of a waste given that there's already an "official" implementation.
But I think ideally this should be better supported by GCP itself, as easy distributed hparam tuning is one of the major competitive advantages Vertex AI has over some alternatives.
It'd be good to have a stable (i.e. non-alpha) release of this library with explicit support for python 3.7 to 3.10.
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