Accelerated Data Science 2.10.0 is released

The following changes were made in ADS 2.10.0:

  • Improved the progress bar to use the percentage completed of workflow request instead of hardcoded steps.
  • Used the service default for WEB_CONCURRENCY for model deployment.
  • Fixed the bug with zipping the model artifacts directory when TMPRDIR is provided.
  • Improved the watch() method for model deployment to keep streaming logs when the deployment is finished.
  • Changed the default log type of watch to both access logs and predict logs.
  • Changed the target directory to artifact_dir instead of temp directory when saving the model artifacts.
  • Fixed the mount file system pre-check to check for duplicate dest.
  • Fixed duplicate logs in the model deployment consolidated logs.
  • Added support for the optional downloading of artifacts in GenericMode using a download_artifact() method.
  • Set the Data Science service endpoint through the environment variable in OCIDataScienceMixin.
  • Made reloading the model to environment as optional at the time of invoking GenericModel.from_id().
  • Mandated the Python version in GenericModel.prepare() when it can't be resolved.
  • Added a print out of the model deployment OCID in the notebook cell when deploy() is called.