- Revise flaml.tune API
- Add a “scheduler” argument (a user can choose from “flaml”, “asha” or a customized scheduler)
- Rename "prune_attr" to "resource_attr"
- Rename “training_function” to “evaluation_function”
- Remove the “report_intermediate_result” argument (covered by “scheduler” instead)
- Add tests for the supported schedulers
- Re-run notebooks that use schedulers
- Add save_best_config() to save best config in a json file
What's Changed
- add save_best_config() by @sonichi in #324
- tune api for schedulers by @qingyun-wu in #322
- add init.py in nlp by @sonichi in #325
- rename training_function by @qingyun-wu in #327
Full Changelog: v0.8.2...v0.9.0