v0.2.0
Version 0.2.0
We're happy to announce the AutoGluon-Cloud 0.2.0 release. This release added support for TimeSeriesCloudPredictor.
Please give it a try and provide us feedback!
Currently, AutoGluon-Cloud supports training and deploying TabularPredictor, MultiModalPredictor and TimeSeriesPredictor with AutoGluon Deep Learning Containers version 0.6.0 and newer.
It is always recommended to use the latest version of the container as it has more features and are updated with security patches.
To learn more, check out our tutorial
This release contains 27 commits from 2 contributors.
See the full commit change-log here: 0.1.0...0.2.0
Full Contributor List (ordered by # of commits):
This release supports Python versions 3.8, 3.9, and 3.10. Python 3.7 is no longer supported as of this release.
NEW: TimeSeriesCloudPredictor
We are happy to announce that you can train TimeSeriesPredictor with SageMaker backend in the cloud just like TabularPredictor and MultiModalPredictor now.
Checkout the quick example here!
NEW Doc Site Style
We have updated the doc site to match the new style being used by the main AutoGluon site.
Check it out here
General:
- Added Python 3.10 support and dropped python 3.7 support. @yinweisu (#29)
- Updated dependency ranges. @yinweisu (#59)
Improvements and Refactoring:
- Concurrency and space controls for large models. @yinweisu (#42)
- Extract Sagemaker backend. @yinweisu (#43)
- IAM role and policy utils. @yinweisu (#53)
- Add better warning message for
to_local_predictor()call. @yinweisu (#64)
Bug Fixes/Doc Improvements:
CI:
Distributed Training:
Added components to support distributed training in the future. This feature is not available yet, but is being actively working on
- Ray interface. @yinweisu (#43)
- Ray AWS Cluster Config Generator. @yinweius (#47)
- Ray AWS Cluster Manager. @yinweisu (#49)
- Ray Job. @yinweisu (#51)
