Releases: aws/sagemaker-python-sdk
Releases · aws/sagemaker-python-sdk
v1.38.0
Features
- support training inputs from EFS and FSx
v1.37.2
Bug fixes and other changes
- Add support for Managed Spot Training and Checkpoint support
- Integration Tests now dynamically checks AZs
v1.37.1
Bug fixes and other changes
- eliminate dependency on mnist dataset website
Documentation changes
- refactor using_sklearn and fix minor errors in using_pytorch and using_chainer
v1.37.0
Features
- add XGBoost Estimator as new framework
Bug fixes and other changes
- fix tests for new regions
- add update_endpoint for PipelineModel
Documentation changes
- refactor the using Chainer topic
v1.36.4
Bug fixes and other changes
- region build from staging pr
Documentation changes
- Refactor Using PyTorch topic for consistency
v1.36.3
Bug fixes and other changes
- fix integration test failures masked by timeout bug
- prevent multiple values error in sklearn.transformer()
- model.transformer() passes tags to create_model()
v1.36.2
Bug fixes and other changes
- rework CONTRIBUTING.md to include a development workflow
v1.36.1
Bug fixes and other changes
- prevent integration test's timeout functions from hiding failures
Documentation changes
- correct typo in using_sklearn.rst
v1.36.0
Features
- support for TensorFlow 1.14
Bug fixes and other changes
- ignore FI18 flake8 rule
- allow Airflow enabled estimators to use absolute path entry_point
v1.35.1
Bug fixes and other changes
- update sklearn document to include 3p dependency installation
Documentation changes
- refactor and edit using_mxnet topic