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Releases: aws/sagemaker-python-sdk

v1.38.0

23 Aug 16:39
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Features

  • support training inputs from EFS and FSx

v1.37.2

20 Aug 22:00
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Bug fixes and other changes

  • Add support for Managed Spot Training and Checkpoint support
  • Integration Tests now dynamically checks AZs

v1.37.1

19 Aug 17:41
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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

15 Aug 16:34
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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

13 Aug 22:52
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Bug fixes and other changes

  • region build from staging pr

Documentation changes

  • Refactor Using PyTorch topic for consistency

v1.36.3

13 Aug 17:37
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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

12 Aug 17:38
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Bug fixes and other changes

  • rework CONTRIBUTING.md to include a development workflow

v1.36.1

08 Aug 17:37
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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

07 Aug 15:45
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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

01 Aug 17:39
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Bug fixes and other changes

  • update sklearn document to include 3p dependency installation

Documentation changes

  • refactor and edit using_mxnet topic