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Releases: aws/sagemaker-pytorch-training-toolkit

v2.1.0

04 May 15:20
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Features

  • add Dockerfiles for PyTorch 1.5.0

v2.0.0

27 Apr 15:25
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Breaking Changes

  • Replace sagemaker-containers with sagemaker-training

v1.3.3

16 Apr 15:20
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Bug Fixes and Other Changes

  • change miniconda installation in 1.4.0 Dockerfiles

Testing and Release Infrastructure

  • parallelize SageMaker integ test runs
  • remove (unused) model_fn from training scripts

v1.3.2

07 Apr 15:20
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Bug Fixes and Other Changes

  • bump smdebug version

Testing and Release Infrastructure

  • add requirements.txt integ test

v1.3.1

02 Apr 15:20
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Bug Fixes and Other Changes

  • upgrade pillow etc. to fix safety issues
  • Upgrade sagemaker-containers and test with more than 1 epoch

v1.3.0

23 Mar 19:55
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Features

  • Install toolkit from PyPI.

Bug Fixes and Other Changes

  • upgrade sagemaker-containers to 2.8.2
  • Install jupyter_client 5.3.4 in advanced for py2 gpu image
  • update smdebug

Testing and Release Infrastructure

  • run test-toolkit unit tests for release
  • run build steps only when necessary.
  • refactor toolkit tests.

v1.2.4

12 Mar 15:20
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Bug Fixes and Other Changes

  • install sm experiments always when python 3.6 or greater

v1.2.3

11 Mar 15:19
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Bug Fixes and Other Changes

  • Update smdebug to 0.7.0
  • install sagemaker-experiments package only for 3.6

v1.2.2

10 Mar 15:19
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Bug Fixes and Other Changes

  • upgrade to latest sagemaker-experiments
  • install SageMaker Python SDK into Python 3 images

v1.2.1

09 Mar 15:19
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Bug Fixes and Other Changes

  • Install awscli from pypi instead of conda for PyTorch containers