v1.2.0

Features

• Remove unnecessary dependencies.

Bug Fixes and Other Changes

• Fix python 2 tox dependencies.
• copy all tests to test-toolkit folder.
• Update license URL
• Adding changes for PyTorch 1.4.0 DLC

v1.1.0

Features

• Add release to PyPI. Change package name to sagemaker-pytorch-training.

Bug Fixes and Other Changes

• Fix flake8 erros. Add flake configuration to run during PR.
• Add twine section to tox.
• Update build artifacts
• update: Bump awscli version and constrain spyder on conda
• update: bump smdebug version to 0.5.0.post0
• Create init.py
• run local GPU tests for Python 3
• update: Update buildspec for PyTorch 1.3.1
• update copyright year in license header
• Added changes for DLC 2.1 with PyTorch v1.3.1
• Remove stale-bot config
• upgrade sagemaker-containers to 2.5.11
• upgrade pillow to 6.2.0
• use SageMaker Containers' ProcessRunner for executing the entry point
• use regional endpoint for STS in builds
• update instance type region availability.
• Update Dockerfile.gpu
• Removing extra packages to optimize space
• Adding function to skip test for py2 verison
• Installing tochvision from official pip wheel
• Add /bin/bash as default CMD
• Pytorch 1.2 py2 py3 dockerfiles added
• Add wait on entrypoint
• Add entrypoint script
• split training and serving logic

Testing and Release Infrastructure

• properly fail build if has-matching-changes fails
• properly fail build if has-matching-changes fails

AWS Deep Learning Containers for PyTorch Training v2.1

This tag refers to the release of AWS Deep Learning Containers for PyTorch Training version 2.1. The images below were built using the PyTorch 1.3.1 Dockerfiles at this commit of master. Subsequent Dockerfile commits to master will be incorporated in future releases.

763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:1.3.1-cpu-py36-ubuntu16.04-v2.1
763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:1.3.1-cpu-py27-ubuntu16.04-v2.1
763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:1.3.1-gpu-py36-cu101-ubuntu16.04-v2.1
763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:1.3.1-gpu-py27-cu101-ubuntu16.04-v2.1

v1.0.9

Bug fixes and other changes

• fix placeholder name cpu-instance-type in buildspec-release.yml

v1.0.8

Bug fixes and other changes

• Update no-p2 and no-p3 regions.

v1.0.7

Bug fixes and other changes

• upgrade sagemaker-container version

v1.0.4

Bug fixes and other changes

• skip tests in gpu instance restricted regions

v1.0.3

Bug fixes and other changes

• modify buildspecs and tox files

v1.0.2

Bug fixes and other changes

• freeze dependency versions

v1.0.1

Bug fixes and other changes

• add buildspec-release file and upgrade cuda version
• upgrade PyTorch to 1.1
• disable test_mnist_gpu for py2 for now
• fix broken line of buildspec
• prevent hidden errors in buildspec
• Add AWS CodeBuild buildspec for pull request
• Bump minimum SageMaker Containers version to 2.4.6 and pin SageMaker Python SDK to 1.18.16
• fix broken link in README
• Add timeout to test_mnist_gpu test
• Use dummy role in tests and update local failure integ test
• Use the SageMaker Python SDK for local serving integ tests
• Use the SageMaker Python SDK for local integ distributed training tests
• Use the SageMaker Python SDK for local integ single-machine training tests
• Pin fastai version to 1.0.39 in CPU dockerfile
• Use the SageMaker Python SDK for SageMaker integration tests
• Add missing rendering dependencies for opencv and a simple test.
• Add opencv support.
• Freeze PyYAML version to avoid conflict with Docker Compose
• Unfreeze numpy version.
• Freeze TorchVision to 0.2.1
• Specify region when creating S3 resource in integ tests
• Read framework version from Python SDK for integ test default
• Fix unicode display problem in py2 container
• freeze pip <=18.1, fastai == 1.0.39, numpy <= 1.15.4
• Add support for fastai (https://github.com/fastai/fastai) library.
• Remove "requsests" from tests dependencies to avoid regular conflicts with "requests" package from "sagemaker" dependencies.
• Add support for PyTorch-1.0.