v0.7.0

See: https://github.com/pytorch/torchx/blob/main/CHANGELOG.md#torchx-070

v0.6.0

See: https://github.com/pytorch/torchx/blob/main/CHANGELOG.md#torchx-060

v0.5.0

See: https://github.com/pytorch/torchx/blob/main/CHANGELOG.md#torchx-050

v0.4.0

See: https://github.com/pytorch/torchx/blob/main/CHANGELOG.md#torchx-040

v0.3.0

See https://github.com/pytorch/torchx/blob/main/CHANGELOG.md?plain=1#L3

v0.2.0

See https://github.com/pytorch/torchx/blob/main/CHANGELOG.md?plain=1#L3

v0.1.2

Full Changelog: v0.1.1...v0.1.2

Milestone: https://github.com/pytorch/torchx/milestones/3

• PyTorch 1.11 Support
• Python 3.10 Support
• torchx.workspace
  • TorchX now supports a concept of workspaces. This enables seamless launching
    of jobs using changes present in your local workspace. For Docker based
    schedulers, we automatically build a new docker container on job launch
    making it easier than ever to run experiments. #333
• torchx.schedulers
  • Ray #329
    • Newly added Ray scheduler makes it easy to launch jobs on Ray.
    • https://pytorch.medium.com/large-scale-distributed-training-with-torchx-and-ray-1d09a329aacb
  • AWS Batch #381
    • Newly added AWS Batch scheduler makes it easy to launch jobs in AWS with minimal infrastructure setup.
  • Slurm
    • Slurm jobs will by default launch in the current working directory to match local_cwd and workspace behavior. #372
    • Replicas now have their own log files and can be accessed programmatically. #373
    • Support for comment, mail-user and constraint fields. #391
    • Workspace support (prototype) - Slurm jobs can now be launched in isolated experiment directories. #416
  • Kubernetes
    • Support for running jobs under service accounts. #408
    • Support for specifying instance types. #433
  • All Docker-based Schedulers (Kubernetes, Batch, Docker)
    • Added bind mount and volume supports #420, #426
    • Bug fix: Better shm support for large dataloader #429
    • Support for .dockerignore and custom Dockerfiles #401
  • Local Scheduler
    • Automatically set CUDA_VISIBLE_DEVICES #383
    • Improved log ordering #366
• torchx.components
  • dist.ddp
    • Rendezvous works out of the box on all schedulers #400
    • Logs are now prefixed with local ranks #412
    • Can specify resources via the CLI #395
    • Can specify environment variables via the CLI #399
  • HPO
    • Ax runner now lives in the Ax repo facebook/Ax@8e2e68f
• torchx.cli
  • .torchxconfig
    • You can now specify component argument defaults .torchxconfig c37cfd7
    • ~/.torchxconfig can now be used to set user level defaults. #378
    • --workspace can be configured #397
  • Color change and bug fixes #419
• torchx.runner
  • Now supports workspace interfaces. #360
  • Returned lines now preserve whitespace to provide support for progress bars #425
  • Events are now logged to torch.monitor when available. #379
• torchx.notebook (prototype)
  • Added new workspace interface for developing models and launching jobs via a Jupyter Notebook. #356
• Docs
  • Improvements to clarify TorchX usage w/ workspaces and general cleanups.
  • #374, #402, #404, #407, #434

v0.1.1

See: https://github.com/pytorch/torchx/blob/main/CHANGELOG.md#torchx-011

v0.1.0

See: https://github.com/pytorch/torchx/blob/master/CHANGELOG.md

v0.1.0rc1

See: https://github.com/pytorch/torchx/blob/master/CHANGELOG.md