Highlight
- You can now cancel remote tasks using the
ray.cancel API.
- PyTorch is now a first-class citizen in RLlib! We've achieved parity between TensorFlow and PyTorch.
- Did you struggle to find good example code for Ray ML libraries? We wrote more examples for Ray SGD and Ray Serve.
Core
- Task cancellation is now available for locally submitted tasks. (#7699)
- 📌 Experimental support for recovering objects that were lost from the Ray distributed memory store. You can try this out by setting
lineage_pinning_enabled: 1 in the internal config. (#7733)
RLlib
- 👍 PyTorch support has now reached parity with TensorFlow. (#7926, #8188, #8120, #8101, #8106, #8104, #8082, #7953, #7984, #7836, #7597, #7797)
- 👌 Improved callbacks API. (#6972)
- Enable Ray distributed reference counting. (#8037)
- Work towards customizable distributed training workflows. (#7958, #8077)
Tune
- 📚 Documentation has improved with a new format. (#8083, #8201, #7716)
- 🔨 Search algorithms are refactored to make them easier to extend, deprecating
max_concurrent argument. (#7037, #8258, #8285)
- TensorboardX errors are now handled safely. (#8174)
- 🐛 Bug fix in PBT checkpointing. (#7794)
- 🆕 New ZOOpt search algorithm added. (#7960)
Serve
- 👌 Improved APIs.
- Add delete_endpoint and delete_backend. (#8252, #8256)
- Use dictionary to update backend config. (#8202)
- ➕ Added overview section to the documentation.
- ➕ Added tutorials for serving models in Tensorflow/Keras, PyTorch, and Scikit-Learn.
- Made serve clusters tolerant to process failures. (#8116, #8008,#7970,#7936)
SGD
- 🆕 New Semantic Segmentation and HuggingFace GLUE Fine-tuning Examples. (#7792, #7825)
- 🛠 Fix GPU Reservations in SLURM usage. (#8157)
- ⚡️ Update learning rate scheduler stepping parameter. (#8107)
- 👉 Make serialization of data creation optional. (#8027)
- Automatic DDP wrapping is now optional. (#7875)
Others Projects
- Progress towards the highly available and fault tolerant control plane. (#8144, #8119, #8145, #7909, #7949, #7771, #7557, #7675)
- Progress towards the Ray streaming library. (#8044, #7827, #7955, #7961, #7348)
- Autoscaler improvement. (#8178, #8168, #7986, #7844, #7717)
- 👍 Progress towards Java support. (#8014)
- Progress towards the Window compatibility. (#8237, #8186)
- 👍 Progress towards cross language support. (#7711)
Thanks
🚀 We thank the following contributors for their work on this release:
@simon-mo, @robertnishihara, @BalaBalaYi, @ericl, @kfstorm, @tirkarthi, @nflu, @ffbin, @chaokunyang, @ijrsvt, @pcmoritz, @mehrdadn, @sven1977, @iamhatesz, @nmatthews-asapp, @mitchellstern, @edoakes, @anabranch, @billowkiller, @eisber, @ujvl, @allenyin55, @yncxcw, @deanwampler, @DavidMChan, @ConeyLiu, @micafan, @rkooo567, @datayjz, @wizardfishball, @sumanthratna, @ashione, @marload, @stephanie-wang, @richardliaw, @jovany-wang, @MissiontoMars, @aannadi, @fyrestone, @JarnoRFB, @wumuzi520, @roireshef, @acxz, @gramhagen, @Servon-Lee, @ClarkZinzow, @mfitton, @maximsmol, @janblumenkamp, @istoica