v0.5.0

Major release: v0.5.0 is finally here! 🚀

We are proud to finally release our latest version, 0.5.0, after much work done for NeurIPS!
(Will our paper finally get accepted? 🤞)

Changelog

✨ Features

• New documentation released at rl4.co!
• Add SOTA FJSP environment @LTluttmann
• Add Improvement methods and respective environments MDP @yining043
  • N2S
  • DACT
  • NeuOpt
• Ade HetGNN model for the JFSP @LTluttmann
• Add L2D model @LTluttmann
• Add Multi-task VRP (MTVRP) environment
• Add temperature in NARGNN policies @Furffico
• Add multiple batch sizes for different dataset
• Local search support, DeepACO + Local search @hyeok9855
• Add MTPOMO, MVMoE model @RoyalSkye @FeiLiu36
• Supporting the meta learning trainer @jieyibi
• Supporting the improvement training @yining043
• Add graph problems: MCP and FLP @bokveizen
• New PPO versions:
  • Stepwise @LTluttmann
  • Improvement @yining043
• PolyNet support @ahottung
• Different distributions support + MDPOMO @jieyibi
• Add initial support for solvers API from RL4CO (MTVRP): PyVRP, OR-Tools, LKH3 @N-Wouda @leonlan
• Faster data logprobs collection: now we don't need to collect logprobs for unused trajectories, but we gather only logprobs for selected nodes by default, which decreases memory consumption
• Add Codecov to track the tests coverage

⚙️ Refactoring

• [Environment] Supporting generator_params arguments for environments, more modularized and flexible.
• Modularization of the Attention Model decoder’s QKV calculation for more flexibility @LTluttmann
• Refactor the MatNet encoder with the cross attention only needs to be calculated once @LTluttmann

📝 Documentation

• New documentation based on MkDocs
  • Fast search
  • Beautiful (we hope you'll like it!) new homepage
  • New API reference, about section
  • Ad-free website
  • Light/Dark mode
  • New about sections (licensing, citation)
  • ...and more!
• New tutorial on data distributions
• Miscellaneous: fix Colab links @wouterkool

🐛 Bug Fixes

• Fix the DeepACO’s log_heuristic calculation bug to raise the performance. @Furffico @henry-yeh
• Solve memory leakage during the autoregressive decoding @LTluttmann
• Python versioning: remove Python 3.8, compatibility with Python 3.12, and poetry support @ShuN6211
• Compatibility with tensordict>=0.5.0
• Memory leak in OP and PCTSP
• Fix A2C bug: optimize all parameters in module instead of only "policy" by default
• Fix double logging parameters, better logging in Wandb