Releases: microsoft/maro
Releases · microsoft/maro
maro-0.3.2a4 🚀
- Add DDQN
- Add prioritized sampling
- Improve explore strategy
- Fix minor issues
maro-0.3.2a3 🚀
maro-0.3.2a1 🚀
- Refine RL workflow
- Add
**kwargs
to support more problem setting (e.g., Graph based ones) (#589)- add
**kwargs
to RL models'forward
funcs and_shape_check()
- add
**kwargs
to RL policies'get_action
related funcs and_post_check()
- add
**kwargs
tochoose_actions
ofAbsEnvSampler
; remain it None in currentsample()
andeval()
- add
- Add detached loss to the return value of
update_critic()
andupdate_actor()
of currentTrainOps
; add defaultFalse
early_stop
toupdate_actor()
of currentTrainOps
(#589) - Refine random seed setting logic in RL workflow (#584)
- Refine rollout workflow (#577) to support:
- Run a specific number of steps in rollout
- Run a specific number of episodes during evaluation with
num_eval_episodes
- Flexible metrics management during rollout with
AbsEnvSampler.metrics
- Add
AbsEnvSampler.metrics
to support flexible metrics management during roullout (#577) - Add
Callback
as a general interface to support customized operations in each phase of the workflow. - Re-organize RL job's output paths. (#577)
- Fix several RL algorithm bugs. (#577, #589)
- Add
- Replace the numpy data type with python common data type in whole project (#571)
- Add RL benchmark on Mujoco as a module to tests/, compared with spinning up benchmark, performance results can be found in tests/rl/performance.md (#575, #577, #583, #584)
- Other minor code refinements
maro-0.3.1a2 🚀
Update build workflow to fix pymaro package failed in manylinux issue
maro-0.3.1a1 🚀
- Refine decision event logic (#559)
- Add
DecisionEventPayload
andActionPayload
as the base class for payloads of decision events & action events. - Add related type check during running.
- Rename related variables under
simulator/
. - Refine the action handling logic. Modify
Env
and related BEs.
- Add
- Refine RL component bundle logic (#549)
- Refine
rl_component_bundle
. Use a more straightforward & easier way to organize. In this new version, we do not need easyrl anymore. - Update related examples.
- Fix bugs in distributed training. Add config YAML file for distributed training in CIM scenario.
- Add
rl_formulation.ipynb
as an example.
- Refine
- Fix CITI BIKE hello world dashboard (#555)
- Update data model doc (#554)
- Update requirements (#552, #553)
maro-0.3.0a1 🚀
maro-0.2.4a1 🚀
maro-0.2.3a4 🚀
maro-0.2.3a3 🚀
Simulator/CIM Scenario:
- Fix the environment reset issue #385, and update the simulator random seed interfaces (#387)
- Fix the "Wrong future stop tick predictions" issue #384 (#386)
RL Toolkit:
Visualization Tool/CIM:
Others:
- update dataclasses requirement to setup
- fix some typo in codes comments and online document
maro-0.2.3a2 🚀
- CIM data container/data loader interface for real data mode updated (#372)
- README for pymaro description updated