10 Commits

Author SHA1 Message Date
ChenDRAG
c25926dd8f
Formalize variable names (#509)
Co-authored-by: Jiayi Weng <trinkle23897@gmail.com>
2022-01-30 00:53:56 +08:00
n+e
fc251ab0b8
bump to v0.4.3 (#432)
* add makefile
* bump version
* add isort and yapf
* update contributing.md
* update PR template
* spelling check
2021-09-03 05:05:04 +08:00
n+e
09692c84fe
fix numpy>=1.20 typing check (#323)
Change the behavior of to_numpy and to_torch: from now on, dict is automatically converted to Batch and list is automatically converted to np.ndarray (if an error occurs, raise the exception instead of converting each element in the list).
2021-03-30 16:06:03 +08:00
Nico Gürtler
5d13d8a453
Saving and loading replay buffer with HDF5 (#261)
As mentioned in #260, this pull request is about an implementation of saving and loading the replay buffer with HDF5.
2020-12-17 08:58:43 +08:00
n+e
b284ace102
type check in unit test (#200)
Fix #195: Add mypy test in .github/workflows/docs_and_lint.yml.

Also remove the out-of-the-date api
2020-09-13 19:31:50 +08:00
n+e
c91def6cbc
code format and update function signatures (#213)
Cherry-pick from #200 

- update the function signature
- format code-style
- move _compile into separate functions
- fix a bug in to_torch and to_numpy (Batch)
- remove None in action_range

In short, the code-format only contains function-signature style and `'` -> `"`. (pick up from [black](https://github.com/psf/black))
2020-09-12 15:39:01 +08:00
n+e
b86d78766b
fix docs and add docstring check (#210)
- fix broken links and out-of-the-date content
- add pydocstyle and doc8 check
- remove collector.seed and collector.render
2020-09-11 07:55:37 +08:00
Trinkle23897
34f714a677 Numba acceleration (#193)
Training FPS improvement (base commit is 94bfb32):
test_pdqn: 1660 (without numba) -> 1930
discrete/test_ppo: 5100 -> 5170

since nstep has little impact on overall performance, the unit test result is:
GAE: 4.1s -> 0.057s
nstep: 0.3s -> 0.15s (little improvement)

Others:
- fix a bug in ttt set_eps
- keep only sumtree in segment tree implementation
- dirty fix for asyncVenv check_id test
2020-09-02 13:03:32 +08:00
n+e
94bfb32cc1
optimize training procedure and improve code coverage (#189)
1. add policy.eval() in all test scripts' "watch performance"
2. remove dict return support for collector preprocess_fn
3. add `__contains__` and `pop` in batch: `key in batch`, `batch.pop(key, deft)`
4. exact n_episode for a list of n_episode limitation and save fake data in cache_buffer when self.buffer is None (#184)
5. fix tensorboard logging: h-axis stands for env step instead of gradient step; add test results into tensorboard
6. add test_returns (both GAE and nstep)
7. change the type-checking order in batch.py and converter.py in order to meet the most often case first
8. fix shape inconsistency for torch.Tensor in replay buffer
9. remove `**kwargs` in ReplayBuffer
10. remove default value in batch.split() and add merge_last argument (#185)
11. improve nstep efficiency
12. add max_batchsize in onpolicy algorithms
13. potential bugfix for subproc.wait
14. fix RecurrentActorProb
15. improve the code-coverage (from 90% to 95%) and remove the dead code
16. fix some incorrect type annotation

The above improvement also increases the training FPS: on my computer, the previous version is only ~1800 FPS and after that, it can reach ~2050 (faster than v0.2.4.post1).
2020-08-27 12:15:18 +08:00
n+e
140b1c2cab
Improve PER (#159)
- use segment tree to rewrite the previous PrioReplayBuffer code, add the test

- enable all Q-learning algorithms to use PER
2020-08-06 10:26:24 +08:00