https://github.com/threewisemonkeys-as/torched_impala
Implementation of Distributed RL in pytorch
https://github.com/threewisemonkeys-as/torched_impala
Last synced: 6 months ago
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Implementation of Distributed RL in pytorch
- Host: GitHub
- URL: https://github.com/threewisemonkeys-as/torched_impala
- Owner: threewisemonkeys-as
- Created: 2020-07-01T10:40:44.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-07-09T12:01:21.000Z (almost 5 years ago)
- Last Synced: 2024-11-22T08:53:31.349Z (6 months ago)
- Language: Python
- Size: 9.77 KB
- Stars: 6
- Watchers: 4
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Pytorch IMPALA
A Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures (IMPALA) implemented in pytorch
## Requirements
1. [python 3.7+]()
```bash
$ sudo apt install python3.7
```
2. [pytorch](https://pytorch.org/)
```bash
$ pip install torch
```
3. [tensorboard](https://pytorch.org/docs/stable/tensorboard.html)
```bash
$ pip install tensorboard
```
## Usage
1. Edit hyperparameters in `main.py`
2. Train the model
```bash
$ python train.py
```
3. Logs will be collected in specified folder. You can use `tensorboard` to view them in a browser
```bash
$ tensorboard --logdir ./logs/
```
4. Test the model
```bash
$ python test.py
```
Example
```bash
$ python test.py -pp ./models/IMPALA_RacecarBulletEnv-v0_400.pt -hd 32 -en RacecarBulletEnv-v0 -ne 10 -el 1000 -ld ./logs/
```
## References
1. [IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures by Espeholt, Soyer, Munos et al.] (https://arxiv.org/pdf/1802.01561.pdf)
## TODO
- [X] Fix OSError
- [X] Add batched updates
- [X] Add tensorboard logging
- [X] Test performance
- [ ] Fix performance collapse issues
- [ ] Add comand line argument support