43 lines
1.4 KiB
Markdown
43 lines
1.4 KiB
Markdown
# dreamerv3-torch
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Pytorch implementation of [Mastering Diverse Domains through World Models](https://arxiv.org/abs/2301.04104v1).
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## Instructions
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Get dependencies:
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```
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pip install -r requirements.txt
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```
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Train the agent on Walker Walk in Vision DMC:
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```
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python3 dreamer.py --configs defaults --task dmc_walker_walk --logdir ~/dreamerv3-torch/logdir/dmc_walker_walk
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```
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Train the agent on Alien in Atari 100K:
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```
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python3 dreamer.py --configs defaults atari --task atari_alien --logdir ~/dreamerv3-torch/logdir/atari_alien
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```
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Monitor results:
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```
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tensorboard --logdir ~/dreamerv3-torch/logdir
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```
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## ToDo
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- [x] Prototyping
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- [x] Modify implementation details based on the author's implementation
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- [x] Evaluate on DMC vision
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- [ ] Evaluate on Atari 100K
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- [ ] Add state input capability
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- [ ] Evaluate on DMC Proprio
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- [ ] etc.
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## Acknowledgments
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This code is heavily inspired by the following works:
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- danijar's Dreamer-v3 jax implementation: https://github.com/danijar/dreamerv3
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- danijar's Dreamer-v2 tensorflow implementation: https://github.com/danijar/dreamerv2
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- jsikyoon's Dreamer-v2 pytorch implementation: https://github.com/jsikyoon/dreamer-torch
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- RajGhugare19's Dreamer-v2 pytorch implementation: https://github.com/RajGhugare19/dreamerv2
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- denisyarats's DrQ-v2 original implementation: https://github.com/facebookresearch/drqv2
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