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Eloi Alonso
2022-10-05 10:56:15 +02:00
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- Our approach casts dynamics learning as a sequence modeling problem, where the autoencoder builds a language of image tokens and the Transformer composes that language over time.
## BibTeX
If you find this code or paper useful, please use the following reference:
@@ -33,7 +32,6 @@ If you find this code or paper useful, please use the following reference:
## Setup
- Clone the repository. If you want to download the [pretrained models](#pretrained-models) (~3.1 GB), install [Git LFS](https://git-lfs.github.com/) before cloning. To prevent Git LFS from downloading models, set `GIT_LFS_SKIP_SMUDGE=1`.
- Install [PyTorch](https://pytorch.org/get-started/locally/) (torch and torchvision). Code developed with torch==1.11.0 and torchvision==0.12.0.
- Install [other dependencies](requirements.txt): `pip install -r requirements.txt`
- Warning: Atari ROMs will be downloaded with the dependencies, which means that you acknowledge that you have the license to use them.
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## Pretrained models
Pretrained models are available in `pretrained_models/`.
Pretrained models are available [here](https://github.com/eloialonso/iris_pretrained_models).
- To start a training run from one of these checkpoints, in the section `initialization` of `config/trainer.yaml`, set `path_to_checkpoint` to the corresponding path, and `load_tokenizer`, `load_world_model`, and `load_actor_critic` to `True`.