README.md

---
license: cc0-1.0
---
# Atari-Asterix Dataset

This is a large dataset of **10M video frames** and actions collected from the **Alien** atari environment (Bellemare et al., 2012) in order to train world models.   
The dataset enables reproducible, large-scale experiments in action-conditioned video prediction. It is meant to be used with [Jasmine](https://github.com/p-doom/jasmine), our JAX-based world modeling codebase.

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### Dataset Summary
- **Environment:** Atari Learning Environment  
- **Frames:** 10 million  
- **Resolution:** 84 × 84  
- **Format:** [`ArrayRecord`](https://github.com/google/array_record) (for fast I/O)  
- **Splits:** `train` / `val` / `test`  
- **License:** [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/)  

---

## Usage
This dataset is part of the [Jasmine](https://github.com/p-doom/jasmine) repository release. Frames were collected during Rainbow (Hessel et al. 2017) agent training.
You can find the dataset generation code at https://github.com/p-doom/jasmine/tree/main/data/jasmine_data.

The ArrayRecord format enables efficient dataloading using Grain and is optimized for the [Jasmine dataloader](https://github.com/p-doom/jasmine/blob/main/jasmine/utils/dataloader.py).

You can download the dataset using the `huggingface-cli` tool.

```bash
huggingface-cli download --repo-type dataset p-doom/atari-asterix-dataset --local-dir <data_path>
```

To start a training run using Jasmine, simply pass the `train` and `val` split to the training script. 
```bash
python jasmine/baselines/maskgit/train_tokenizer_vqvae.py \
    --data_dir <data_path>/train \
    --val_data_dir <data_path>/val \
    ...
```
## Citation

If you use our Atari datasets, please cite our work:

```tex
@article{
    mahajan2025jasmine,
    title={Jasmine: A simple, performant and scalable JAX-based world modeling codebase},
    author={Mihir Mahajan and Alfred Nguyen and Franz Srambical and Stefan Bauer},
    journal = {p(doom) blog},
    year={2025},
    url={https://pdoom.org/jasmine.html},
    note = {https://pdoom.org/blog.html}
}