Dungeon And Data

Dataset Instructions and Tutorials for Submission to NeurIPS2022 Datasets and Benchmarks Track

License

This data is licensed under the NetHack General Public License - based on the GPL-style BISON license. It is the license used for the game of NetHack, and can be found here.

Accessing the Dataset

The dataset is currently hosted on WeTransfer with open access for all, and will remain there for the duration of the review period. It will eventually move to its own dedicated hosting site, which is in the process of being set up. For the time being, NLD-AA is one file, while NLD-NAO is in 5 parts (4 ttyrec zips + the xlogfiles).

Download Links

NLD-AA (1 file)

nld-aa.zip

NLD_NAO (5 files)

Reconstructing the Dataset

Unzip the files in the standard way, with separate directories for NLD-AA, and NLD-NAO.

$ unzip /path/to/nld-aa.zip 

$ unzip /path/to/nld-xlogfiles.zip -d /path/to/nld-nao
$ unzip /path/to/nld-nao_part1.zip -d /path/to/nld-nao
$ unzip /path/to/nld-nao_part2.zip -d /path/to/nld-nao
$ unzip /path/to/nld-nao_part3.zip -d /path/to/nld-nao
$ unzip /path/to/nld-nao_part4.zip -d /path/to/nld-nao

NB: NLD-AA is already a single directory, so will unzip to one directory already, where as all the NLD-NAO files should be zipped to one directory.

Using the Dataset

The code needed to use the dataset will be distributed in NLE v0.9.0. For now it can be found on the main branch of NLE. You can follow the instructions to install there, or try the below.

# With pip:
pip install git+https://github.com/facebookresearch/nle.git@main

# From source:
git clone --recursive https://github.com/facebookresearch/nle.git
cd nle && pip install -e .

Once this is installed, you simply need to load the nld folders (once) which will create a small local sqlite3 database, and then you can use the dataset.

import nle.dataset as nld

if not nld.db.exists():
    nld.db.create()
    # NB: Different methods are used for data based on NLE and data from NAO.
    nld.add_nledata_directory("/path/to/nld-aa", "nld-aa-v0")
    nld.add_altorg_directory("/path/to/nld-nao", "nld-nao-v0")

dataset = nld.TtyrecDataset("nld-aa-v0", batch_size=128, ...)
for i, mb in enumerate(dataset):
    foo(mb) # etc...

for more instructions on usage see the accompanying tutorial notebook in this repo.

Replicating Experiments

Code with a README.md on how to replicate experiments is available in the experiment_code directory. This code was developed for use on an internal cluster, and will be tidied up and open sourced in NLE upon full release of the dataset.

Troubleshooting

If you are having issues loading the dataset, ensure that the directory structure is as laid out in the docstrings to the add_*_directory functions.

help(nld.add_nledata_directory) # will print docstring

Or if you need to get in touch email dungeons.data.submission@gmail.com

upiterbarg / dungeonsdata-neurips2022