Commit 7ec8d594 authored by danielle_rothermel's avatar danielle_rothermel
Browse files

Merge branch 'more_readme_fixes' into 'master'

Update README & Bugfixes

See merge request !12
parents aa867d1c 5e1c8bc1
......@@ -102,7 +102,6 @@ The different files and directories have following meaning:
Finally, **you must specify an AIcrowd submission JSON in `aicrowd.json` to be scored!** See "How do I actually make a submission" below for more details.
**How can I get going with an existing baseline?**
The best current baseline is the torchbeast baseline. Follow the instructions
......@@ -160,64 +159,61 @@ The machine where the submission will run will have following specifications:
1. **Add your SSH key** to AIcrowd GitLab
You can add your SSH Keys to your GitLab account by going to your profile settings [here](https://gitlab.aicrowd.com/profile/keys). If you do not have SSH Keys, you will first need to [generate one](https://docs.gitlab.com/ee/ssh/README.html#generating-a-new-ssh-key-pair).
You can add your SSH Keys to your GitLab account by going to your profile settings [here](https://gitlab.aicrowd.com/profile/keys). If you do not have SSH Keys, you will first need to [generate one](https://docs.gitlab.com/ee/ssh/README.html#generating-a-new-ssh-key-pair).
2. **Clone the repository** - TODO
2. **Clone the repository**
```
git clone git@gitlab.aicrowd.com:nethack/neurips-2021-the-nethack-challenge.git
```
3. **Install** competition specific dependencies!
3. **Verify you have dependencies** for the Nethack Learning Environment
NLE requires `python>=3.5`, `cmake>=3.14` to be installed and available both when building the
package, and at runtime.
On **MacOS**, one can use `Homebrew` as follows:
``` bash
$ brew install cmake
```
pip install -r requirements
On a plain **Ubuntu 18.04** distribution, `cmake` and other dependencies
can be installed by doing:
```bash
# Python and most build deps
$ sudo apt-get install -y build-essential autoconf libtool pkg-config \
python3-dev python3-pip python3-numpy git flex bison libbz2-dev
# recent cmake version
$ wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | sudo apt-key add -
$ sudo apt-add-repository 'deb https://apt.kitware.com/ubuntu/ bionic main'
$ sudo apt-get update && apt-get --allow-unauthenticated install -y \
cmake \
kitware-archive-keyring
```
4. Run rollouts with a random agent with `python test_submission.py`.
### For setting up the Nethack Learning Environment:
NLE requires `python>=3.5`, `cmake>=3.14` to be installed and available both when building the
package, and at runtime.
On **MacOS**, one can use `Homebrew` as follows:
``` bash
$ brew install cmake
```
On a plain **Ubuntu 18.04** distribution, `cmake` and other dependencies
can be installed by doing:
```bash
# Python and most build deps
$ sudo apt-get install -y build-essential autoconf libtool pkg-config \
python3-dev python3-pip python3-numpy git flex bison libbz2-dev
# recent cmake version
$ wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | sudo apt-key add -
$ sudo apt-add-repository 'deb https://apt.kitware.com/ubuntu/ bionic main'
$ sudo apt-get update && apt-get --allow-unauthenticated install -y \
cmake \
kitware-archive-keyring
```
4. **Install** competition specific dependencies!
Afterwards it's a matter of setting up your environment. We advise using a conda
environment for this:
We advise using a conda environment for this:
```bash
# Optional: Create a conda env
$ conda create -n nle_challenge python=3.8
$ conda activate nle_challenge
$ pip install -r requirements.txt
```
```bash
$ conda create -n nle python=3.8
$ conda activate nle
$ pip install nle
```
5. **Run rollouts** with a random agent with `python test_submission.py`.
Find more details on the [original nethack repository](https://github.com/facebookresearch/nle)
Find more details on the [original nethack repository](https://github.com/facebookresearch/nle)
# Baselines
Although we are looking to supply this repository with more baselines throughout the first month of the competition, this repository comes with a strong IMPALA-based baseline in the directory `./nethack_baselines/torchbeast`.
More info on how to install, train and submit that repo are available [here](./nethack_baselines/torchbeast/README.md) - along with some suggestions on where to go next!
Follow the instructions [here](/nethack_baselines/torchbeast/) to install and start training the model (there are even some suggestions for improvements).
# How to Test and Debug Locally
......@@ -454,4 +450,4 @@ To be added
└── verify_or_download_data.py
<p style="text-align:center"><img style="text-align:center" src="https://raw.githubusercontent.com/facebookresearch/nle/master/dat/nle/example_run.gif"></p> -->
\ No newline at end of file
<p style="text-align:center"><img style="text-align:center" src="https://raw.githubusercontent.com/facebookresearch/nle/master/dat/nle/example_run.gif"></p> -->
......@@ -7,7 +7,6 @@
import numpy as np
from agents.batched_agent import BatchedAgent
from submission_config import SubmissionConfig, TestEvaluationConfig
from rollout import run_batched_rollout
......
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