test sphinx github action

.github/workflows/docs.yml

@@ -0,0 +1,18 @@
+name: Deploy Sphinx documentation to Pages
+
+on:
+  push:
+    branches: [main] # branch to trigger deployment
+
+jobs:
+  pages:
+    runs-on: ubuntu-22.04
+    steps:
+    - id: deployment
+      uses: sphinx-notes/pages@v3
+      with:
+        publish: false
+    - uses: peaceiris/actions-gh-pages@v3
+      with:
+        github_token: ${{ secrets.GITHUB_TOKEN }}
+        publish_dir: ${{ steps.deployment.outputs.artifact }}

docs/index.rst

@@ -1,15 +1,71 @@
 .. gomoku_rl documentation master file, created by
-   sphinx-quickstart on Thu Feb 29 02:06:21 2024.
+   sphinx-quickstart on Thu Feb 29 12:40:14 2024.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
 Welcome to gomoku_rl's documentation!
 =====================================
 
+Introduction
+------------
+
+*gomoku_rl* is an open-sourced project that trains agents to play the game of Gomoku through deep reinforcement learning.
+Previous works often rely on variants of AlphaGo/AlphaZero and inefficiently use GPU resources.
+*gomoku_rl* features GPU-parallelized simulation and leverages recent advancements in **MARL**.
+Starting from random play, a model can achieve human-level performance on a :math:`15\times15` board within hours of training on a 3090.
+
+
+Installation
+------------
+
+Install *gomoku_rl* with the following command:
+
+.. code-block:: bash
+
+   git clone [email protected]:hesic73/gomoku_rl.git
+   cd gomoku_rl
+   conda create -n gomoku_rl python=3.11.5
+   conda activate gomoku_rl
+   pip install -e .
+
+I use python 3.11.5, torch 2.1.0 and **torchrl 0.2.1**. Lower versions of python and torch 1.x should be compatible as well. 
+
+Usage
+-----
+
+*gomoku_rl* uses `hydra` to configure training hyperparameters. You can modify the settings in `cfg/train_InRL.yaml` or override them via the command line:
+
+.. code-block:: bash
+
+   # override default settings in cfg/train_InRL.yaml
+   python scripts/train_InRL.py num_env=1024 device=cuda epochs=3000 wandb.mode=online
+   # or simply:
+   python scripts/train_InRL.py.py
+
+
+The default location for saving checkpoints is `wandb/*/files` or `tempfile.gettempdir()` if `wandb.mode=='disabled'`. Modify the output directory by specifying the `run_dir` parameter.
+
+After training, play Gomoku with your model using the `scripts/demo.py` script:
+
+.. code-block:: bash
+
+   # Install PyQt5
+   pip install PyQt5
+   python scripts/demo.py device=cpu grid_size=56 piece_radius=24 checkpoint=/model/path
+   # default checkpoint (only for board_size=15)
+   python scripts/demo.py
+
+
+Pretrained models for a :math:`15\times15` board are available under  `pretrained_models/15_15/`. Be aware that using the wrong model for the board size will lead to loading errors due to mismatches in AI architectures. In PPO, when `share_network=True`, the actor and the critic could utilize a shared encoding module. At present, a `PPOPolicy` object with a shared encoder cannot load from a checkpoint without sharing.
+
+
+
+
 .. toctree::
    :maxdepth: 2
    :caption: Contents:
 
+   modules
 
 
 Indices and tables