System Requirements

To run the training procedure and log an experiment you will need to have a Weights & Biases access token. Once you have one, place it under ~/.wandb_secret or manually provide it to the build script by editing the WANDB_SECRET docker argument (TODO: pass it as a parameter).

Since the whole procedure is executed inside a docker, you will have to install it on your machine.

If you plan on training the model on a GPU, you will also have to install the Nvidia Container Toolkit to enable GPU passthrough (this will only work with Nvidia gpus, there is currently no plan on supporting other type of accelerators).

Usage

For starters, you will need to edit src/napoleonzero-torch.py and provide your own project_name and entity parameters to the WandbCallbackobject that is passed to the TrainingLoop. This will allow you to log the experiment on your own Weights & Biases project.

Further modifications might involve hyperparameters and dataset selection.

You can then build and run the docker container to start the experiment:

./build.sh

and

./run.sh

By default the run script tries to use any Nvidia gpu available. If you have none, please don't bother running it (TODO: will work on this).

Note that any modification to the code require you to build the container before running it again.