Installation

💽 Installing SLM Lab

Clone the repository:

git clone https://github.com/kengz/SLM-Lab.git

Install the dependencies:

cd SLM-Lab/
./bin/setup

This runs a prepared bash script with the necessary setup steps, with Python dependencies managed through Conda. Refer to the Help page if you encounter issues.

Readers of the book📖Foundations of Deep Reinforcement Learning: please see this custom instruction page.

Alternative Installations

Windows

The best way to run SLM Lab on Windows is to use a Bash shell/Linux subsystem. Credit to @vladimirnitu and @steindaian for providing a detailed instruction PDF for doing so on Windows:

190KB

SLM_for_Windows.pdf

PDF

Open

SLM Lab for Windows (Instruction PDF)

Google Colab/Jupyter Notebook

Although we do not recommend running SLM Lab on Google Colab or Jupyter notebooks (notebooks come with inherent limitations, e.g. no rendering/multi-processing), we have prepared an example notebook for illustration. Credit to @piosif97 for helping with this:

SLM Lab Colab notebook

For details on how it works, refer to this Help section.

🖥️ Hardware Requirements

Non-image based environments can run on a laptop. Only image based environments such as the Atari games benefit from a GPU speedup. For these, we recommend 1 GPU and at least 4 CPUs. This can run a single Atari Trial consisting of 4 Sessions.

For desktop, a reference spec is GTX 1080 GPU, 4 CPUs above 3.0 GHz, and 32 GB RAM.

For cloud computing, start with an affordable instance of AWS EC2 p2.xlarge with a K80 GPU and 4 CPUs. Use the Deep Learning AMI with Conda when creating an instance.