Installation
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Clone the repository:
Install the dependencies:
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 bookFoundations of Deep Reinforcement Learning: please see this custom instruction page.
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:
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:
For details on how it works, refer to this Help section.
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.