Deep-Reinforcement-Learning-Hands-On-Second-Edition

Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt

Code branches

The repository is maintained to keep dependency versions up-to-date. This requires efforts and time to test all the examples on new versions, so, be patient.

The logic is following: there are several branches of the code, corresponding to major pytorch version code was tested. Due to incompatibilities in pytorch and other components, code in the printed book might differ from the code in the repo.

At the moment, there are the following branches available:

• master: contains the code with the latest pytorch which was tested. At the moment, it is pytorch 1.7.
• torch-1.3-book: code printed in the book with minor bug fixes. Uses pytorch=1.3 which is available only on conda repos.
• torch-1.7: pytorch 1.7. This branch was tested and merged into master.

All the branches uses python 3.7, more recent versions weren't tested.

Dependencies installation

Anaconda is recommended for virtual environment creation. Once installed, the following steps will install everything needed:

• change directory to book repository dir: cd Deep-Reinforcement-Learning-Hands-On-Second-Edition
• create virtual environment with conda create -n rlbook python=3.7
• activate it: conda activate rlbook
• install pytorch (update CUDA version according to your CUDA): conda install pytorch==1.7 torchvision torchaudio cudatoolkit=10.2 -c pytorch
• install rest of dependencies: pip install requirements.txt

Now you're ready to launch and experiment with examples!