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

**Repository Path**: slkyrim/Deep-Reinforcement-Learning-Hands-On-Second-Edition

## Basic Information

- **Project Name**: Deep-Reinforcement-Learning-Hands-On-Second-Edition
- **Description**: 深度强化学习实践(第2版)
fork from: 
https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition
- **Primary Language**: Python
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 1
- **Created**: 2021-07-01
- **Last Updated**: 2023-12-13

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# 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!