openstarlab rlearn modeliing package
Project description
OpenSTARLab Rlearn Modeling package
Introduction
The OpenSTARLab RLearn package is the fundamental package for Reinforcement Learning modeling. It is designed to provide a simple and efficient way to train, inference, and simulate Reinforcement Learning. This package supports the data preprocessed by the OpenSTARLab PreProcessing package.
This package is continuously evolving to support future OpenSTARLab projects. If you have any suggestions or encounter any bugs, please feel free to open an issue.
Installation
- Install pytorch (recommended version 2.4.0 linux pip python3.10 cuda12.6)
pip install torch
- To install this package via PyPI
pip install openstarlab-rlearn
- To install manually
git clone git@github.com:open-starlab/RLearn.git
cd ./RLearn
pip install -e .
Current Features
Sports
RoadMap
- Release the package
- Incorporate more functions
Developer
 Kenjiro Ide 💻 |
 Keisuke Fujii 🧑💻 |
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file openstarlab_rlearn-0.1.32.tar.gz.
File metadata
- Download URL: openstarlab_rlearn-0.1.32.tar.gz
- Upload date:
- Size: 62.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b9b05b588a3ad78f720d9e6b541d946c3c541ce5f9615a99b6521b8f601d20d1
|
|
| MD5 |
c7d124a6ac481e2e28b4abb2c66080cd
|
|
| BLAKE2b-256 |
1054df99eae10e35d270b4b43cb34ef821c9d8ff2d5e31cc718c6514f4346700
|
File details
Details for the file openstarlab_rlearn-0.1.32-py3-none-any.whl.
File metadata
- Download URL: openstarlab_rlearn-0.1.32-py3-none-any.whl
- Upload date:
- Size: 84.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7122f69e454a92fd0f2b06ad620edb9ad78b208de92fa5e41661f1f5568d61b4
|
|
| MD5 |
ca4133dd42c9b289059f848ca70ae365
|
|
| BLAKE2b-256 |
c794de0b1bb7ab39b99e297917652162c5532d189f9b50733586fd875e701ebf
|
