TorchRL - 高度模块化、可扩展的强化学习实验框架

TorchRL提供高度模块化和可扩展的方法来试验强化学习。 它允许基于注册表的方法来运行实验，允许轻松检查点和更新超参数集。 所有这些都可以通过编程接口和友好的CLI访问。

Python 机器学习

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详细介绍

TorchRL

https://travis-ci.org/activatedgeek/torchrl.svg?branch=master
Docs: https://torchrl.sanyamkapoor.com Github: https://github.com/activatedgeek/torchrl

TorchRL provides highly modular and extensible approach to experimenting with Reinforcement Learning. It allows for a registry based approach to running experiments, allows easy checkpointing, and updating hyper parameter sets. All this is accessible via a programmatic interface as well as a friendly CLI.

Objectives

  • Modularity in the RL pipeline
  • Clean implementations of fundamental ideas
  • Fast Experimentation
  • Scalability
  • Low bar and High ceiling

Install

pip install torchrl

Install from source for the latest changes that have not been published to PyPI.

pip install https://github.com/activatedgeek/torchrl/tarball/master

This installs the torchrl package and the torchrl CLI.

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