Trainify-proto
Project description
Trainify-proto
本工具是CAV2022中Trainify: A CEGAR-Driven Training and Verification Framework for Safe Deep Reinforcement Learning的原型工具,Trainify-proto在论文代码的基础上进行了重构改进,增强了易用性、可拓展性和通用性,实现了自定义抽象训练流程和自选形式化验证等功能。
安装
-
pypi (完整功能)
pip install Trainify-proto如果想体验最新功能,可以安装测试版本
pip install -i https://test.pypi.org/simple/ Trainify-proto
-
git clone(完整功能)
通过
git clone项目到本地,集成进自己的项目中使用 -
web在线使用(部分功能)
核心模块
abstract 存放抽象相关工具
agents 存放自带agent/policy
core 核心组件
data 训练数据保存
env 存放自带env
evaluate 评估模块
test 测试代码
utils 工具函数
查看训练/验证结果
# 先安装tensorboard
pip install tensorboard
# log_dir替换为需要查看的实验目录
tensorboard --logdir=log_dir
开发内容
-
环境与状态抽象 需要输入的环境信息:
Dim:2 State_var: x1, x2 Range: [0,1] [0,4] dqn or ddpg Env class obj dynamics: x1' = x1 + t *x2^2 x2' = x2+ t* x1 -
训练Policy与Agent
-
验证规则
- AG(safe) AF(taget)
- 返回['safe']的函数
-
统一输出
- 命令行中的统一格式规范的输出
- tensorboard 作为图表形式
发布
切换到publish分支:git checkout publish
打包:python setup.py sdist bdist_wheel
测试版本:python -m twine upload --repository-url https://test.pypi.org/legacy/ dist/*
正式版本:python -m twine upload dist/*
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