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moabitcoin / cherry-pytorch

Reinforcement Learning Tutorials & other bedtime stories in PyTorch
MIT License
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Major code restructure #33

Closed sandhawalia closed 4 years ago

sandhawalia commented 4 years ago

Currently the codebase is organised as follows 

├── ddqn
│   ├── atari
│   └── doom
├── dqn
│   ├── atari
│   └── doom
├── policy_gradients
│   ├── atari
│   ├── classic_control
│   └── doom
├── q-learning
└── utils

Rather than running via an entry scripts as we do currently. We'd like a cli : bin/cherry We'd to like to re-organise as follow 

├── agents
│   ├── dqn
│   └── ddqn
│   ├── q_learning
│   └── policy_gradient
├── envs
│   ├── atari
│   └── doom
│   └── classic_control
├── configs
│   ├── doom.yaml
│   └── atari.yaml
├── utils
└── bin/cherry

And run as follows

bin/cherry train -cfg configs/doom.yaml
bin/cherry play -cfg configs/doom.yaml