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@@ -7,3 +7,4 @@ logs/* | |
figs/* | ||
**/*.pyc | ||
**/*.egg-info | ||
*~ |
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@@ -36,8 +36,8 @@ If you are interested in playing with Atari games or other advanced packages in | |
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(4) Clone the code repo and install the requirements. | ||
``` | ||
git clone [email protected]:lilianweng/playground-drl.git | ||
cd playground-drl | ||
git clone [email protected]:lilianweng/deep-reinforcement-learning-gym.git | ||
cd deep-reinforcement-learning-gym | ||
pip install -e . # install the “playground” project. | ||
pip install -r requirements.txt # install required packages. | ||
``` | ||
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@@ -54,7 +54,7 @@ cd playground | |
python learn.py configs/data/reinforce-cartpole-v1.json | ||
``` | ||
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During training, three folders will be created in the root `playground-drl/`: `logs`, `checkpoints` and `figs`. Because the env is wrapped by `gym.wrappers.Monitor`, the gym training log is written into `/tmp/` in the meantime. Feel free to comment that out in `playground.configs.manager.ConfigManager` if you are not a fan of that. | ||
During training, three folders will be created in the root directory: `logs`, `checkpoints` and `figs`. Because the env is wrapped by `gym.wrappers.Monitor`, the gym training log is written into `/tmp/` in the meantime. Feel free to comment that out in `playground.configs.manager.ConfigManager` if you are not a fan of that. | ||
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Meanwhile, you can start the tensorboard, | ||
```bash | ||
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