- CPU tensorflow:
pip install -e ".[cpu]"
- GPU tensorflow (requires installation of CUDA libraries):
pip install -e ".[gpu]"
- CPU tensorflow:
pip install ".[cpu]"
- GPU tensorflow (requires installation of CUDA libraries):
pip install ".[gpu]"
The general strategy for running OrbtXLearn is to
- (Optional) start
tensorboard --logdir=data/tf_logs
and navigate tohttp://localhost:6006
in your browser - Start this project according to the instructions below
- Wait for it to print out "Ready"
- Start [orbtxlearn-spy][orbtxlearn-spy]: https://github.com/elite-hanksorr/orbtxlearn-spy
- Hit "Play"
Currently the only ways to collect data are to let OrbtXLearn play completely randomly, or by having it play using the current model. In the future, you should be able to collect human input.
python -m orbtxlearn run [--host HOST] [--port PORT] [--no-model | --model] [--restore-model | --no-restore-model]
python -m orbtxlearn train [--restore-model|--no-restore-model] EPOCHS
python -m orbtxlearn run [--host HOST] [--port PORY] --model --restore-model