# rlmodule
Flexible reinforcement learning models instantiators library
Function approximators simple, but still strong. RNN - GRU - LSTM / SAC
Now it only supports skrl, but is intended to be library agnostic - in later expansion
try other algos
shared separate model
<!--
# todo
# some envs have by default range on which they work, like pendulum -2, 2, need to propaget that in.
# cnn
# WRITE README tutorial
# Run & fix pre-commit
# annotate cfgs in modules - why doesn't work TYPE_CHECKING
# extensive comments
# Launch new version to pip
# Import new version in Isaac-lab
# lazy linear? what is it ?
# random model run add function back
-->
## How to run
### Install rlmodule from local code
- Make sure you are in base rlmodule dict.
- Start virtual env.
```
python3 -m venv venv
source venv/bin/activate
```
- Install library from local code
```
pip install -e .
```
Note: sometimes installation may fail, if there is a run/ dir present, you may need to remove it (TODO: fix)
```
rm -rf runs
```
### Run chosen example
```
python3 rlmodule/skrl/torch/examples/gymnasium/pendulum_ppo_mlp_separate_model.py
```
Optional: observe run results in Tensorboard
```
tensorboard --logdir=runs/
```
## Update new version to PIP
Change version name in pyproject.toml
```
pip install build twine
```
```
rm -rf runs
python -m build
```
```
twine upload dist/*
```
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