Skip to main content

Flexible reinforcement learning models instantiators library

Project description

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

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/rlmodule/skrl/torch/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/*

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rlmodule-0.1.6.tar.gz (34.4 kB view details)

Uploaded Source

Built Distribution

rlmodule-0.1.6-py3-none-any.whl (51.0 kB view details)

Uploaded Python 3

File details

Details for the file rlmodule-0.1.6.tar.gz.

File metadata

  • Download URL: rlmodule-0.1.6.tar.gz
  • Upload date:
  • Size: 34.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

File hashes

Hashes for rlmodule-0.1.6.tar.gz
Algorithm Hash digest
SHA256 f69a8471efb9bcbbad8aa22bf055b8c0baa39f844f26f593432b91805d46c0dd
MD5 73e68070d42e9000d3c5c7b2c6f3d695
BLAKE2b-256 9d491808c48cd9f0f4a8a4ab06913d5ea79e3cfa08dbc0aba1d3be17745cd72c

See more details on using hashes here.

File details

Details for the file rlmodule-0.1.6-py3-none-any.whl.

File metadata

  • Download URL: rlmodule-0.1.6-py3-none-any.whl
  • Upload date:
  • Size: 51.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.12

File hashes

Hashes for rlmodule-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 12611d8aec3c94b8e6c3e43a645a468a9f5da55b21df5fa0821abf95e112264b
MD5 ebb6ff87b535b668bf3d327de52a1266
BLAKE2b-256 ba958052e5eed13fdb5e057b4ae633e113745603f3e75a37e0ee20fba104503a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page