python-ray 2.38.0
Propagated dependencies: python-aiohttp@3.8.4 python-aiosignal@1.3.1 python-click@8.1.7 python-colorama@0.4.4 python-dm-tree@0.1.8 python-fastapi@0.92.0 python-filelock@3.16.1 python-frozenlist@1.2.0 python-fsspec@2024.10.0 python-grpcio@1.47.0 python-gymnasium@0.29.1 python-jsonschema@4.23.0 python-lz4@4.3.2 python-msgpack@1.0.4 python-numpy@1.24.4 python-packaging@24.2 python-pandas@2.2.3 python-prometheus-client@0.20.0 python-protobuf@3.20.2 python-psutil@5.9.2 python-pyarrow@17.0.0 python-pydantic@1.10.19 python-pyyaml@6.0.1 python-requests@2.31.0 python-rich@13.7.1 python-scikit-image@0.23.2 python-scipy@1.12.0 python-setproctitle@1.3.2 python-smart-open@6.0.0 python-typer@0.6.1 python-virtualenv@20.3.1
Channel: guix-science
Home page: https://github.com/ray-project/ray
Licenses: ASL 2.0
Synopsis: Framework for scaling machine learning applications
Description:
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute. These are the provided Ray AI libraries:
Data: Scalable datasets for ML;
Train: Distributed training;
Tune: Scalable hyperparameter tuning;
RLlib: Scalable reinforcement learning;
Serve: Scalable and programmable serving.
Total results: 2