TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.

TorchX currently supports:

• Kubernetes (EKS, GKE, AKS, etc)
• Slurm
• AWS Batch
• Docker
• Local
• Ray (prototype)

Need a scheduler not listed? Let us know!

See the quickstart guide.

• Stable Documentation
• Nightly Documentation

torchx:

• python3 (3.8+)
• PyTorch
• optional: Docker (needed for docker based schedulers)

Certain schedulers may require scheduler specific requirements. See installation for info.

# install torchx sdk and CLI -- minimum dependencies
pip install torchx

# install torchx sdk and CLI -- all dependencies
pip install "torchx[dev]"

# install torchx kubeflow pipelines (kfp) support
pip install "torchx[kfp]"

# install torchx Kubernetes / Volcano support
pip install "torchx[kubernetes]"

# install torchx Ray support
pip install "torchx[ray]"

# install torchx sdk and CLI
pip install torchx-nightly[dev]

# install torchx sdk and CLI from source
$ pip install -e git+https://github.com/pytorch/torchx.git#egg=torchx

# install extra dependencies
$ pip install -e git+https://github.com/pytorch/torchx.git#egg=torchx[dev]

TorchX provides a docker container for using as as part of a TorchX role.

See: https://github.com/pytorch/torchx/pkgs/container/torchx

We welcome PRs! See the CONTRIBUTING file.

TorchX is BSD licensed, as found in the LICENSE file.