Skip to main content

pytorch plugin for flyte

Project description

Union PyTorch Plugin

Union can execute PyTorch distributed training jobs natively on a Kubernetes Cluster, which manages the lifecycle of worker pods, rendezvous coordination, spin-up, and tear down. It leverages the open-sourced TorchElastic (torch.distributed.elastic) launcher and the Kubeflow PyTorch Operator, enabling fault-tolerant and elastic training across multiple nodes.

This is like running a transient PyTorch cluster — worker groups are created for the specific job and torn down automatically after completion. Elastic training allows nodes to scale in and out, and failed workers can be restarted without bringing down the entire job.

To install the plugin, run the following command:

pip install --pre flyteplugins-pytorch

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

flyteplugins_pytorch-2.5.1-py3-none-any.whl (8.5 kB view details)

Uploaded Python 3

File details

Details for the file flyteplugins_pytorch-2.5.1-py3-none-any.whl.

File metadata

File hashes

Hashes for flyteplugins_pytorch-2.5.1-py3-none-any.whl
Algorithm Hash digest
SHA256 9f44474539abb0956ce587f8a7348cfdb4ff2f2f0cfe65ed1f4dd6de537d1e1b
MD5 3e452fd916e574a2e091d415ee18ce32
BLAKE2b-256 f6543b8078bdc361572e70f17411b620fe52a0332254b2f82bce31a65145beec

See more details on using hashes here.

Supported by

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