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
1 maintainer
Release files for flyteplugins-pytorch 2.6.11
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| flyteplugins_pytorch-2.6.11-py3-none-any.whl | Python 3 | none | any | Details |
Release files / flyteplugins_pytorch-2.6.11-py3-none-any.whl
| Download URL | flyteplugins_pytorch-2.6.11-py3-none-any.whl |
|---|---|
| Size | 8.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
99b7cf9405a1753572f3ff1acdfffb01ccc74a27b5446ffdfb17102c1d8882b4
|
|
BLAKE2b-256 checksum How to use checksums |
15f9c736b78b5c54f718f9f63a7d3652edb2b4e8eb4c43431563336ef950b42a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.15
|
