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
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file flyteplugins_pytorch-2.6.4-py3-none-any.whl.
File metadata
- Download URL: flyteplugins_pytorch-2.6.4-py3-none-any.whl
- Upload date:
- Size: 8.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.13.15
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f86e2ab80f0322ba9edbfd74d6491ff52e902e6311fa3e031a7ec454becf1c7b
|
|
| MD5 |
bf9194c70bab402cf8a4a202cf1a9208
|
|
| BLAKE2b-256 |
addc74f81a7a65d206ea8a3edea0086305b4f793d9f4e7bd0359095e9dde272b
|
