This release is a pre-release and may not be stable for production use.
ml-pipes-torch
ml-pipes-torch brings Torch-backed execution into ml-pipes.
Use this package when a pipeline needs to cross into Torch for model inference, device-aware execution, or postprocess that is worth keeping on the Torch side. In practice, it often sits between NumPy-oriented preparation or postprocess stages so mixed pipelines can move in and out of the Torch domain explicitly. It also mirrors the generic tensor registry helpers that are often worth keeping on-device during Torch-side postprocess, together with Torch-native vision-adjacent registry helpers such as box-format conversion, mask reconstruction, filtering, resizing, and NMS.
Operators can be used as plain callables, but this package is best used inside
an ml-pipes pipeline.
Package Reference
| Field | Value |
|---|---|
| Package | ml-pipes-torch |
| Guide | docs/README.md |
| Reference | docs/INDEX.md |
| Depends on | ml-pipes-core, ml-pipes-tensor |
| Public modules | ml_pipes.torch |
| Content | Torch execution stages; NumPy/Torch boundary crossing; device placement; mirrored Torch-native tensor postprocess |
See docs/PACKAGES.md
for direct package installs, umbrella profiles, and the full package matrix.
1 maintainer
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