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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.

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.

Release files for ml-pipes-torch 0.1.2rc1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ml-pipes-torch 0.1.2rc1
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Built distribution (wheel)

Table of built distributions (wheels) for ml-pipes-torch 0.1.2rc1
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ml_pipes_torch-0.1.2rc1-py3-none-any.whl Python 3 none any Details

Total release size: 32.2 kB

Release files / ml_pipes_torch-0.1.2rc1.tar.gz

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