BSD Ports

misc/py-onnx-ir 1.1.0 FreeBSD

In-memory representation for ONNX models

System
FreeBSD
Repository
FreeBSD ports
Maintainer
[email protected]
Port added
Last update
Commit
9299f2bb39
License
APACHE20
Categories
misc, python

Description

ONNX IR is an in-memory representation for ONNX models. It loads a model into a mutable object graph, lets programs inspect and rewrite graphs, initializers and metadata, and serializes the result back to ONNX, without going through protobuf by hand.

It is the representation that the ONNX rewriter and exporter tooling build upon.

Version history 1

  1. 1.1.0 9299f2bb39

Upstream's version as each commit to the port's Makefile set it, or as this site first saw it in the system's packages; the tree's own revisions are not versions here.

Install

Binary package:

pkg install py312-onnx-ir

From the ports tree:

cd /usr/ports/misc/py-onnx-ir/ && make install clean

To depend on this port in another port's Makefile:

RUN_DEPENDS=	py312-onnx-ir>0:misc/py-onnx-ir

Packages

The version each package repository carries. “-” means the repository builds no package of it, “n/a” that there is no such repository.

Repositoryaarch64amd64armv6armv7i386
FreeBSD:14:latest-----
FreeBSD:14:quarterly--n/a--
FreeBSD:15:latest--n/a--
FreeBSD:15:quarterly--n/an/an/a
FreeBSD:16:latest--n/an/an/a
FreeBSD:16:quarterlyn/an/an/an/an/a

Dependency graph

Ports that need it on the left, what it needs to run on the right; at most 8 of each. "Dependencies" below lists them all.

Dependencies

As this port's Makefile names them.

Build 1

Runtime 6

The full lists below include those, and their dependencies in turn.

Build dependencies 16
Run dependencies 28

Configuration

No options to configure.

USES
python
Service scripts
none

Files

distinfo 1
FileSizeSHA256
onnx_ir-1.1.0.tar.gz169010b72176de575d820ec26864d17270d58ef886a7cf64db7649d15fcc3d5ae2a8ee
Master sites 1
  • PYPI

Commit history 1

DateCommitCreditsLog message
9299f2bb39 Jochen Neumeister misc/py-onnx-ir: Add New Port
ONNX IR is an in-memory representation for ONNX models. It loads a model into a mutable object graph, lets programs inspect and rewrite graphs, initializers and metadata, and serializes the result back to ONNX. Sponsored by: Netzkommune GmbH