openKylin onnx package

onnx 1.16.2-ok1 source package in openKylin

Changelog

onnx (1.16.2-ok1)  nile; urgency=medium

  * Build for openkylin.

 -- openKylinBot <email address hidden>  Thu, 06 Mar 2025 16:30:12 -0400

Upload details

Uploaded by:
openKylinBot
Sponsored by:
liweinan
Uploaded to:
Nile V2.0
Original maintainer:
Openkylin Developers
Architectures:
any all
Section:
science
Urgency:
Medium Urgency

Publishing See full publishing history

Series Pocket Published Component Section
Nile.bedrock release main science

Downloads

File Size SHA-256 Checksum
onnx_1.16.2.orig.tar.gz 11.9 MiB 84fc1c3d6133417f8a13af6643ed50983c91dacde5ffba16cc8bb39b22c2acbb
onnx_1.16.2-ok1.debian.tar.xz 11.1 KiB 54422f5265277f93cd675d99b8d1e7c75d68d11b0615b937498e7a8777ec22ab
onnx_1.16.2-ok1.dsc 2.2 KiB da404951cf844bc5aae507051a40784a62903cec8c2d910af8af4dfe35782c79

Available diffs

View changes file

Binary packages built by this source

libonnx-dev: Open Neural Network Exchange (ONNX) (dev)

 Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem
 that empowers AI developers to choose the right tools as their project evolves.
 ONNX provides an open source format for AI models. It defines an extensible
 computation graph model, as well as definitions of built-in operators and
 standard data types. Initially onnx focuses on the capabilities needed for
 inferencing (evaluation).
 .
 Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are
 developing ONNX support. Enabling interoperability between different frameworks
 and streamlining the path from research to production will increase the speed
 of innovation in the AI community.
 .
 This package contains the development files.

libonnx-testdata: Open Neural Network Exchange (ONNX) (test data)

 Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem
 that empowers AI developers to choose the right tools as their project evolves.
 ONNX provides an open source format for AI models. It defines an extensible
 computation graph model, as well as definitions of built-in operators and
 standard data types. Initially onnx focuses on the capabilities needed for
 inferencing (evaluation).
 .
 Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are
 developing ONNX support. Enabling interoperability between different frameworks
 and streamlining the path from research to production will increase the speed
 of innovation in the AI community.
 .
 This package contains the test data.

libonnx1t64: Open Neural Network Exchange (ONNX) (libs)

 Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem
 that empowers AI developers to choose the right tools as their project evolves.
 ONNX provides an open source format for AI models. It defines an extensible
 computation graph model, as well as definitions of built-in operators and
 standard data types. Initially onnx focuses on the capabilities needed for
 inferencing (evaluation).
 .
 Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are
 developing ONNX support. Enabling interoperability between different frameworks
 and streamlining the path from research to production will increase the speed
 of innovation in the AI community.
 .
 This package contains the shared objects.

python3-onnx: Open Neural Network Exchange (ONNX) (Python)

 Open Neural Network Exchange (ONNX) is the first step toward an open ecosystem
 that empowers AI developers to choose the right tools as their project evolves.
 ONNX provides an open source format for AI models. It defines an extensible
 computation graph model, as well as definitions of built-in operators and
 standard data types. Initially onnx focuses on the capabilities needed for
 inferencing (evaluation).
 .
 Caffe2, PyTorch, Microsoft Cognitive Toolkit, Apache MXNet and other tools are
 developing ONNX support. Enabling interoperability between different frameworks
 and streamlining the path from research to production will increase the speed
 of innovation in the AI community.
 .
 This package contains the python interface.