onnx 1.16.0

Open Neural Network Exchange

08-10-2021 301 words 2 minutes 0 views

Contents

Open Neural Network Exchange (ONNX) is 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, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).

16735 Stars :star:

Stars: 16735, Watchers: 16735, Forks: 3592, Open Issues: 309

The onnx/onnx repo was created 6 years ago and the last code push was 27 minutes ago.
The project is extremely popular with a mindblowing 16735 github stars!

How to Install onnx

You can install onnx using pip

pip install onnx

or add it to a project with poetry

poetry add onnx

Package Details

Author: None
License: Apache License v2.0
Homepage: None
PyPi:: https://pypi.org/project/onnx/
GitHub Repo:: https://github.com/onnx/onnx

Classifiers

No onnx pypi packages just yet.

Errors

A list of common onnx errors.

Code Examples

Here are some onnx code examples and snippets.

GitHub Issues

The onnx package has 309 open issues on GitHub

Checker should validate the Loop outputs have names.
mypy typecheck (mypy version now is 0.760 in main branch) cannot work with Python 3.8 and 3.9
mypy: update to 0.782 and enable it with Python 3.8 and 3.9
More backend tests for Pad operator
Upgrade mypy to latest version
Use Python type annotations rather than comments
Add bfloat16 type to a few ops missing it
Resize-11 scales input should be optional
[proposal] ONNX Model metadata for provenance
[Tracking] Upgrade MacOS to 11.0 from 10.15 in Mac release pipeline
Bugfix extractor misses local functions
Apache Licence template not populated
Add Col2Im operator
MeanVarianceNormalization without division by zero
Refactor shape_inference_test.py and separate shape inference tests with data propagation.

See more issues on GitHub

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