Skip to main content

ONNX Converter and Optimization Tools

Project description

Linux Windows
Build Status Build Status

Introduction

The onnxconverter-common package provides common functions and utilities for use in converters from various AI frameworks to ONNX. It also enables the different converters to work together to convert a model from mixed frameworks, like a scikit-learn pipeline embedding a xgboost model.

License

MIT License

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

onnxconverter_common-1.12.2-py2.py3-none-any.whl (83.6 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file onnxconverter_common-1.12.2-py2.py3-none-any.whl.

File metadata

  • Download URL: onnxconverter_common-1.12.2-py2.py3-none-any.whl
  • Upload date:
  • Size: 83.6 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/30.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.62.3 importlib-metadata/4.11.2 keyring/23.2.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.9.7

File hashes

Hashes for onnxconverter_common-1.12.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 29b7caade27aeda1b827232554cec352db8afc6e16c3e3ea8c4264449f9ff3a6
MD5 97d9cb4fc6108bd98375d9604cf3baf2
BLAKE2b-256 c55963a053e30e9f8bdaefbd6628fb71b7c705a76e5ce528599f431078ae84d9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page