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Bump onnx from 1.3.0 to 1.13.0 #1002

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@dependabot dependabot bot commented on behalf of github Jan 27, 2023

Bumps onnx from 1.3.0 to 1.13.0.

Release notes

Sourced from onnx's releases.

v1.13.0

ONNX v1.13.0 is now available with exciting new features! We would like to thank everyone who contributed to this release! Please visit onnx.ai to learn more about ONNX and associated projects.

New operators

Operator extensions

Function updates

Reference Python runtime

Reference Python runtime dependent on only Python and numpy has been added. #4483

Python 3.11 support

ONNX 1.13.0 supports Python 3.11. #4490

Apple Silicon support

Support for M1/M2 ARM processors has been added. #4642

More

ONNX 1.13.0 also comes with numerous:

  • bugfixes
  • infrastructure improvements
  • CI improvements
  • documentation updates
  • security updates

For full details see Logistics for ONNX Release 1.13.0.

Deprecation notice

  • TENSOR_TYPE_TO_STORAGE_TENSOR_TYPE has been deprecated #4270
  • ONNXIFI: ONNX Interface for Framework Integration has been deprecated #4431

Installation

You can upgrade to the latest release using pip install onnx --upgrade or build from source following the README instructions.

Contributors

Thanks to these individuals for their contributions in this release since last 1.12.0 release: @​AnandKri, @​cbourjau, @​jcwchen, @​gramalingam, @​garymm, @​GaetanLepage, @​ilya-lavrenov, @​jnovikov, @​JackBoosY, @​jbachurski, @​tjich, @​jantonguirao, @​justinchuby, @​natke, @​philass, @​prasanthpul, @​p-wysocki, @​SpaceIm, @​stephenneuendorffer,@​take-cheeze, @​sechkova, @​thiagocrepaldi, @​xadupre, @​mszhanyi, @​yuanyao-nv, @​andife, @​daquexian, @​kylesayrs, @​liqunfu, @​longlee0622, @​HSQ79815, @​williamberman, @​YanBC

... (truncated)

Changelog

Sourced from onnx's changelog.

Operator Changelog

This file is automatically generated from the def files via this script. Do not modify directly and instead edit operator definitions.

For an operator input/output's differentiability, it can be differentiable, non-differentiable, or undefined. If a variable's differentiability is not specified, that variable has undefined differentiability.

ai.onnx (default)

Version 1 of the default ONNX operator set

Abs-1

Absolute takes one input data (Tensor) and produces one output data (Tensor) where the absolute is, y = abs(x), is applied to the tensor elementwise.

Version

This version of the operator has been available since version 1 of the default ONNX operator set.

Attributes

Inputs

Outputs

Type Constraints

... (truncated)

Commits

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Bumps [onnx](https://github.com/onnx/onnx) from 1.3.0 to 1.13.0.
- [Release notes](https://github.com/onnx/onnx/releases)
- [Changelog](https://github.com/onnx/onnx/blob/main/docs/Changelog.md)
- [Commits](onnx/onnx@v1.3.0...v1.13.0)

---
updated-dependencies:
- dependency-name: onnx
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Jan 27, 2023
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