Open standard for machine learning interoperability
ONNX v1.16.0 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.
stash_type
attribute and change input shape of scale
and bias
from (G) to (C) for GroupNormalization
metadata_props
fieldvalue_info
fieldoverload
field to support overloaded functions.You can upgrade to the latest release using pip install onnx --upgrade
or build from source following the README instructions.
Thanks to these individuals for their contributions in this release since last 1.16.0 release: Aditya Goel, Adrian Lizarraga, Andreas Fehlner, Charles Volzka, Daniel Richard G, Danni, G. Ramalingam, Gal Hubara-Agam, Ilya Lavrenov, Justin Chu, Tabari Alexander, Takeshi Watanabe, WORLD PEACE, Wouter Deconinck, Xavier Dupré, Yuan Yao, dependabot[bot], galagam, jslap-ubi, liqun Fu
ONNX v1.15.0 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.
Added new operators: ImageDecoderhttps://github.com/onnx/onnx/pull/5294 RegexFullMatchhttps://github.com/onnx/onnx/pull/5401 StringConcathttps://github.com/onnx/onnx/issues/5350 StringSplithttps://github.com/onnx/onnx/pull/5371 AffineGridhttps://github.com/onnx/onnx/issues/5225 Geluhttps://github.com/onnx/onnx/issues/5277
Updated existing operators: ConstantOfShapehttps://github.com/onnx/onnx/pull/5390 GridSamplehttps://github.com/onnx/onnx/pull/5010 ReduceMaxhttps://github.com/onnx/onnx/pull/5539 ReduceMinhttps://github.com/onnx/onnx/pull/5539 IsNanhttps://github.com/onnx/onnx/pull/5583 IsInfhttps://github.com/onnx/onnx/pull/5583 DFThttps://github.com/onnx/onnx/pull/5514 LabelEncoderhttps://github.com/onnx/onnx/pull/5453
New features, bug fixes, and document updates
New Operators (ai.onnx):
Operator Updates (ai.onnx):
inf/-inf
as float literals. PR#5528
Users are now able to serialize the model proto to a text format by specifying supported file extensions or supplying the format=
argument in save_model
.
For example
# model: onnx.ModelProto
onnx.save_model(model, "model.json")
will save the model as a json file.
You can upgrade to the latest release using pip install onnx --upgrade
or build from source following the README instructions.
python setup.py develop
deprecationDirect invocation of setup.py
is deprecated following https://setuptools.pypa.io/en/latest/deprecated/commands.html. To build ONNX, users should switch to use
# Editable installation
# Before: python setup.py develop
# Now
pip install -e .
# Build wheel
# Before: python setup.py bdist_wheel
# Now
pip install --upgrade build
python -m build .
Thanks to these individuals for their contributions in this release since last 1.15.0 release: @adityagoel4512 @AlexandreEichenberger @andife @AtanasDimitrovQC @BowenBao @cbourjau @ClifHouck @guoyuhong @gramalingam @ilya-lavrenov @jantonguirao @jbachurski @jcwchen @justinchuby @leso-kn @linkerzhang @liqunfu @prasanthpul @slowlyideal @smk2007 @snnn @take-cheeze @xadupre @yuanyao-nv @zhenhuaw-me
ONNX v1.14.1 is a patch release based on v1.14.1.
shape
data propagation function to handle missing optional parameters #5219ONNX v1.14.0 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.
DeformConv added in https://github.com/onnx/onnx/pull/4783
Equal - Support for string data type added in https://github.com/onnx/onnx/pull/4828
AveragePool - New attribute dilations
https://github.com/onnx/onnx/pull/4790
Pad - Added new wrap
to the mode
attribute to support circular padding https://github.com/onnx/onnx/pull/4793
Resize - Added half_pixel_symmetric
to the coordinate_transformation_mode
attribute https://github.com/onnx/onnx/pull/4862
Replaced real models with light models in backend tests. https://github.com/onnx/onnx/pull/4861 https://github.com/onnx/onnx/pull/4960
Now ONNX supports Protobuf v21: https://github.com/onnx/onnx/pull/4956
You can upgrade to the latest release using pip install onnx --upgrade
or build from source following the README instructions.
Thanks to these individuals for their contributions in this release since last 1.13.0 release: @jcwchen, @andife, @gramalingam, @xadupre, @justinchuby, @liqunfu, @yuanyao-nv, @jbachurski, @p-wysocki, @prasanthpul, @jantonguirao, @take-cheeze, @smk2007, @AlexandreEichenberger, @snnn, @daquexian, @linkerzhang.
ONNX v1.13.1 is a patch release based on 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.
antialias
, axes
and keep_aspect_ratio_policy
, allow for both scales
and sizes
to be provided when one of them is an empty constant #4126, #4388
axes
#4190
max
and min
as supported reduction attributes #4411
num_outputs
attribute #4481
ceil_mode
and dilations
#4534
Reference Python runtime dependent on only Python and numpy has been added. #4483
ONNX 1.13.0 supports Python 3.11. #4490
Support for M1/M2 ARM processors has been added. #4642
ONNX 1.13.0 also comes with numerous:
For full details see Logistics for ONNX Release 1.13.0.
TENSOR_TYPE_TO_STORAGE_TENSOR_TYPE
has been deprecated #4270
You can upgrade to the latest release using pip install onnx --upgrade
or build from source following the README instructions.
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
The list has been acquired with a script written by Aaron Bockover.
ONNX v1.12.0 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.
input
(#4044)You can upgrade to the latest release using pip install onnx --upgrade
or build from source following the README instructions.
Thanks to these individuals for their contributions in this release since last 1.11.0 release. (Contributor list obtained with: https://github.com/onnx/onnx/graphs/contributors?from=2022-02-08&to=2022-05-24&type=c): @jcwchen, @gramalingam, @xuzijian629, @garymm, @diyessi, @liqunfu, @jantonguirao, @daquexian, @fdwr, @andife, @wschin, @xadupre, @xkszltl, @snnn
ONNX v1.11.0 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.
You can upgrade to the latest release using pip install onnx --upgrade
or build from source following the README instructions.
Thanks to these individuals for their contributions in this release since last 1.10.0 release. (Contributor list obtained with: https://github.com/onnx/onnx/graphs/contributors?from=2021-07-30&to=2022-02-08&type=c): @jcwchen, @gramalingam, @garymm, @mhamilton723, @TomWildenhain-Microsoft, @neginraoof, @xuzijian629, @liqunfu, @gwang-msft, @chudegao, @AlexandreEichenberger, @rajeevsrao, @matteosal, @stillmatic, @askhade, @liuyu21, @jantonguirao, @shinh, @kevinch-nv, @shubhambhokare1, @hwangdeyu, @jiafatom, @postrational, @snnn, @jackwish
This release is a patch release based on v1.10.0.
Bug fix: