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.

Key Updates

Added new operators: ImageDecoder #5294 RegexFullMatch #5401 StringConcat #5350 StringSplit #5371 AffineGrid #5225 Gelu #5277
Updated existing operators: ConstantOfShape #5390 GridSample #5010 ReduceMax #5539 ReduceMin #5539 IsNan #5583 IsInf #5583 DFT #5514 LabelEncoder #5453
New features, bug fixes, and document updates

ai.onnx opset version increased to 20 with following changes:

New Operators (ai.onnx):
- ImageDecoder a new ImageDecoder operator to be used in preprocessing models
- RegexFullMatch a new operator for regex matching that is commonly used in feature preprocessing
- StringConcat takes two string tensors as input and returns the elementwise concatenation of the strings in each tensor
- StringSplit takes a string tensor as input and splits each element based on a delimiter attribute and a maxsplit attribute
- AffineGrid Generates a 2D or 3D flow field (sampling grid), given a batch of affine matrices theta
- Gelu applies gaussian error linear unit function or its approximation to input
Operator Updates (ai.onnx):
- ConstantOfShape extends supported data types
- GridSample extends to ND data
- ReduceMax adds support for boolean
- ReduceMin adds support for boolean
- IsNan adds support of float8 types
- IsInf adds support of float8 types
- DFT promote axis as input

ai.onnx.ml opset version increased to 4 with following changes:

Operator Updates (ai.onnx.ml):
- LabelEncoder adds keys_as_tensor and values_as_tensor attributes

New functionality:

Enable empty list of values as attribute PR#5559
Update diff bakend node tests for auto update doc PR#5604
Enable pylint checks with Ruff and remove pylint from lintrunner PR#5589
Getting onnx to treat inf/-inf as float literals. PR#5528
Create the onnxtxt serialization format PR#5524
Support JSON as a serialization target PR#5523
Support for parsing and printing empty list value as attribute PR#5516
Add auto update doc pipeline to help developers update docs PR#5450
Implement GELU as function op PR#5277
Integrate function-inlining with version-conversion PR#5211
Extend function type inference to handle missing optional parameters PR#5169
Create repr functions for OpSchema PR#5117
Utility to inline model-local functions PR#5105
Faster reference implementation for operator Conv based on im2col PR#5069
Support textproto as a serialization format PR#5112

ONNX now supports serializing to JSON, Text Proto as well as the ONNX Text Representation

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.

Shape inference enhancements

[Spec] output_shape for ConvTranspose should not have batch and channels PR#5400
Infer rank where reshape shape is inferred PR#5327

Bug fixes and infrastructure improvements

Do not use LFS64 on non-glibc linu PR#5669
[Web] Use tensor_dtype_to_np_dtype instead of deprecated function PR#5593
Reject absolute path when saving external data PR#5566
Support Python editable builds PR#5558
Test onnxruntime 1.15 with opset 19/IR 9 and fix test source distribution PR#5376
Supports float 8 initializers in ReferenceEvaluator PR#5295
Fix check_tensor to work with large models on UNIX PR#5286
Fix check_tensor to work with large models on Windows PR#5227
Transpose scalar shape inference PR#5204
Enable RUFF as a formatter PR#5176
correct averagepool kernel shape in dilation test case PR#5158
Fix type constraints of Reshape(19) PR#5146
Add github action to check urls are valid PR#5434 Y
Introduce optional cpplint in CI PR#5396 Y
Test the serialization API with custom serializers PR#5315 Y
[CI] Use ONNX Hub directly in test_model_zoo CI PR#5267 Y
Clean up setup.py in favor of pyproject.toml PR#4879 Y

Documentation updates

Merge the two contributing docs and create instructions for updating an op PR#5584
[Doc] Update README.md regarding Protobuf update and fix typo in Slice-13 spec PR#5435
Generate both onnx and onnx-ml operator docs when ONNX_ML=1 PR#5381
Publish md files under docs/ to the documentation site PR#5312
Update OpSchema docs to include new methods and classes PR#5297
Fix missing examples in documentation for ai.onnx.ml PR#5228
Modify OneHot operator explanation PR#5197
Update CIPipelines.md PR#5157
Extend python API documentation PR#5156
Update sphinx to create markdown pages for operators PR#5137

Installation

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

`python setup.py develop` deprecation

Direct 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 .

Contributors

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 1.15.0 v1.15.0 on Python PyPI