v1.12.0

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.

Key Updates

• Added new operators: SequenceMap, LayerNormalization function operator, DFT, HannWindow, HammingWindow, BlackmanWindow, MelWeightMatrix, STFT
• Updated existing operators: Scan
• Miscellaneous shape inference enhancements.
• Miscellaneous bugfixes and infrastructure improvements.
• Miscellaneous documentation updates.
• Wheel updates
  • Add Python 3.10 and drop Python 3.6 support
  • Now use newer manylinux2014_* instead of manylinux2010_* for Linux environments. Please check the support list here.
  • Drop support for x86 (32-bit) Linux due to low usage

ai.onnx opset version increased to 17 with following changes:

• New operators (ai.onnx):
  - LayerNormalization (#4076)
  - SequenceMap (#3892)
  - Signal Operators: DFT, HannWindow, HammingWindow, BlackmanWindow, MelWeightMatrix, STFT (#3741)
• Operator Updates (ai.onnx):
  - [Scan] Remove unused type constraint I for newer Scan (opset 9+)(#4012)

Shape inference enhancements

• Extend InferShapes to expose result of data propagation (#3879)
• Update shape inference for constant of shape (#4141)
• Catch missing input type in function shape inference (#4123)
• Add shape inference for Expand using symbolic shape input (#3789)
• Fix Expand shape inference: stop rank inference if the shape is symbolic (#4019)

Bug fixes and infrastructure improvements

• Fix a bug in _get_initializer_tensors() (#4118)
• Fix bug of resizeShapeInference for Resize13 (#4140)
• Fix bug in SCE function body (#4038)
• Use correct pytest types in backend (#3990) (#3994)
• Checker should validate the node's inputs/outputs have names when its formal parameter is Variadic (#3979)
• Loose NumPy requirement to grant more flexibility (#4059)
• Fix crash: Skip unused value_info for version_converter (#4079)
• Use %d for integer in version_converter (#4182)
• Extend parser to handle other types (#4136)

Documentation updates

• Add documentation about functions to IR.md (#4180)
• Clarify add new op documentation (#4150)
• Clarify NonZero behavior for scalar input in spec (#4113)
• Update shape inference documentation (#4163)
• Fix a minor typo in operator Gather documentation (#4125)
• Fix typo in CIPipelines.md (#4157)
• Fix typo in slice doc (#4117)
• Fix grammar in documents (#4094)
• Clearer description of Slice (#3908)
• Add OperatorSetId definition in docs (#4039)
• Clean up protocol buffer definitions (#4201)
• Change the wrong words of second layer input (#4044)
• Clarify that op_type is case sensitive (#4096)

Installation

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

Notes

• Beware of the protobuf version gap issue (building onnx with protobuf>=3.12 is not compatible with older protobuf)

Contributors

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