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- update to 1.16.0 
  * Update to support int4 and uint4:
    + Cast, CastLike, Constant, ConstantOfShape, Identity, If,
      Loop, Reshape, Scan, Shape, Size
  * Update to support float8e4m3fnuz, float8e5m2, float8e5m2fnuz,
    int4 and uint4:
    +  Flatten, Pad, Squeeze, Transpose, Unsqueeze
  * Support blocked quantization. Support int4, uint4, int16, and uint16:
    + DequantizeLinear, QuantizeLinear,
  * Support bfloat16 and float16 scales. Support float8e4m3fn,
    float8e4m3fnuz, float8e5m2, float8e5m2fnuz quantized tensors:
    + QLinearMatMul,
  * Add stash_type attribute and change input shape of scale and
    bias from (G) to (C) for GroupNormalization
  * ai.onnx.ml Opset 4
  * Addeded new operator TreeEnsemble
  * IR Version 10
    + Added support for UINT4, INT4 types
    + GraphProto, FunctionProto, NodeProto, TensorProto added
      metadata_props field
    + FunctionProto added value_info field
    + FunctionProto and NodeProto added overload field to support
     overloaded functions.
- Security Updates
  * Fix path sanitization bypass leading to arbitrary read
    (CVE-2024-27318)
  * Fix Out of bounds read due to lack of string termination in
    assert (CVE-2024-27319)
- Several Bug fixes and infrastructure improvements
- removed python39 support

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- update to 1.15.0
  * 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
  * New functionality:
    + Enable empty list of values as attribute 
    + Update diff bakend node tests for auto update doc 
    + Enable pylint checks with Ruff and remove pylint from lintrunner 
    + Getting onnx to treat inf/-inf as float literals. 
    + Create the onnxtxt serialization format 
    + Support JSON as a serialization target 
    + Support for parsing and printing empty list value as attribute

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- Update to 1.14.1
  * Bug fixes
    - Fix shape data propagation function to handle missing optional parameters #5219
    - Fix a couple of shape inference issues #5223
    - Extend function type inference to handle missing optional parameters #5169
    - Fix check_tensor to work with large models on Windows #5227
    - Fix check_tensor to work with large models on UNIX #5286
- Changes from 1.14.0
  * Opset 19 is released
  * New operators
    - DeformConv added in #4783
  * Operator extensions
    - Equal - Support for string data type added in #4828
    - AveragePool - New attribute dilations #4790
    - Pad - Added new wrap to the mode attribute to support circular padding #4793
    - Resize - Added half_pixel_symmetric to the coordinate_transformation_mode attribute #4862
  * IR updates (bump to 9)
    - Support attributes with default values: #4911
    - Added 4 new 8-bit floating point data types: #4805
  * Backend tests
    - Replaced real models with light models in backend tests. #4861 #4960
  * Support Protobuf v21
    - Now ONNX supports Protobuf v21: #4956
  * Deprecation notice
    - Python 3.7 support will be deprecated due to EOL in next release: #5191
    - onnx-weekly package will be deprecated in TestPyPI. 
      Please use them from PyPI instead: #4930
    - Properties in FormalParameter will be deprecated in future release.
      Please use newer properties name: #5074
    - Variables from mapping.py will be deprecated and become private implementation details.
      Please use public functions to get corresponding types from helper.py instead: #4554
- Changes from 1.13.1
  * Bug fixes
    - Add missing f-string for DeprecatedWarningDict in mapping.py #4707
    - Fix types deprecated in numpy==1.24 #4721
    - Update URL for real models from ONNX Runtime #4865
    - Fix attribute substitution within subgraphs during function type/shape inference #4792
    - Handle variants of constant op in shape inference #4824
    - Fix parser bug in handling non-tensor types #4863
    - Fix function shape inference bug #4880
  * Announcement
    - Deprecate real model tests from onnx repo in next ONNX release #4885
    - Move onnx-weekly package from TestPyPI to PyPI and stop
      uploading onnx-weekly to TestPyPI after next ONNX release #4930
- Changes from 1.13.0
  * New operators
    - Col2Im added in #3948
    - BitwiseNot added in #4497
    - BitwiseAnd, BitwiseOr and BitwiseXor added in #4496
  * Operator extensions
    - Resize - New attributes: 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
    - Pad - New attribute axes #4190
    - OptionalHasElement - New input types handling #4326
    - OptionalHasElement and OptionalGetElement - Accept tensor and sequence types #4421
    - ScatterElement and ScatterND - Add max and min as supported reduction attributes #4411
    - Split - Add support for uneven tensor splitting and a new num_outputs attribute #4481
    - LpPool - New attributes: ceil_mode and dilations #4534
  * Function updates
    - CenterCropPad added in #4190
    - mish added in #4350
    - GroupNormalization added in #4621
  * 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 
    https://github.com/onnx/onnx/wiki/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
- Add %{?sle15_python_module_pythons}

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- Use older protobuf (protobuf21) to fix build

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baserev update by copy to link target

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- python-six is not required

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- Update to version 1.12.0: https://github.com/onnx/onnx/releases/tag/v1.12.0
- Drop upstream patch:
  * 3734-enable-python310.patch

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- Add 3734-enable-python310.patch to make the package Python 3.10
  compatible (gh#onnx/onnx#3734).
- Remove no-python2.patch, it is really better to fix shebang
  with a sed command.

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- Update to 1.10.2: https://github.com/onnx/onnx/releases/tag/v1.10.2
- Rebase no-python2.patch
- Disable python 3.10 support as onnx is not ready yet.
- Do not run tests in parallel, since it is not parallel safe.

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- NEP 29: Tumbleweed does not have python36-numpy and depending
  packages anymore. Skip python36 build.
- Make setup.py cmake call and %cmake macros compatible, even for
  multiple python3 flavors (when we get python39)
- Fix boo#1182258

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- Update to 1.8.1: https://github.com/onnx/onnx/releases/tag/v1.8.1
  * Bug fixes:
    - #3169 To resolve memory crash on Windows, register python exceptions and update exceptions handling
    - #3171 Fix bugs in external data helpers and add add size thresholds for converting
    - #2961 Fix build issues on some distributions of linux due to hard dependency on python2
    - #3221 Fix mypy wrapper error while using ONNX as a submodule
- Changes from skipped 1.8.0: https://github.com/onnx/onnx/releases/tag/v1.8.0
  * Training
    - Added Differentiable tags to make Gradient operator better defined #2723, #2893, #2911, #2954
    - Removed GraphCall; eliminated need to implement GraphCall #2964
    - Created a tool and example for users to use TrainingInfoProto for training #3008
  * Shape Inference and Checker
    - Large model (>2GB model) support added for checker and shape_inference #2744
    - Graph level shape inference fixes to patch the IR gap introduced since IR version 4 #3023
    - Node level shape inference fixes for operators
  * Version Converter
    - More operators supported #2664
  * General Features
    - Added serialization for inputs and outputs of Sequence and Map data types #2581
    - Added programmatic access to version-table and extend make-model #2918
    - Added size check to make_tensor #2987
- Drop patch as the related problem has been fixed upstream:
  * using-onnxruntime-proto.patch

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- reorganized package in order to have shared library support.
  Additional  packages are:
  * onnx-devel
  * libonnxifi_dummy
  * libonnx
  * onnx-devel
  As no so versions for the shared libraries are available, there
  is not a explicit dependency for the shared libraries.
  The archive file libonnxifi_loader.a is explicitely allowed in 
  the rpmlintrc as this archive file is consumed by libonnxifi_loader.so
- Added the proto files from onnxruntime so that both packages can 
  use the same shared libraries:
  * added using-onnxruntime-proto.patch

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