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Releases: Quantco/spox

0.12.1 (2024-06-18)

18 Jun 10:53
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Bug fix

  • Unset optional inputs are no longer erroneously prefixed by spox.inline.

Other changes

  • The node-naming algorithm now has constant rather than quadratic time complexity.

0.12.0 (2024-05-16)

16 May 13:06
efbe343
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New feature

  • The spox.build function gained the optional drop_unused_inputs argument.

0.11.0 (2024-04-23)

23 Apr 11:18
0731c0a
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New feature

  • Add opsets ai.onnx version 21 and ai.onnx.ml version 5 (released with ONNX 1.16)

0.10.3 (2024-03-14)

14 Mar 11:24
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0.10.3 (2024-03-14)

Other changes

  • Improved node creation speed by skipping the storing of the traceback
  • :class:spox.Var objects may now be shallow copied. Deep copies are explicitly prohibited.

Bug fix

  • Addresses node adaptation failure when referencing a non-input name from inside a subgraph by aborting opset adaptation.

0.10.2 (2023-02-08)

08 Feb 15:12
0b1d08d
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Other changes

  • Added packaging as an explicit dependency.

0.10.1 (2023-02-07)

07 Feb 12:06
d6c9b85
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Other changes

  • Spox's compatibility with older versions of onnx has been improved.

0.10.0 (2023-02-02)

02 Feb 13:30
8cb7271
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0.10.0 (2023-02-02)

New feature

  • The opsets ai.onnx version 20 and ai.onnx.ml version 4 (ONNX 1.15) are now shipped with Spox.

Other changes

  • The validation of Node attributes has been improved and more consistent exceptions are raised if needed.
  • ONNX node attributes are now computed only once and then cached so that the values are reused for validation and building the model.

0.9.3 (2023-10-23)

23 Oct 14:42
4df8779
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0.9.3 (2023-10-23)

Bug fixes

  • Address missing Value Infos when building singleton model for shape inference.
  • Fix issue where Value Propagation failure prevents model creation/inlining.

0.9.2 (2023-10-20)

20 Oct 19:10
701e8ba
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Other changes

  • Fix a deprecation warning from one of Spox's dependencies.

0.9.1 (2023-10-05)

05 Oct 16:10
f4aef40
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Bug fixes

  • The node-adaption no longer fails if faced with a node that has repeating inputs.
  • Forego version adaption of inlined models if no nodes are from the default domain.