build(deps): update onnxruntime requirement from <1.19,>=1.12.0 to >=1.12.0,<1.20 in /requirements

[dependabot]

Updates the requirements on onnxruntime to permit the latest version.

Release notes

Sourced from onnxruntime's releases.

ONNX Runtime v1.19

Announcements

• Note that Java (maven) and training (pypi) packages are delayed from package manager release due to some publishing errors. Feel free to contact @​maanavd if you need release candidates for some workflows ASAP. In the meantime, binaries are attached to this post. This message will be deleted once this ceases to be the case. Thanks for your understanding :)
• Second note that the wrong commit was initially tagged with v1.19.0. The final commit has since been correctly tagged: microsoft/onnxruntime@26250ae. This shouldn't effect much, but sorry for the inconvenience!

Build System & Packages

• Numpy support for 2.x has been added
• Qualcomm SDK has been upgraded to 2.25
• ONNX has been upgraded from 1.16 → 1.16.1
• Default GPU packages use CUDA 12.x and Cudnn 8.x (previously CUDA 11.x/CuDNN 8.x) CUDA 11.x/CuDNN 8.x packages are moved to the aiinfra VS feed.
• TensorRT 10.2 support added
• Introduced Java CUDA 12 packages on Maven.
• Discontinued support for Xamarin. (Xamarin reached EOL on May 1, 2024)
• Discontinued support for macOS 11 and increasing the minimum supported macOS version to 12. (macOS 11 reached EOL in September 2023)
• Discontinued support for iOS 12 and increasing the minimum supported iOS version to 13.

Core

• Implemented DeformConv

Performance

• Added QDQ support for INT4 quantization in CPU and CUDA Execution Providers
• Implemented FlashAttention on CPU to improve performance for GenAI prompt cases
• Improved INT4 performance on CPU (X64, ARM64) and NVIDIA GPUs

Execution Providers

• TensorRT

  • Updated to support TensorRT 10.2
  • Remove calls to deprecated api’s
  • Enable refittable embedded engine when ONNX model provided as byte stream

• CUDA

  • Added support for building with CUDA 12.5.
  • Upgraded cutlass to 3.5.0 for performance improvement of memory efficient attention.
  • Updated MultiHeadAttention and Attention operators to be thread-safe.
  • Added sdpa_kernel provider option to choose kernel for Scaled Dot-Product Attention.
  • Expanded op support - Tile (bf16)

• CPU

  • Expanded op support - GroupQueryAttention, SparseAttention (for Phi-3 small)

• QNN

  • Updated to support QNN SDK 2.25
  • Expanded op support - HardSigmoid, ConvTranspose 3d, Clip (int32 data), Matmul (int4 weights), Conv (int4 weights), prelu (fp16)
  • Expanded fusion support – Conv + Clip/Relu fusion

• OpenVINO

  • Added support for OpenVINO 2024.3
  • Support for enabling EpContext using session options

• DirectML

... (truncated)

Commits

• 26250ae ORT 1.19.0 Release: Cherry-Pick Round 2 (#21726)
• ccf6a28 ORT 1.19.0 Release: Cherry-Pick Round 1 (#21619)
• ee2fe87 ORT 1.19.0 Release: Cherry-Pick Round 0 (#21609)
• 530a2d7 Enable FP16 Clip and Handle Bias in FP16 Depthwise Conv (#21493)
• 82036b0 Remove references to the outdated CUDA EP factory method (#21549)
• 07d3be5 CoreML: Add ML Program Split Op (#21456)
• 5d78b9a [TensorRT EP] Update TRT OSS Parser to 10.2 (#21552)
• 8417c32 Keep QDQ nodes w/ nonpositive scale around MaxPool (#21182)
• d985814 Update labeling bot (#21548)
• 7543dd0 Propagate NaNs in the CPU min and max operators (#21492)
• Additional commits viewable in compare view

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📚 Documentation preview 📚: https://torchmetrics--2692.org.readthedocs.build/en/2692/

[Borda]

@dependabot rebase

[Borda]

this seems to be similar: facebookresearch/svoice#97

[SkafteNicki]

Lets try to bump numpy as it seems to be partial solution

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 69%. Comparing base (0313c6b) to head (7d2201f).
Report is 1 commits behind head on master.

Additional details and impacted files

@@          Coverage Diff           @@
##           master   #2692   +/-   ##
======================================
  Coverage      69%     69%           
======================================
  Files         316     316           
  Lines       17900   17900           
======================================
  Hits        12328   12328           
  Misses       5572    5572           

[SkafteNicki]

So the problem seems to be with the pesq package with complains that it is compiled against numpy<2.0. So currently docs are failing because numpy>=2.0 is being used there.

[Borda]

So the problem seems to be with the pesq package with complains that it is compiled against numpy<2.0. So currently docs are failing because numpy>=2.0 is being used there.

reporting it in ludlows/PESQ#54