[Dependency] Bump onnxruntime from 1.3.0 to 1.9.0 in /.setup/pip

[dependabot]

Bumps onnxruntime from 1.3.0 to 1.9.0.

Release notes

Sourced from onnxruntime's releases.

ONNX Runtime v1.9.0

Announcements

• GCC version < 7 is no longer supported
• CMAKE_SYSTEM_PROCESSOR needs be set when cross-compiling on Linux because pytorch cpuinfo was introduced as a dependency for ARM big.LITTLE support. Set it to the value of uname -m output of your target device.

General

• ONNX 1.10 support
  • opset 15
  • ONNX IR 8 (SparseTensor type, model local functionprotos, Optional type not yet fully supported this release)
• Improved documentation of C/C++ APIs
• IBM Power support
• WinML - DLL dependency fix supports learning models on Windows 8.1
• Support for sub-building onnxruntime-extensions and statically linking into onnxruntime binary for custom builds
  • Add --_use_extensions option to run models with custom operators implemented in onnxruntime-extensions

APIs

• Registration of a custom allocator for sharing between multiple sessions. (See RegisterAllocator and UnregisterAllocator APIs in onnxruntime_c_api.h)
• SessionOptionsAppendExecutionProvider_TensorRT API is deprecated; use SessionOptionsAppendExecutionProvider_TensorRT_V2
• New APIs: SessionOptionsAppendExecutionProvider_TensorRT_V2, CreateTensorRTProviderOptions, UpdateTensorRTProviderOptions, GetTensorRTProviderOptionsAsString, ReleaseTensorRTProviderOptions, EnableOrtCustomOps, RegisterAllocator, UnregisterAllocator, IsSparseTensor, CreateSparseTensorAsOrtValue, FillSparseTensorCoo, FillSparseTensorCsr, FillSparseTensorBlockSparse, CreateSparseTensorWithValuesAsOrtValue, UseCooIndices, UseCsrIndices, UseBlockSparseIndices, GetSparseTensorFormat, GetSparseTensorValuesTypeAndShape, GetSparseTensorValues, GetSparseTensorIndicesTypeShape, GetSparseTensorIndices,

Performance and quantization

• Performance improvement on ARM
  • Added S8S8 (signed int8, signed int8) matmul kernel. This avoids extending uin8 to int16 for better performance on ARM64 without dot-product instruction
  • Expanded GEMM udot kernel to 8x8 accumulator
  • Added sgemm and qgemm optimized kernels for ARM64EC
• Operator improvements
  • Improved performance for quantized operators: DynamicQuantizeLSTM, QLinearAvgPool
  • Added new quantized operator QGemm for quantizing Gemm directly
  • Fused HardSigmoid and Conv
• Quantization tool - subgraph support
• Transformers tool improvements
  • Fused Attention for BART encoder and Megatron GPT-2
  • Integrated mixed precision ONNX conversion and parity test for GPT-2
  • Updated graph fusion for embed layer normalization for BERT
  • Improved symbolic shape inference for operators: Attention, EmbedLayerNormalization, Einsum and Reciprocal

Packages

• Official ORT GPU packages (except Python) now include both CUDA and TensorRT Execution Providers.
  • Python packages will be updated next release. Please note that EPs should be explicitly registered to ensure the correct provider is used.
• GPU packages are built with CUDA 11.4 and should be compatible with 11.x on systems with the minimum required driver version. See: CUDA minor version compatibility
• Pypi
  • ORT + DirectML Python packages now available: onnxruntime-directml
  • GPU package can be used on both CPU-only and GPU machines
• Nuget
  • C#: Added support for using netstandard2.0 as a target framework
  • Windows symbol (PDB) files are no longer included in the Nuget package, reducing size of the binary Nuget package by 85%. To download, please see the artifacts below in Github.

Execution Providers

• CUDA EP

... (truncated)

Commits

• 4daa14b Fixes to rel-1.9.0 to compile and pass for AMD ROCm (#9144)
• 66b3c31 Final round cherry-picks to 1.9.0 (#9133)
• b73bc79 Add a pipeline for audio ops (#9102)
• 83dc225 Second round cherry-pick to rel-1.9.0 (#9062)
• f202cf3 First round cherry-pick to rel-1.9.0 (#9019)
• 6fbd0a8 Change cmake_cuda_architectures to double quotes (#8990)
• 5ae4c54 Fix bug for validating GPU packages (#8997)
• a30d9f5 fix windows gpu pipelines that use cuda 10.2 (training, reduced_ops and 10.2 ...
• 4505243 [js/web] WebAssembly profiling (#8932)
• 0193490 ReduceMin - add int64 cuda kernel support for opset12/13 (#8966)
• Additional commits viewable in compare view

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[dependabot]

The following labels could not be found: dependencies.

[codecov-commenter]

Codecov Report

Merging #151 (a30a970) into master (8572427) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master     #151   +/-   ##
=========================================
  Coverage     22.33%   22.33%           
  Complexity     7284     7284           
=========================================
  Files           191      191           
  Lines         23709    23709           
  Branches         31       31           
=========================================
  Hits           5295     5295           
  Misses        18383    18383           
  Partials         31       31           

Flag	Coverage Δ
autograder	16.58% <ø> (ø)
js	51.69% <ø> (ø)
migrator	99.18% <ø> (ø)
php	20.56% <ø> (ø)
python_submitty_utils	71.65% <ø> (ø)

Flags with carried forward coverage won't be shown. Click here to find out more.

[dependabot]

Superseded by #248.