chore: deps: Bump Microsoft.ML.OnnxRuntime from 1.20.1 to 1.23.2

[dependabot]

Updated Microsoft.ML.OnnxRuntime from 1.20.1 to 1.23.2.

Release notes

Sourced from Microsoft.ML.OnnxRuntime's releases.

1.23.2

1.23.1

What's Changed

• Fix Attention GQA implementation on CPU (#​25966)
• Address edge GetMemInfo edge cases (#​26021)
• Implement new Python APIs (#​25999)
• MemcpyFromHost and MemcpyToHost support for plugin EPs (#​26088)
• [TRT RTX EP] Fix bug for generating the correct subgraph in GetCapability (#​26132)
• add session_id_ to LogEvaluationStart/Stop, LogSessionCreationStart (#​25590)
• [build] fix WebAssembly build on macOS/arm64 (#​25653)
• [CPU] MoE Kernel (#​25958)
• [CPU] Block-wise QMoE kernel for CPU (#​26009)
• [C#] Implement missing APIs (#​26101)
• Regenerate test model with ONNX IR < 12 (#​26149)
• [CPU] Fix compilation errors because of unused variables (#​26147)
• [EP ABI] Check if nodes specified in GetCapability() have already been assigned (#​26156)
• [QNN EP] Add dynamic option to set HTP performance mode (#​26135)

Full Changelog: microsoft/onnxruntime@v1.23.0...v1.23.1

1.23.0

Announcements

• This release introduces Execution Provider (EP) Plugin API, which is a new infrastructure for building plugin-based EPs. (#​24887 , #​25137, #​25124, #​25147, #​25127, #​25159, #​25191, #​2524)

• This release introduces the ability to dynamically download and install execution providers. This feature is exclusively available in the WinML build and requires Windows 11 version 25H2 or later. To leverage this new capability, C/C++/C# users should use the builds distributed through the Windows App SDK, and Python users should install the onnxruntime-winml package(will be published soon). We encourage users who can upgrade to the latest Windows 11 to utilize the WinML build to take advantage of this enhancement.

Upcoming Changes

• The next release will stop providing x86_64 binaries for macOS and iOS operating systems.
• The next release will increase the minimum supported macOS version from 13.4 to 14.0.
• The next release will stop providing python 3.10 wheels.

Execution & Core Optimizations

Shutdown logic on Windows is simplified

Now on Windows some global object will be not destroyed if we detect that the process is being shutting down(#​24891) . It will not cause memory leak as when a process ends all the memory will be returned to the operating system. This change can reduce the chance of having crashes on process exit.

AutoEP/Device Management

Now ONNX Runtime has the ability to automatically discovery computing devices and select the best EPs to download and register. The EP downloading feature currently only works on Windows 11 version 25H2 or later.

Execution Provider (EP) Updates

ROCM EP was removed from the source tree. Users are recommended to use Migraphx or Vitis AI EPs from AMD.
A new EP, Nvidia TensorRT RTX, was added.

Web

EMDSK is upgraded from 4.0.4 to 4.0.8

WebGPU EP

Added WGSL template support.

QNN EP

SDK Update: Added support for QNN SDK 2.37.

KleidiAI

Enhanced performance for SGEMM, IGEMM, and Dynamic Quantized MatMul operations, especially for Conv2D operators on hardware that supports SME2 (Scalable Matrix Extension v2).

Known Problems

• There was a change in build.py that was related to KleidiAI that may cause build failures when doing cross-compiling (#​26175) .

Contributions

Contributors to ONNX Runtime include members across teams at Microsoft, along with our community members:

@​1duo, @​Akupadhye, @​amarin16, @​AndreyOrb, @​ankan-ban, @​ankitm3k, @​anujj, @​aparmp-quic, @​arnej27959, @​bachelor-dou, @​benjamin-hodgson, @​Bonoy0328, @​chenweng-quic, @​chuteng-quic, @​clementperon, @​co63oc, @​daijh, @​damdoo01-arm, @​danyue333, @​fanchenkong1, @​gedoensmax, @​genarks, @​gnedanur, @​Honry, @​huaychou, @​ianfhunter, @​ishwar-raut1, @​jing-bao, @​joeyearsley, @​johnpaultaken, @​jordanozang, @​JulienMaille, @​keshavv27, @​kevinch-nv, @​khoover, @​krahenbuhl, @​kuanyul-quic, @​mauriciocm9, @​mc-nv, @​minfhong-quic, @​mingyueliuh, @​MQ-mengqing, @​NingW101, @​notken12, @​omarhass47, @​peishenyan, @​pkubaj, @​qc-tbhardwa, @​qti-jkilpatrick, @​qti-yuduo, @​quic-ankus, @​quic-ashigarg, @​quic-ashwshan, @​quic-calvnguy, @​quic-hungjuiw, @​quic-tirupath, @​qwu16, @​ranjitshs, @​saurabhkale17, @​schuermans-slx, @​sfatimar, @​stefantalpalaru, @​sunnyshu-intel, @​TedThemistokleous, @​thevishalagarwal, @​toothache, @​umangb-09, @​vatlark, @​VishalX, @​wcy123, @​xhcao, @​xuke537, @​zhaoxul-qti

1.22.2

What's new?

This release adds an optimized CPU/MLAS implementation of DequantizeLinear (8 bit) and introduces the build option client_package_build, which enables default options that are more appropriate for client/on-device workloads (e.g., disable thread spinning by default).

Build System & Packages

• Add –client_package_build option (#​25351) - @​jywu-msft
• Remove the python installation steps from win-qnn-arm64-ci-pipeline.yml (#​25552) - @​snnn

CPU EP

• Add multithreaded/vectorized implementation of DequantizeLinear for int8 and uint8 inputs (SSE2, NEON) (#​24818) - @​adrianlizarraga

QNN EP

• Add support for the Upsample, Einsum, LSTM, and CumSum operators (#​24265, #​24616, #​24646, #​24820) - @​quic-zhaoxul, @​1duo, @​chenweng-quic, @​Akupadhye
• Fuse scale into Softmax (#​24809) - @​qti-yuduo
• Enable DSP queue polling when performance is set to “burst” mode (#​25361) - @​quic-calvnguy
• Update QNN SDK to version 2.36.1 (#​25388) - @​qti-jkilpatrick
• Include the license file from QNN SDK in the Microsoft.ML.OnnxRunitme.QNN NuGet package (#​25158) - @​HectorSVC

1.22.1

What's new?

This release replaces static linking of dxcore.lib with optional runtime loading, lowering the minimum supported version from Windows 10 22H2 (10.0.22621) to 20H1 (10.0.19041). This enables compatibility with Windows Server 2019 (10.0.17763), where dxcore.dll may be absent.

• change dependency from gitlab eigen to github eigen-mirror #​24884 - @​prathikr
• Weaken dxcore dependency #​24845 - @​skottmckay
• [DML] Restore compatibility with Windows Sdk 10.0.17134.0 #​24950 - @​JulienMaille
• Disable VCPKG's binary cache #​24889 - @​snnn

1.22

Announcements

• This release introduces new API's for Model Editor, Auto EP infrastructure, and AOT Compile
• OnnxRuntime GPU packages require CUDA 12.x , packages built for CUDA 11.x are no longer published.
• The min supported Windows version is now 10.0.19041.

GenAI & Advanced Model Features

• Constrained Decoding: Introduced new capabilities for constrained decoding, offering more control over generative AI model outputs.

Execution & Core Optimizations

Core

• Auto EP Selection Infrastructure: Added foundational infrastructure to enable automatic selection of Execution Providers via selection policies, aiming to simplify configuration and optimize performance. (Pull Request #​24430)
• Compile API: Introduced new APIs to support explicit compilation of ONNX models.
  • See: OrtCompileApi Struct Reference (Assuming a similar link structure for future documentation)
  • See: EP Context Design (Assuming a similar link structure for future documentation)
• Model Editor API api's for creating or editing ONNX models
  • See: OrtModelEditorApi

Execution Provider (EP) Updates

CPU EP/MLAS

• KleidiAI Integration: Integrated KleidiAI into ONNX Runtime/MLAS for enhanced performance on Arm architectures.
• MatMulNBits Support: Added support for MatMulNBits, enabling matrix multiplication with weights quantized to 8 bits.
• GroupQueryAttention optimizations and enhancements

OpenVINO EP

• Added support up to OpenVINO 2025.1
• Introduced Intel compiler level optimizations for QDQ models.
• Added support to select Intel devices based on LUID
• Load_config feature improvement to support AUTO, HETERO and MULTI plugin.
• misc bugfixes/optimizations
• For detailed updates, refer to Pull Request #​24394: ONNXRuntime OpenVINO - Release 1.22

QNN EP

• SDK Update: Added support for QNN SDK 2.33.2.
• operator updates/support to Sum, Softmax, Upsample, Expand, ScatterND, Einsum
• QNN EP can be built as shared or static library.
• enable QnnGpu backend
• For detailed updates refer to recent QNN tagged PR's

TensorRT EP

• TensorRT Version: Added support for TensorRT 10.9.
  • Note for onnx-tensorrt open-source parser users: Please check here for specific requirements (Referencing 1.21 link as a placeholder, this should be updated for 1.22).
• New Features:
  • EP option to enable TRT Preview Feature
  • Support to load TensorRT V3 plugin
• Bug Fixes:
  • Resolved an issue related to multithreading scenarios.
    ... (truncated)

1.21.1

What's new?

• Extend CMAKE_CUDA_FLAGS with all Blackwell compute capacity #​23928 - @​yf711
• [ARM CPU] Fix fp16 const initialization on no-fp16 platform #​23978 - @​fajin-corp
• [TensorRT EP] Call cudaSetDevice at compute function for handling multithreading scenario #​24010 - @​chilo-ms
• Fix attention bias broadcast #​24017 - @​tianleiwu
• Deleted the constant SKIP_CUDA_TEST_WITH_DML #​24113 - @​CodingSeaotter
• [QNN EP] ARM64EC python package remove --vcpkg in build #​24174 - @​jywu-msft
• [wasm] remove --vcpkg in wasm build #​24179 - @​fs-eire

1.21.0

Announcements

• No large announcements of note this release! We've made a lot of small refinements to streamline your ONNX Runtime experience.

GenAI & Advanced Model Features

Enhanced Decoding & Pipeline Support

• Added "chat mode" support for CPU, GPU, and WebGPU.
• Provided support for decoder model pipelines.
• Added support for Java API for MultiLoRA.

API & Compatibility Updates

• Chat mode introduced breaking changes in the API (see migration guide).

Bug Fixes for Model Output

• Fixed Phi series garbage output issues with long prompts.
• Resolved gibberish issues with top_k on CPU.

Execution & Core Optimizations

Core Refinements

• Reduced default logger usage for improved efficiency(#​23030).
• Fixed a visibility issue in theadpool (#​23098).

Execution Provider (EP) Updates

General

• Removed TVM EP from the source tree(#​22827).
• Marked NNAPI EP for deprecation (following Google's deprecation of NNAPI).
• Fixed a DLL delay loading issue that impacts WebGPU EP and DirectML EP's usability on Windows (#​23111, #​23227)

TensorRT EP Improvements

• Added support for TensorRT 10.8.
  • onnx-tensorrt open-source parser user: please check here for requirement.
• Assigned DDS ops (NMS, RoiAlign, NonZero) to TensorRT by default.
• Introduced option trt_op_types_to_exclude to exclude specific ops from TensorRT assignment.

CUDA EP Improvements

• Added a python API preload_dlls to coexist with PyTorch.
• Miscellaneous enhancements for Flux model inference.

QNN EP Improvements

• Introduced QNN shared memory support.
• Improved performance for AI Hub models.
• Added support for QAIRT/QNN SDK 2.31.
• Added Python 3.13 package.
• Miscellaneous bug fixes and enhancements.
• QNN EP is now built as a shared library/DLL by default. To retain previous build behavior, use build option --use_qnn static_lib.

DirectML EP Support & Upgrades

• Updated DirectML version from 1.15.2 to 1.15.4(#​22635).

... (truncated)

1.20.2

What's new?

Build System & Packages

• Merge Windows machine pools for Web CI pipeline to reduce maintenance costs (#​23243) - @​snnn
• Update boost URL for React Native CI pipeline (#​23281) - @​jchen351
• Move ORT Training pipeline to GitHub actions and enable CodeQL scan for the source code (#​22543) - @​snnn
• Move Linux GitHub actions to a dedicated machine pool (#​22566) - @​snnn
• Update Apple deployment target to iOS 15.1 and macOS 13.3 (#​23308) - @​snnn
• Deprecate macOS 12 in packaging pipeline (#​23017) - @​mszhanyi
• Remove net8.0-android MAUI target from MAUI test project (#​23607) - @​carzh

CUDA EP

• Fixes use of numeric_limits that causes a compiler error in Visual Studio 2022 v17.12 Preview 5 (#​22738, #​22868) - @​tianleiwu

QNN EP

• Enable offloading graph input quantization and graph output dequantization to CPU by default. Improves inference latency by reducing the amount of I/O data copied between CPU and NPU. (#​23368) - @​adrianlizarraga

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deps: Bump Microsoft.ML.OnnxRuntime from 1.20.1 to 1.23.2

New title:
chore: deps: Bump Microsoft.ML.OnnxRuntime from 1.20.1 to 1.23.2

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