Bump Microsoft.ML.OnnxRuntime from 1.22.1 to 1.23.0 #176
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Updated Microsoft.ML.OnnxRuntime from 1.22.1 to 1.23.0.
Release notes
Sourced from Microsoft.ML.OnnxRuntime's releases.
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
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
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
CPU EP
QNN EP
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