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ac44e16
Make shared WebGPU data transfers stateless (#33208)
mustjab Oct 9, 2026
d7a4f6a
[CPU] Support mixed types and precision in QuantizeLinear (#32735)
TANGBUDU Oct 9, 2026
2297e77
Fix WASM Debug external-data test failures (#33226)
Copilot Oct 9, 2026
8fe86b1
[WebGPU] Reduce QMoE single-token gate sorting to stable TopK (#33058)
sayanshaw24 Oct 9, 2026
a477eff
[CUDA] Fix QMoE SM120 configuration dispatch on SM121 devices (#33225)
kunal-vaishnavi Oct 9, 2026
f289d7a
[WebGPU] Accelerated model loading using Win32 and D3D12 (#33055)
sushraja-msft Oct 9, 2026
e19a9ae
Fix PadFusion changing MaxPool results for negative inputs (#33206)
the0cp Oct 9, 2026
9a6089e
Fix empty CPU reductions with negative axes (#33232)
xadupre Oct 9, 2026
426d9b3
Add FP16 and BF16 H512 GQA decode support (#33176)
hanbitmyths Oct 9, 2026
0066c38
[WebGPU EP] fixes fp16 accumulation bug in gemm kernel (#33057)
prathikr Oct 9, 2026
58bacbc
Fix model package EP setup and stable API contracts (#32790)
xiaoyu-work Oct 9, 2026
e2a99af
Improve INT4 decode and GEMM profiler buffer safety (#33177)
hanbitmyths Oct 9, 2026
29feb3b
[WebGPU] Tile large block-FP8 QMoE expert matmuls (#33075)
sayanshaw24 Oct 9, 2026
11cba20
[CUDA] Single-source remaining GQA preparation scratch sizing (#33118)
chilo-ms Oct 9, 2026
6e0f154
[WebGPU] Restore ORT 1.24.4 compatibility with per-Session recording …
xiaofeihan1 Oct 10, 2026
9073c94
Bump plugin ep versions (#33214)
tianleiwu Oct 10, 2026
bde59f3
[WebGPU] Refactor MatMul algorithm selection (#32630)
qjia7 Oct 10, 2026
bb47315
[WebGPU] Widen MatMulNBits SubgroupMatrix-8x16x16 tiling to 128x256 (…
daijh Oct 10, 2026
3571447
[WebGPU] Prepack ConvTranspose1D/2D initializer weights (#33231)
gyagp Oct 10, 2026
8fc9fd5
[WebGPU] Fix shader cache collisions across operator variants (#33242)
gyagp Oct 10, 2026
86d6073
Remove stale Intel MKL third-party notice (#33233)
xadupre Oct 11, 2026
67c61ae
webgpu: Fix Python factory selection for plugin EP hosts (#33241)
qjia7 Oct 12, 2026
988cc07
Reintegrate ONNX 1.23.2 base plumbing (#33134)
gramalingam Oct 12, 2026
e0940a3
[MLAS] Add support for Transposed B SME/SME2 Half Gemm path (#33130)
patryk-kaiser-ARM Oct 12, 2026
da8e897
Update libprotobuf-mutator to handle protobuf api changes (#33210)
eserscor Oct 12, 2026
9ddcd77
Fix CPU OneHot handling of fractional floating-point indices (#33273)
Mohit-25-tech Oct 12, 2026
115e449
[MLAS + CORE] Improve YOLOX FP32 models performance on CPU (#32335)
swetha097 Oct 12, 2026
63ff13b
Fix WebGPU pipeline callback test shader keys (#33310)
edgchen1 Oct 12, 2026
994f349
[float16] Reuse Cast nodes for shared always-float inputs (#33090)
Copilot Oct 12, 2026
42518d8
[CUDA] Add persistent fpA_intB MatMulNBits tactic autotune cache (#29…
tianleiwu Oct 13, 2026
e2e7a0a
[CUDA] Include SM100 in Linux aarch64 CUDA 13 packages (#33315)
DevChuriwala Oct 13, 2026
6a78e30
[WebGPU] Support fixed subgroup size in im2col_matmul (#33249)
Jiawei-Shao Oct 13, 2026
9036f07
Validate inline sparse payloads before dense allocation (#32863)
danielsongmicrosoft Oct 13, 2026
208463a
[MLAS] Skip FP16 unit tests on CPUs without FP16 arithmetic (#33260)
yairbenavraham Oct 13, 2026
c9f4bb5
Fix Windows float16 model-path conversion (#33193)
aswanth-07 Oct 13, 2026
07daf40
Remove thread-pool parallelism assertion in GQA CPU test (#33342)
n1harika Oct 13, 2026
9c21c82
[WebGPU] Fix Pow scalar operands in vectorized broadcasting (#33348)
gyagp Oct 14, 2026
bbfa896
[WebGPU] Validate MatMul execution plans in planner (#33288)
qjia7 Oct 14, 2026
7c1103e
WebGPU: Fix DequantizeLinear 1-D block_size handling (#32734)
qjia7 Oct 14, 2026
6cbefcc
Add sm_110 (Jetson Thor) to the Linux aarch64 CUDA 13 packaging archi…
LinCanNerd Oct 14, 2026
2db2a3a
[WebGPU] Preserve pending JSEP reads before CPU uploads (#33361)
gyagp Oct 14, 2026
9c87bdf
[WebGPU] Support 16x16x16 subgroup matrix MatMul (#32937)
SharmaRithik Oct 14, 2026
a5e205b
Skip NCHWc conversion for zero-channel Conv (#33346)
rookieLiu2018 Oct 14, 2026
f8f8644
Fix OpenVINO provider info namespace for Python builds (#33327)
mustjab Oct 14, 2026
dc89460
[WebGPU] Handle empty-rank MatMul and DequantizeLinear correctly (#33…
mustjab Oct 14, 2026
d661330
fix: don't infer GQA present length from a non-constant total length …
ykhrustalev Oct 15, 2026
1fd4fa1
[CUDA] fix Nemotron-H relu2, RMSNorm, and activation precision (#33312)
rui-ren Oct 15, 2026
e0f06b1
[WebGPU] Refactor `FlashAttention` into eligibility and execution hel…
daijh Oct 15, 2026
b4aaada
[WebGPU] Capture GPU buffer copies for graph replay (#33362)
xiaofeihan1 Oct 15, 2026
943b501
Add sm_87 for Jetson Orin CUDA 13 packaging (#33369)
alexk201 Oct 15, 2026
9cdf0f1
cuda plugin: add native sm_120 SASS to the LLM target under MSVC (#33…
tianleiwu Oct 15, 2026
122c193
Validate fp16 MatMulNBits prepack inputs (#33375)
apsonawane Oct 15, 2026
0af178c
[ONNX] Support Mod opset 28 (#32369)
justinchuby Oct 15, 2026
fc49223
[CPU] Prevent QLinearSoftmax requantization overflow (#33277)
MokiMeow Oct 15, 2026
648f708
Preserve double constants in graph fusions (#32983)
Yuhx141 Oct 15, 2026
1988019
Make zero-input-channel NCHWc regression graph-only (#33398)
chilo-ms Oct 15, 2026
327d11a
[CUDA] Bound GQA non-windowed workspace via the KV-length envelope (r…
chilo-ms Oct 15, 2026
ca64594
Revert "webgpu: Fix Python factory selection for plugin EP hosts (#33…
qjia7 Oct 16, 2026
5e42959
fix: name the activation the WebGPU Conv kernel cannot fuse (#32716) …
ykhrustalev Oct 16, 2026
2fd0afa
[CUDA] Support offline NVFP4 QMoE weights and fused block-FP8 executi…
kunal-vaishnavi Oct 16, 2026
f33c174
[CUDA][WebGPU] Add PackedSparseAttentionIndexerMerge for MTP index sh…
kunal-vaishnavi Oct 16, 2026
52131d9
[WebGPU] Optimize subgroup matrix MatMulNBits for AMD wave64 (#32796)
gyagp Oct 16, 2026
a8fda2f
Fix d3d12_file_buffer_loader so it can build with no exception and cl…
sushraja-msft Oct 16, 2026
b016c16
[CUDA] Optimize packed QSA scoring and multi-token verification (#33328)
kunal-vaishnavi Oct 16, 2026
ec70cae
[Framework] Honor Level-1 estimates for nodes missing from memory pro…
chilo-ms Oct 16, 2026
529efb6
[docs] Experimental C API usage (#29701)
edgchen1 Oct 16, 2026
0fb935a
Bump github/issue-labeler from 3.4 to 3.5 (#33388)
dependabot[bot] Oct 16, 2026
454b3dd
Fix QLinearSoftmax output for empty inputs (#33401)
DavidLuong98 Oct 16, 2026
0767b73
[WebGPU] Upgrade Dawn to the latest version (#33390)
Jiawei-Shao Oct 16, 2026
e88538c
Zero initialize OrtEpFactory in provider bridge EP factories (#33117)
maxim-davgalev Oct 16, 2026
d8a3445
[WebGPU] Add GatedDeltaNetStateReplay contrib operator (#33213)
aciddelgado Oct 17, 2026
fed1f4b
[CUDA] Load fpA_intB tactic cache on session create and save on close…
tianleiwu Oct 17, 2026
b5375da
[WebGPU] Extend FP16 MatMul GEMV fast path to M=2–8 (#33351)
aciddelgado Oct 17, 2026
c64c9fd
Fix 1DS telemetry deadlock during Windows process termination (#33291)
qjia7 Oct 17, 2026
ce1d73c
[CUDA plugin EP] Improve NuGet package metadata (#33405)
tianleiwu Oct 18, 2026
c1ea5bf
Fix safety guards in training loss fusions (#32987)
Yuhx141 Oct 18, 2026
c43d712
Revert "Fix non-deterministic constant folding output" (#32471)
xiaofeihan1 Oct 19, 2026
81f5efa
[WebGPU] Support block-quantized FP8 dense MatMul (#33074)
sayanshaw24 Oct 19, 2026
0614f48
Fix WebGPU Conv2dMM input indexing for vec3 channels (#33432)
gyagp Oct 19, 2026
9eec7d5
[CUDA] Add opt-in native E4M3 block-scale conversion to NVFP4 GEMV (#…
sayanshaw24 Oct 19, 2026
69eeb2b
[CUDA] Add decode GEMV kernel for K-packed NVFP4 QMoE (#33354)
tianleiwu Oct 19, 2026
dc1ae7a
Skip MatMul BatchNormalization fusion when the channel axis moves (#3…
samridh10exe Oct 19, 2026
bb68f5d
[CUDA] Add opt-in tail-safe INT4 MatMulNBits dispatch for N % 8 == 4,…
tianleiwu Oct 19, 2026
7764273
Add exact normalization and rotary CUDA operator modes
apsonawane Oct 19, 2026
9a662b9
Allow onnxruntime_DISABLE_EXCEPTIONS without onnxruntime_MINIMAL_BUIL…
rvandermeulen Oct 19, 2026
d76d17c
Fix lint
apsonawane Oct 19, 2026
26cb236
Merge main into normalization and rotary stack
apsonawane Oct 19, 2026
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2 changes: 1 addition & 1 deletion .github/workflows/labeler.yml
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ jobs:
]
timeout-minutes: 120
steps:
- uses: github/issue-labeler@c1b0f9f52a63158c4adc09425e858e87b32e9685 # v3.4
- uses: github/issue-labeler@ccca1e16fcb66762200e616fc29b57b940c1cb67 # v3.5
with:
repo-token: "${{ secrets.GITHUB_TOKEN }}"
configuration-path: .github/labeler.yml
Expand Down
21 changes: 19 additions & 2 deletions .github/workflows/linux_ci.yml
Original file line number Diff line number Diff line change
Expand Up @@ -2,10 +2,11 @@
# It leverages a reusable workflow (`reusable_linux_build.yml`) to handle the core build and test logic
# within Docker containers, ensuring a consistent environment.
#
# The workflow consists of five parallel jobs targeting different combinations:
# The workflow consists of parallel jobs targeting different combinations:
# - build-linux-x64-debug: Builds/tests Debug config on Linux x64 (AMD CPU pool), enables AddressSanitizer.
# - build-linux-x64-release: Builds/tests Release config on Linux x64 (AMD CPU pool), includes wheel/nuget/benchmark flags.
# - orttraining-linux-ci-pipeline: Builds/tests Release config with Training enabled (--enable_training) on Linux x64 (AMD CPU pool).
# - build-linux-x64-no-exceptions: Builds MinSizeRel config with exceptions disabled (--disable_exceptions), without unit tests, on Linux x64 (AMD CPU pool).
# - build-linux-arm64-debug: Builds/tests Debug config on Linux arm64 (ARM CPU pool); ASan is disabled due to excessive runtime. Includes wheel build.
# - build-linux-arm64-release: Builds/tests Release config on Linux arm64 (ARM CPU pool), includes wheel/benchmark flags.
#
Expand Down Expand Up @@ -79,7 +80,7 @@ jobs:
dockerfile_path: tools/ci_build/github/linux/docker/Dockerfile.manylinux2_28_cpu
docker_image_repo: onnxruntimecpubuildpythonx64
# MATERIALIZE=ON needs no explicit pre-build pip install on this leg: the manylinux cp314
# image already ships onnx==1.22.0 + numpy==2.4.2 (the exact gate pins) via its
# image already ships the pinned onnx + numpy versions via its
# requirements.txt (install_deps.sh installs it into cp311-cp314). Intentional, not an
# omission -- unlike the QNN/android legs which run on bare agents and pip-install the pins.
extra_build_flags: '--use_binskim_compliant_compile_flags --build_wheel --build_nuget --enable_transformers_tool_test --cmake_extra_defines onnxruntime_BUILD_BENCHMARKS=ON --cmake_extra_defines onnxruntime_MATERIALIZE_ONNX_NODE_TESTS=ON'
Expand All @@ -103,6 +104,22 @@ jobs:
secrets:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}

build-linux-x64-no-exceptions:
name: Build Linux x64 MinSizeRel (Exceptions Disabled)
uses: ./.github/workflows/reusable_linux_build.yml
with:
pool_name: "onnxruntime-github-Ubuntu2204-AMD-CPU"
build_config: MinSizeRel
architecture: x64
dockerfile_path: tools/ci_build/github/linux/docker/inference/x86_64/default/cpu/Dockerfile
docker_image_repo: onnxruntimecpubuildcix64
# TODO: fix the unit test code (unguarded try/catch and gsl::narrow) to build with exceptions disabled, then build and run the tests here.
extra_build_flags: '--use_binskim_compliant_compile_flags --disable_exceptions --cmake_extra_defines onnxruntime_BUILD_UNIT_TESTS=OFF'
run_tests: false
job_identifier: build-linux-x64-no-exceptions
secrets:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}

# --- arm64 Builds ---
build-linux-arm64-debug:
name: Build Linux arm64 Debug
Expand Down
3 changes: 2 additions & 1 deletion .github/workflows/linux_cuda_ci.yml
Original file line number Diff line number Diff line change
Expand Up @@ -127,6 +127,7 @@ jobs:
mode: 'test' # Set mode to test
execution_providers: 'cuda'
extra_build_flags: >-
--enable_pybind
--use_binskim_compliant_compile_flags
--cuda_version=13.0
--cuda_home=/usr/local/cuda-13.0
Expand All @@ -137,4 +138,4 @@ jobs:
--cmake_extra_defines onnxruntime_QUICK_BUILD=ON
--cmake_extra_defines onnxruntime_ENABLE_CUDA_EP_INTERNAL_TESTS=ON
--cmake_extra_defines onnxruntime_BUILD_CUDA_QUANT_PREPROCESS=ON
python_path_prefix: 'PATH=/opt/python/cp310-cp310/bin:$PATH'
python_path_prefix: 'export ORT_RUN_CUDA_TACTIC_CACHE_TESTS=1 PATH=/opt/python/cp310-cp310/bin:$PATH'
4 changes: 4 additions & 0 deletions .github/workflows/linux_cuda_plugin_ci.yml
Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,8 @@ jobs:
-v ${{ runner.temp }}/Release:/build/Release \
-e NVIDIA_VISIBLE_DEVICES=all \
-e ORT_TEST_CUDA_PLUGIN_EP=1 \
-e ORT_RUN_CUDA_TACTIC_CACHE_TESTS=1 \
-e ORT_CUDA_PLUGIN_PATH=/build/Release/Release/libonnxruntime_providers_cuda.so \
${{ steps.build_docker_image_step.outputs.full-image-name }} \
bash -c "
set -ex
Expand All @@ -144,6 +146,8 @@ jobs:
python -m pip install /build/Release/Release/dist/onnxruntime*.whl
python -m pip install numpy onnx
python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
cd /build/Release/Release
python /onnxruntime_src/onnxruntime/test/python/onnxruntime_test_python_fpa_intb_tune.py
cd /onnxruntime_src/onnxruntime/test/python/transformers
python test_cuda_plugin_ep.py
"
2 changes: 1 addition & 1 deletion .github/workflows/title-only-labeler.yml
Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ jobs:
]
timeout-minutes: 120
steps:
- uses: github/issue-labeler@c1b0f9f52a63158c4adc09425e858e87b32e9685 # v3.4
- uses: github/issue-labeler@ccca1e16fcb66762200e616fc29b57b940c1cb67 # v3.5
with:
repo-token: "${{ secrets.GITHUB_TOKEN }}"
configuration-path: .github/title-only-labeler.yml
Expand Down
70 changes: 0 additions & 70 deletions ThirdPartyNotices.txt
Original file line number Diff line number Diff line change
Expand Up @@ -19,76 +19,6 @@ General Public License.

_____

Intel Math Kernel Library (Intel MKL)

Intel Simplified Software License (Version April 2018)

Copyright (c) 2018 Intel Corporation.

Use and Redistribution. You may use and redistribute the software (the “Software”), without modification,
provided the following conditions are met:

* Redistributions must reproduce the above copyright notice and the following terms of use in the Software
and in the documentation and/or other materials provided with the distribution.

* Neither the name of Intel nor the names of its suppliers may be used to endorse or promote products
derived from this Software without specific prior written permission.

* No reverse engineering, decompilation, or disassembly of this Software is permitted.

Limited patent license. Intel grants you a world-wide, royalty-free, non-exclusive license under patents it now
or hereafter owns or controls to make, have made, use, import, offer to sell and sell (“Utilize”) this Software,
but solely to the extent that any such patent is necessary to Utilize the Software alone. The patent license
shall not apply to any combinations which include this software. No hardware per se is licensed hereunder.

Third party and other Intel programs. “Third Party Programs” are the files listed in the “third-party-programs.txt”
text file that is included with the Software and may include Intel programs under separate license terms.
Third Party Programs, even if included with the distribution of the Materials, are governed by
separate license terms and those license terms solely govern your use of those programs.

DISCLAIMER. THIS SOFTWARE IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE, AND NON-INFRINGEMENT ARE DISCLAIMED. THIS SOFTWARE IS
NOT INTENDED FOR USE IN SYSTEMS OR APPLICATIONS WHERE FAILURE OF THE SOFTWARE
MAY CAUSE PERSONAL INJURY OR DEATH AND YOU AGREE THAT YOU ARE FULLY RESPONSIBLE FOR ANY
CLAIMS, COSTS, DAMAGES, EXPENSES, AND ATTORNEYS’ FEES ARISING OUT OF ANY SUCH USE,
EVEN IF ANY CLAIM ALLEGES THAT INTEL WAS NEGLIGENT REGARDING THE DESIGN OR MANUFACTURE OF
THE MATERIALS.

LIMITATION OF LIABILITY. IN NO EVENT WILL INTEL BE LIABLE FOR ANY DIRECT, INDIRECT,
INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY
OF SUCH DAMAGE. YOU AGREE TO INDEMNIFY AND HOLD INTEL HARMLESS AGAINST ANY CLAIMS
AND EXPENSES RESULTING FROM YOUR USE OR UNAUTHORIZED USE OF THE SOFTWARE.

No support. Intel may make changes to the Software, at any time without notice, and is not obligated to
support, update or provide training for the Software.

Termination. Intel may terminate your right to use the Software in the event of your breach of this Agreement
and you fail to cure the breach within a reasonable period of time.

Feedback. Should you provide Intel with comments, modifications, corrections, enhancements or other input
(“Feedback”) related to the Software Intel will be free to use, disclose, reproduce, license or otherwise
distribute or exploit the Feedback in its sole discretion without any obligations or restrictions of any kind,
including without limitation, intellectual property rights or licensing obligations.

Compliance with laws. You agree to comply with all relevant laws and regulations governing your use,
transfer, import or export (or prohibition thereof) of the Software.

Governing law. All disputes will be governed by the laws of the United States of America and the State of
Delaware without reference to conflict of law principles and subject to the exclusive jurisdiction of the state or
federal courts sitting in the State of Delaware, and each party agrees that it submits to the personal
jurisdiction and venue of those courts and waives any objections. The United Nations Convention on
Contracts for the International Sale of Goods (1980) is specifically excluded and will not apply to the
Software.

*Other names and brands may be claimed as the property of others.

_____

protocolbuffers/protobuf

Copyright 2008 Google Inc. All rights reserved.
Expand Down
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