### Description
This PR is to update the win-ort-main branch to the tip main branch as
of 2025-01-23.
### PR List
ddf0d377a7 [QNN EP] Add LoggingManager::HasDefaultLogger() to provider
bridge API (#23467)
05fbbdf91f [QNN EP] Make QNN EP a shared library (#23120)
1336566d7f Add custom vcpkg ports (#23456)
2e1173c411 Update the compile flags for vcpkg packages (#23455)
1f628a9858 [Mobile] Add BrowserStack Android MAUI Test (#23383)
009cae0ec8 [js/webgpu] Optimize ConvTranspose (Continue) (#23429)
04a4a694cb Use onnx_protobuf.h to suppress some GCC warnings (#23453)
2e3b62b4b0 Suppress some strict-aliasing related warnings in WebGPU EP
(#23454)
b708f9b1dc Bump ruff from 0.9.1 to 0.9.2 (#23427)
c0afc66b2a [WebNN] Remove workarounds for TFLite backend (#23406)
8a821ff7f9 Bump vite from 6.0.7 to 6.0.11 in
/js/web/test/e2e/exports/testcases/vite-default (#23446)
220c1a203e Make ORT and Dawn use the same protobuf/abseil source code
(#23447)
b7b5792147 Change MacOS-13 to ubuntu on for
android-java-api-aar-test.yml. (#23444)
19d0d2a30f WIP: Dp4MatMulNBits accuracy level 4 matmul for WebGPU EP
(#23365)
95b8effbc4 [QNN EP]: Clean up QNN logging resources if an error occurs
during initialization (#23435)
626134c5b5 Bump clang-format from 19.1.6 to 19.1.7 (#23428)
0cf975301f Fix eigen external deps (#23439)
f9440aedce Moving RN_CI Android Testing to Linux (#23422)
1aa5902ff4 [QNN EP] workaround for QNN validation bug for Tanh with
uint16 quantized output (#23432)
7f5582a0e2 Seperate RN andriod and IOS into 2 separated Stages. (#23400)
73deac2e7f Implement some missing element wise Add/Sub/Mul/Div/Neg
operations for CPU and CUDA EPs (#23090)
949fe42af4 Upgrade Java version from react-native/android to Java 17
(#23066)
0892c23463 Update Qnn SDK default version to 2.30 (#23411)
94c099bcec Fix type cast build error (#23423)
d633e571d1 [WebNN EP] Fix AddInitializersToSkip issues (#23354)
e988ef00e2 [QNN EP] Fix regression for MatMul with two quantized/dynamic
uint16 inputs (#23419)
7538795f6b Update onnxruntime binary size checks ci pipeline's docker
image (#23405)
6c5ea41cad Revert "[QNN EP] Clean up correctly from a partial setup
(#23320)" (#23420)
e866804bbe Enable comprehension simplification in ruff rules (#23414)
0a5f1f392c bugfix: string_view of invalid memory (#23417)
4cc38e0277 fix crash when first input of BatchNormalization is 1-D
(#23387)
033441487f Target py310 and modernize codebase with ruff (#23401)
87341ac010 [QNN EP] Fix segfault when unregistering HTP shared memory
handles (#23402)
### Motivation and Context
This update includes the change to make QNN-EP a shared library.
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: Adrian Lizarraga <adlizarraga@microsoft.com>
Co-authored-by: Justin Chu <justinchuby@users.noreply.github.com>
Co-authored-by: Yulong Wang <7679871+fs-eire@users.noreply.github.com>
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
Co-authored-by: Changming Sun <chasun@microsoft.com>
Co-authored-by: Peishen Yan <peishen.yan@intel.com>
Co-authored-by: Tianlei Wu <tlwu@microsoft.com>
Co-authored-by: Hector Li <hecli@microsoft.com>
Co-authored-by: Jian Chen <cjian@microsoft.com>
Co-authored-by: Alexis Tsogias <1114095+Zyrin@users.noreply.github.com>
Co-authored-by: junchao-zhao <68935141+junchao-loongson@users.noreply.github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: sushraja-msft <44513542+sushraja-msft@users.noreply.github.com>
Co-authored-by: Wanming Lin <wanming.lin@intel.com>
Co-authored-by: Jiajia Qin <jiajiaqin@microsoft.com>
Co-authored-by: Caroline Zhu <wolfivyaura@gmail.com>
### Description
Making ::p optional in the Linux python CUDA package pipeline
### Motivation and Context
Linux stage from Python-CUDA-Packaging-Pipeline has failed since merge
of #22773
### Description
1. Add XNNPack build on Linux ARM64
2. Build only one python wheel for PR request.
[AB#49763](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/49763)
### Motivation and Context
Why I add xnnpack build on Linux ARM64 rather than Windows ARM64.
Becuase KleidiAI doesn't support Windows
```
IF(XNNPACK_TARGET_PROCESSOR STREQUAL "arm64" AND XNNPACK_ENABLE_ARM_I8MM AND NOT CMAKE_C_COMPILER_ID STREQUAL "MSVC")
IF (XNNPACK_ENABLE_KLEIDIAI)
MESSAGE(STATUS "Enabling KleidiAI for Arm64")
ENDIF()
ELSE()
SET(XNNPACK_ENABLE_KLEIDIAI OFF)
ENDIF()
```
---------
1. Add python 3.13 to our python packaging pipelines
2. Because numpy 2.0.0 doesn't support thread free python, this PR also
upgrades numpy to the latest
3. Delete some unused files.
### Description
Similar to #20786 . The last PR was able to update all pipelines and all
docker files. This is a follow-up to that PR.
### Motivation and Context
1. To extract the common part as a reusable build infra among different
ONNX Runtime projects.
2. Avoid hitting docker hub's limit: 429 Too Many Requests - Server
message: toomanyrequests: You have reached your pull rate limit. You may
increase the limit by authenticating and upgrading:
https://www.docker.com/increase-rate-limit
### Description
In PR #19073 I mistunderstood the value of "--parallel". Instead of
testing if args.parallel is None or not , I should test the returned
value of number_of_parallel_jobs function.
If build.py was invoked without --parallel, then args.parallel equals to
1. Because it is the default value. Then we should not add "/MP".
However, the current code adds it. Because if `args.paralllel` is
evaluated to `if 1` , which is True.
If build.py was invoked with --parallel with additional numbers, then
args.parallel equals to 0. Because it is unspecified. Then we should add
"/MP". However, the current code does not add it. Because `if
args.paralllel` is evaluated to `if 0` , which is False.
This also adds a new build flag: use_binskim_compliant_compile_flags, which is intended to be only used in ONNX Runtime team's build pipelines for compliance reasons.
### Motivation and Context
### Description
1. Add two build jobs for enabling Address Sanitizer in CI. One for
Windows CPU, One for Linux CPU.
2. Set default compiler flags/linker flags in build.py for normal
Windows/Linux/MacOS build. This can help control compiler flags in a
more centralized way.
3. All Windows binaries in our official packages will be built with
"/PROFILE" flag. Symbols of onnxruntime.dll can be found at [Microsoft
public symbol
server](https://learn.microsoft.com/en-us/windows-hardware/drivers/debugger/microsoft-public-symbols).
Limitations:
1. On Linux Address Sanitizer ignores RPATH settings in ELF binaries.
Therefore once Address Sanitizer is enabled, before running tests we
need to manually set LD_LIBRARY_PATH properly otherwise
libonnxruntime.so may not be able to find custom ops and shared EPs.
4. On Linux we also need to set LD_PRELOAD before running some tests(if
the main executable, like python, is not built with address sanitizer.
On Windows we do not need to.
5. On Windows before running python tests we should manually copy
address sanitizer DLL to the onnxruntime/capi directory, because python
3.8 and above has enabled "Safe DLL Search Mode" that wouldn't use the
information provided by PATH env.
6. On Linux Address Sanitizer found a lot of memory leaks from our
python binding code. Therefore right now we cannot enable Address
Sanitizer when building ONNX Runtime with python binding.
7. Address Sanitizer itself uses a lot of memory address space and
delays memory deallocations, which is easy to cause OOM issues in 32-bit
applications. We cannot run all the tests in onnxruntime_test_all in
32-bit mode with Address Sanitizer due to this reason. However, we still
can run individual tests in such a way. We just cannot run all of them
in one process.
### Motivation and Context
To catch memory issues.
### Description
Adding python3.12 support to ORT
### Motivation and Context
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- If it fixes an open issue, please link to the issue here. -->
### Description
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### Motivation and Context
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2023-11-20 09:48:28 -08:00
Renamed from tools/ci_build/github/linux/build_linux_arm64_python_package.sh (Browse further)