### Description
[DML EP] Update DML to 1.15.4
### Motivation and Context
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We want the customer to use the latest DirectML.
### Description
Update DML runtime binary to 1.15.1
### Motivation and Context
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### Description
Fix regression caused by
https://github.com/microsoft/onnxruntime/pull/20995
### Motivation and Context
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### Description
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### Motivation and Context
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### Description
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### Motivation and Context
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I am prefiring this change to pre-run the non-dml checks, and also to
give folks the time to review it before DML gets released. When DML 1.14
officially releases, we'll only need to run the DML pipeline to
automatically pick up the nuget package. This should save us some
valuable time.
Note that DML 1.14 is the release needed for ORT 1.17.4, and DML 1.15
will come soon after.
### Description
1. Upgrade the version from 10.0.19041.0 to 10.0.22621.0. The old one
misses some macros that are needed by PyTorch's CPUINFO
2. Also update cmake.
### Motivation and Context
In PR #19655 I added CPUINFO to all Windows builds, but forgot to test
this pipeline.
### 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
Update DML version to 1.13.1
### Motivation and Context
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### 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
1. Remove Windows ARM32 from nuget packaging pipelines
2. Add missing component-governance-component-detection-steps.yml to
some build jobs.
### Motivation and Context
Stop supporting Windows ARM32 to align with [Windows's support
policy](https://learn.microsoft.com/en-us/windows/arm/arm32-to-arm64).
Users who need this feature still can build the DLLs from source.
However, later on we will remove that support too.
### Description
- Update DML version to 1.11.0
- Disable Gemm+Softmax fusion
### Motivation and Context
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### Description
They were missed in #15707 , because they are not in common places for Dockerfiles.
Though this commit updated tools/ci_build/github/pai/rocm-ci-pipeline-env.Dockerfile, it won't automatically take effect. The image needs to be manually generated and pushed to a place, and before doing that our CMakeLists.txt also needs to be tweaked a little bit.
WindowsAI build failing due to deprecated .NET5 SDK missing in build
image
.NET5 was deprecated last year, and recently the build machine images
have been updated to not include this SDK.
Unblock failing builds by force insalling .NET5 SDK as part of the build
pipeline.
This reverts commit f88a4646cd.
### Description
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### Motivation and Context
For release, winai packaing pipeline's container image is revert to old
image.
So we should revert VS to 2019
### Description
update VS2019 to VS 2022 in
onnxruntime-Nuget-WindowsAI-Pipeline-Official
### Motivation and Context
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### Description
Updated DirectML version to 1.10.1
(https://www.nuget.org/packages/Microsoft.AI.DirectML/1.10.1)
### Motivation and Context
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1. Remove the cmake option onnxruntime_DEV_MODE and replace it with
"--compile-no-warning-as-error"
2. Suppress some GSL warnings because now we treat nvcc diag warnings as
errors
