### Description
<!-- Describe your changes. -->
* Integrate TRT 8.6EA on relevant Linux/Windows/pkg pipelines
* Update onnx-tensorrt to 8.6
* Add new dockerfiles for TRT 8.6 and clean old ones
* Update
[CGManifest](https://github.com/microsoft/onnxruntime/tree/main/cgmanifests)
files and ort build deps version
* yml/script update
* Enable built-in TRT parser option on TRT related pipelines by default
* Exclude test TopKOperator.Top3ExplicitAxisInfinity out of TRT EP tests
(8.6-EA has issue with topk operator)
This change moves the DML CI pipeline to the A10 machines and fixes or
disables tests that were failing from this change.
- Max error rate threshold was increased for Image Tests
- Some failing batch tests were disabled
---------
Co-authored-by: Changming Sun <chasun@microsoft.com>
### Description
<!-- Describe your changes. -->
As title
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
https://github.com/microsoft/onnxruntime/issues/15110
---------
Co-authored-by: rachguo <rachguo@rachguos-Mac-mini.local>
Co-authored-by: rachguo <rachguo@rachguos-Mini.attlocal.net>
Co-authored-by: Scott McKay <skottmckay@gmail.com>
### Description
add script to validate generated NPM packages and publish it to
artifacts, so that release pipeline can use it.
once this PR is merged, I will update the NPM package release pipeline.
### Description
Implement Optional Type metadata support in the library.
Implement optional support in C# API along with metadata.
Implement Sequence, Map, Optional test data support
and test execution.
Prune tests and provide more details for failing tests in C# code.
Note, this PR does not enable running onnx test models in C++.
### Motivation and Context
Opset18 optional type support.
### Description
1. Move it to a separated pool that use the same image as [the public
hosted
pool](https://learn.microsoft.com/en-us/azure/devops/pipelines/agents/hosted?view=azure-devops&tabs=yaml).
Also, create a beta pool which contains the next version image of the
hosted pool, and add jobs in our post merge pipeline to test if the next
version image will break our CI. So, usually we will have at least one
week to prepare.
2. Change the cmake generator in use in our pipelines from "Ninja" to
"MingW Makefile", because the latest version of cmake doesn't work with
the latest version of Ninja. People who prefer Ninja could still use
ninja in their local build by passing "--cmake_generator ninja" to
[build.py](https://github.com/microsoft/onnxruntime/blob/main/tools/ci_build/build.py).
3. Delete eager mode CI pipeline.
### Motivation and Context
I need to update the software we have in our CI build machines, and I
need to resolve this incompatibility issue. In more detail, the build
error I hit was:
em++: error:
CMakeFilesonnxruntime_mlas_test.dirC_a_work1sonnxruntimetestmlasunittesttest_activation.cpp.o:
No such file or directory
("CMakeFilesonnxruntime_mlas_test.dirC_a_work1sonnxruntimetestmlasunittesttest_activation.cpp.o"
was expected to be an input file, based on the commandline arguments
provided)
After this PR we will deprecate python 3.7 support. The eager mode CI
pipeline is the last one that still use python 3.7. Then we can rework
the PR #10953 made by [fs-eire](https://github.com/fs-eire) last year.
Fixed
[AB#14435](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/14435)
Add workflow to update Objective-C API docs. Remove the Objective-C API doc generation step from the packaging pipeline.
There are similar workflows for automatically updating other language API docs. This change enables this for Objective-C too.
Ensure that we build with a known version of NDK and are not surprised when the default version on the build machine changes.
A similar change was made for other Android build pipelines previously, but this one was missed.
### Description
1. The protoc package on nuget.org contains binaries for
Windows_x86/Windows_x64/Linux_x86/Linux_x64/MacOS_x64, which can cover
most use cases. Though it doesn't have binaries for AMR64, they are only
needed when we cross-compile for Intel CPUs on ARM CPUs. It is rare.
When you have such a need, you always can build protoc from source by
yourself and pass it to build.py as "--path_to_protoc_exe". Or if you
have security concerns that you don't want to use prebuilt binaries from
outside, you can do the same thing.
2. Remove GoogleTestAdapter related thing. That part of code is out of
maintain.
### Motivation and Context
As a follow-up of PR #15190.
### Description
Update mimalloc dependency.
### Motivation and Context
The latest release contains important fixes including memory leaks and
used by customers.
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.
### Description
Upgrade remainding python to 3.11 removing 3.7
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
Update python package pipeline to support 3.11
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
In merge branch, the run only reads the cache generated in main build.
As a result, each run in merge branch will not upload new cache except
at the first time.
### Motivation and Context
1.Reduce the cache storage.
If there's some big changes, devs should trigger the specific builds
manually in https://dev.azure.com/onnxruntime/onnxruntime/_build. It
still reads own branch cache.
Temporarily remove Azure build check to unblock PR(s).
We need to investigate the sudden build failure and reenable.
Co-authored-by: Randy Shuai <rashuai@microsoft.com>
rocm python packaging pipeline failed because manylinux version and
manylinux.patch update.
1. fix duplicate `epel-release` installation issue, ROCm pipeline
install it at the begin of the dockerfile to install rocm libs. remove
duplicate installation on install-runtime-packages.sh.
```
/var/tmp/yum-root-sMRl36/epel-release-latest-7.noarch.rpm: does not update installed package.
Error: Nothing to do
```
2. add python10 to fix error below.
```
+ /opt/python/cp310-cp310/bin/python -m venv /opt/_internal/tools
build_scripts/finalize.sh: line 40: /opt/python/cp310-cp310/bin/python: No such file or directory
```
3. add python10 to rocm pipeline.
pipeline link:
https://aiinfra.visualstudio.com/Lotus/_build/results?buildId=294776&view=results
### Description
1. Make 2 cache tasks in one pipeline really works
2. Each building step has its own environment variable CCACHE_DIR
instead of job variables.
3. Extenal Protobuf compilation cache only updates with deps.txt. It
doesn't generate new cache in every commit.
### Motivation and Context
The simple workflow is as below
```
--------build with ccache-------
|
cache
|
{CCACHE_DIR}-----cache stat.
```
```
-------Cache@2------
|
download cache
|
{path}--------upload cache
```
1. {XXX} means environment variable or task input.
2. {CCACHE_DIR} must be consistent with {path}. Ccache produces caches
in {CCACHE_DIR} and Cache@2 download cache into {path} and tar {path}
and upload it.
3. Protobuf changes with deps.txt so that it would reduce the storage
size.
4. Next step, we may split the compilation into 2 steps, one for
external dependencies and another for ORT.
### Description
1. move the cache task definition into template
2. In debug mode, the compiler mtime is different in different machine.
So, change the CCACHE_COMPILERCHECK to content.
### Motivation and Context
1. Accelerate the CoreML pipeline.
Test run:
https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=938040&view=logs&j=1ac7588f-a5bd-5ff7-4a8a-a34869d50220
With Cache, the run can be finished in 12 minutes. Without cache, it
takes about 1 hour.
3. Make the cache function easy to use and maintain.
---------
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
### Description
This PR disables browser test temporarily. The test randomly fails and
we are investigating the issue. Disable the test to unblock others.
### Description
1. Remove Linux jobs for ORT-Extension combined build
2. Add a macOS build job for ORT-Extension combined build
3. Adjust the yaml file so that it can support two different ADO
instances.
### Motivation and Context
To test our code better. And it will enable us to run such tests for
every commit in the main branch. It would be easier for us to figure out
which change caused a build break.
See
[AB#13435](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/13435)
### Description
windows update python3.11
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
---------
Co-authored-by: Ubuntu <chasun@chasunlinux.lw3b1xzoyrkuzm34swpscft0ff.dx.internal.cloudapp.net>
### Description
1. Move Linux CPU pipelines to an AMD CPU pool which is cheaper
2. Enable CCache for orttraining pipeline
### Motivation and Context
Azure AMD CPU machines are generally much cheaper than Intel CPU
machines. However, they don't have local disks.
### Description
Pause caching the docker images in pipeline cache in Linux Aten
Pipeline.
### Motivation and Context
We need to work out a better way to reduce the storage.
### Description
`lintrunner` is a linter runner successfully used by pytorch, onnx and
onnx-script. It provides a uniform experience running linters locally
and in CI. It supports all major dev systems: Windows, Linux and MacOs.
The checks are enforced by the `Python format` workflow.
This PR adopts `lintrunner` to onnxruntime and fixed ~2000 flake8 errors
in Python code. `lintrunner` now runs all required python lints
including `ruff`(replacing `flake8`), `black` and `isort`. Future lints
like `clang-format` can be added.
Most errors are auto-fixed by `ruff` and the fixes should be considered
robust.
Lints that are more complicated to fix are applied `# noqa` for now and
should be fixed in follow up PRs.
### Notable changes
1. This PR **removed some suboptimal patterns**:
- `not xxx in` -> `xxx not in` membership checks
- bare excepts (`except:` -> `except Exception`)
- unused imports
The follow up PR will remove:
- `import *`
- mutable values as default in function definitions (`def func(a=[])`)
- more unused imports
- unused local variables
2. Use `ruff` to replace `flake8`. `ruff` is much (40x) faster than
flake8 and is more robust. We are using it successfully in onnx and
onnx-script. It also supports auto-fixing many flake8 errors.
3. Removed the legacy flake8 ci flow and updated docs.
4. The added workflow supports SARIF code scanning reports on github,
example snapshot:
5. Removed `onnxruntime-python-checks-ci-pipeline` as redundant
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Unified linting experience in CI and local.
Replacing https://github.com/microsoft/onnxruntime/pull/14306
---------
Signed-off-by: Justin Chu <justinchu@microsoft.com>
### Description
Use build.sourceversion in docker image cache key.
### Motivation and Context
We used filpath as the cache key in #14496.
In most cases, the docker base image tag is latest.
So, the hash of the files couldn't be aware of the change of base image.
As the result, the docker image restored, but the image will still be
rebuilt .
The maintenance cost would be huge if we pin image hash in docker file.
For example,
https://quay.io/repository/pypa/manylinux2014_x86_64?tab=tags&tag=latest,
it's updated almost every week.
So far, the build.sourceversion is the right way to keep cache is
updated and valid.
### Description
<!-- Describe your changes. -->
1. upgrade cutlass to 3.0 that containing attn_bias support.
2. extend Attention/MHA to use memory efficient attention when
rel_pos_bias with [1, num_head, s, s*] and 1d mask with [2 * batch_size
+ 1] are present.
new mask format introduction:
MASK_1D_KEY_SEQ_LEN_START,
[3 * batch_size + 2] with [key_len[0], ..., key_len[batch_size - 1],
query_start[0], ..., query_start[batch_size - 1], query_end[batch_size -
1], key_start[0], ..., key_start[batch_size - 1], key_end[batch_size -
1]]
e.g
2D mask with [[1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0]] converts to this
1D mask is [3, 5, 0, 6, 12, 0, 6, 12]
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
It potentially benefits tnlrv6 and t5(encoder)
---------
Co-authored-by: Ubuntu <wy@v100-2.0cdb2e52twzevn1i4fi45bylyg.jx.internal.cloudapp.net>
Co-authored-by: Kunal Vaishnavi <kvaishnavi@microsoft.com>
Co-authored-by: Kunal Vaishnavi <kvaishnavi@microsoft.com@orttrainingdev7.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
### Description
Check the Mac x86_64 packages installation.
### Motivation and Context
To avoid installation error, add packages smoking test before release.
### Description
<!-- Describe your changes. -->
This fix macos packaging build on universal2 arch.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
Re-enable the react native e2e android unit test for react native CI as
recent change of specifying `default` instead of `google-apis` in
android emulator CI tests gives pretty stable result for now.
Upgrade the targetSDKversion for gradle test project in
react-native/android to meet minimum target api level requirement for
Google Play apps.
https://support.google.com/googleplay/android-developer/answer/11926878?hl=en
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
React Native CI issue.
### Description
BUG FIX: the if...else in telemetry-steps.yml does not really work. It
always says "Telemetry is disabled." even through the pipeline doesn't
have the pipeline variable.
### Motivation and Context
For example, recently I setup a new pipeline in
https://dev.azure.com/onnxruntime/onnxruntime/_build without setting the
ADO variable, but the powershell code still thinks that we have enabled
telemetry.
See:
https://dev.azure.com/onnxruntime/onnxruntime/_build/results?buildId=910107&view=results
The reason it didn't work because when the pipeline
variable("TELEMETRYGUID") doesn't exist, the occurrence of
"$(TELEMETRYGUID)" would be not replace to anything. It will remain as
it is.
### Description
- Add QNN 2.8 SDK
- Make QNN SDK version a pipeline template parameter for QNN pipelines.
### Motivation and Context
Updates to latest QNN SDK version, and allows testing different QNN SDK
versions without modifying yaml files.
- Use java/gradlew directly in .github/workflows/publish-java-apidocs.yml.
- Remove use of deleted step from tools/ci_build/github/azure-pipelines/android-arm64-v8a-QNN-crosscompile-ci-pipeline.yml.
- Remove Gradle installations and PATH updates from Dockerfiles and scripts. Now Gradle wrapper is used so a system Gradle installation is not needed.
### Description
Make patch manylinux one single step.
### Motivation and Context
If we want to use hash of docker-related files as the cache key, the
files should keep consistent before and after docker build.
And changes in generated build_scripts should trigger rebuilding the
image as well.
### Description
tensorboard depends on rsa>=3.1.4, while rsa 4.5 has vuln issue, so pin
it to higher version as suggested
Fixed
[AB#7352](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/7352)
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
- Update Gradle version used in most places from 6.8.3 to 8.0.1. Update Android Gradle Plugin version where applicable.
Not updated in this change: React Native Android projects (under `js/react_native/`). That can be done later along with updating the React Native projects.
- Add Gradle wrapper in `java/` to make it easier to consistently use a specific Gradle version.
### Description
Current pipeline refers to an old image which is causing test failures.
Updating the image to the latest one.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
Fixes pipeline failure:
https://dev.azure.com/onnxruntime/onnxruntime/_build?definitionId=198
- If it fixes an open issue, please link to the issue here. -->
### Description
Split up the ORT build step in the Linux QNN CI Pipeline.
### Motivation and Context
Build errors were not being immediately reported at the end of the build
step. The build step currently concatenates multiple shell commands, and
the return code for the last (mkdir) was being reported. This PR ensures
that the return code of the `python build.py ...` command is reported
for the build step.
### Description
To reduce CUDA package's size a little bit. 37 is for Tesla K80. Azure's
NC-series uses it, but in most cases CUDA can dynamic generate device
code .
### Description
1. Remove Python 3.7 from the python packaging pipeline. It is planned
for the next release and approved by the PMs. Also we will add 3.11, but
it will be addressed in another PR.
2. Stop generating python packages based on Ubuntu 18.04 which will
reach EOL next month. We will either replace them with Ubuntu 20.04 or a
CentOS 8 variant.
### Description
<!-- Describe your changes. -->
Consume ONNX 1.13.1 in ONNX Runtime. (ONNX 1.13.0 to ONNX 1.13.1)
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
ONNX 1.13.1 patch was just released yesterday. This PR is making ORT's
ONNX submodule consistent with the latest released ONNX. Not sure
whether this PR is really needed, but let me make it ready. Previous PR
for testing ONNX 1.13.1rc2 :
https://github.com/microsoft/onnxruntime/pull/14634.
Fixed
[AB#13174](https://aiinfra.visualstudio.com/6a833879-cd9b-44a4-a9de-adc2d818f13c/_workitems/edit/13174)
.
### Description
<!-- Describe your changes. -->
Changes to support standalone custom ops in a minimal build. Also
incorporates changes from #14492 (needed to test builds prior to that
being checked in).
We first need to save the schema info from the operators used by the
standalone op invoker in the ORT format model. Add mechanism for that.
Merge the kernel lookup logic so the same is used in full and minimal
build. NOTE: the version matching is now consistent with all other
kernel lookups, and the call to CreateOp MUST use the exact version for
the operator. Previously matching wasn't as strict, but this can lead to
the incorrect kernel being chosen.
Add tests.
NOTE: There is currently no way to detect the ops/types/opsets used
inside these custom ops as they don't exist until we create kernels,
which is after model loading completes (which is the point the ORT
format model is saved). Due to that they have to be manually added to
the configuration used to do the reduced ops build. That shouldn't be
too hard for the custom op author to add given the custom op
implementation is specifying the op, opset and type constraints (i.e.
they have the info and it's just a case of capturing/formatting it
correctly).
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Enable usage of the standalone op invoker by custom ops in a minimal
build.
---------
Co-authored-by: Edward Chen <18449977+edgchen1@users.noreply.github.com>
### Description
Make GPU job depends on all CPU jobs
### Motivation and Context
GPU resources are very limited in packaging pipeline.
And GPU test job is very time consuming.
Only one CPU job fails, the workflow fails, so the GPU job is
meaningless.
To utilize GPU resources more efficiently, run GPU job only after all
CPU jobs succeed.
###test pipeline
https://dev.azure.com/aiinfra/Lotus/_build/results?buildId=280905&view=results
### Description
allow onnxruntime_test_all to run in browser for WebAssembly build (use
flag `--wasm_run_tests_in_browser`).
To output the logs from stdout correctly, this test needs to be build
with `--enable_wasm_threads`.
### Description
<!-- Describe your changes. -->
Disable e2e android react native test temporarily to unblock the CI
failure with no easy fix.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Temp solution to unblock CI failure.
### Description
<!-- Describe your changes. -->
PR a change made to 1.14.1 into Main branch as well.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
### Description
<!-- Describe your changes. -->
Merging extensions from Git submodule to cmake FetchContent
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
---------
Co-authored-by: Changming Sun <chasun@microsoft.com>
Co-authored-by: Jian Chen <jchen351@MacBook-Pro.local>
### Description
<!-- Describe your changes. -->
Update java/build.gradle to not use deprecated features that were
removed in gradle 8.0.
Also move gradle wrapper setup from a script into a step template.
### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->
Fix builds which use hosted Mac agents and gradle.
Recently the system version of gradle got upgraded to 8.0. Even though
we use an older gradle wrapper version, java/build.gradle is still
processed with gradle 8.0 in the initial call to `gradle wrapper`.
### Description
Fixes the DML release build for 1.14.1. This was initially fixed by
https://github.com/microsoft/onnxruntime/pull/13417 for 1.13.1, but the
changes didn't make their way back to the main branch.
### Description
Introduce collective ops into onnxruntime inference build, including
1) AllReduce and AllGather schema in contrib op, controlled by USE_MPI
flag
2) AllReduce and AllGather kernel in cuda EP, controlled by ORT_USE_NCCL
flag
### Motivation and Context
Enable the collective ops in onnxruntime inference build so we have the
ability to run distributed inference with multiple GPUs.
The original ncclAllReduce ops in training build require quite complex
configurations, which is not suitable for inference case, and it already
broken. so we introduce a new implementation.
---------
Co-authored-by: Cheng Tang <chenta@microsoft.com@orttrainingdev9.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
### Description
upgrade protobuf to 3.20.2, same as onnx 1.13.0
### Motivation and Context
Per component governance requirement and Fixes#14060
unused-parameter error occurs in 2 conditions.
1. compile protolbuf
`onnxruntime_src/cmake/external/protobuf/src/google/protobuf/repeated_ptr_field.h:752:66:
error: unused parameter ‘prototype’ [-Werror=unused-parameter]`
2. include onnx_pb.h
```
2023-01-28T10:20:15.0410853Z FAILED: CMakeFiles/onnxruntime_pybind11_state.dir/onnxruntime_src/onnxruntime/python/onnxruntime_pybind_iobinding.cc.o
......
2023-01-28T10:20:15.0466024Z from /build/Debug/_deps/onnx-src/onnx/onnx_pb.h:51,
2023-01-28T10:20:15.0466958Z from /onnxruntime_src/include/onnxruntime/core/framework/to_tensor_proto_element_type.h:10,
....
2023-01-28T10:20:15.0609678Z /build/Debug/_deps/onnx-build/onnx/onnx-operators-ml.pb.h:1178:25: required from here
2023-01-28T10:20:15.0610895Z /onnxruntime_src/cmake/external/protobuf/src/google/protobuf/repeated_ptr_field.h:752:66: error: unused parameter ‘prototype’ [-Werror=unused-parameter]
2023-01-28T10:20:15.0611707Z cc1plus: all warnings being treated as errors
```
https://dev.azure.com/onnxruntime/2a773b67-e88b-4c7f-9fc0-87d31fea8ef2/_apis/build/builds/874605/logs/22
PyTorch skipped version 1.14 and jumped to 2.0, while the image for the
onnxruntime-CI-nightly-ort-pipeline is still using
nightly-ubuntu2004-cu116-py38-torch1140dev. Switch to the new torch
version image to fix the failure of the pipeline.
Update Android package custom build script.
- Use later version of various dependencies (CMake, JDK, Android command line tools, Android NDK, Ubuntu). The CMake version was too old for the current ORT code.
- Do in-container build in a directory that is not shared with the host. Resolves some file permission issues and speeds up file access.
Add a nightly build to make sure the script works with the latest ORT.
…ckaging_CPU_x86_default (#14332)"
This reverts commit a491f33f54.
### Description
### Motivation and Context
It looks an ADO issue.
Now, it's recovered.
It could be reenabled.
### Description
Remove intermedia obj files and reenable cache
### Motivation and Context
Recently, training_debug_x64 pipeline often failed due to not enough
space.
It could free nearly 8G space by deleting obj files.
So, the compilation cache can be reenabled
- Fix debug node inputs outputs nullptr dereference with ONNX optional types.
- Fix model test memory leak.
- Convert jobs to stages in post-merge-jobs.yml to allow a subset of builds to be enabled when running manually.
- Fix buffer overrun in CumSum op exposed by Mimalloc build.
### Description
disable cache to save disk space for training_x64_debug
### Motivation and Context
To mitigate not enough disk space in training_x64_debug first.
### Description
Allows the PostAnalysis@2 task for windows CI jobs to continue even if
an error is encountered.
### Motivation and Context
This is a temporary workaround that enables the
`Windows_Packaging_CPU_x86_default` job within the Zip-Nuget-Java-NodeJS
packaging pipeline to finish. A recent update to dotnet 6 has broken the
PostAnalysis task for this job.
This task was originally added by
https://github.com/microsoft/onnxruntime/pull/13694
