* Change msbuild condition for UAP
* update .netcore target as well
* create nuget packages with _native path
* validate path under _native directory for windowsai package
* pep8
* add diagnostic error message
* pep8
* use baseame
* lib\uap10.0
* uap10
* build\\uap10.0
* Manually binplace winmds into appx when PackageReference is used.
* always binplace winmd regardless of packagereference since c# should work with packages.config also
* resolve all paths to full paths to avoid some reference warnings
* move winmds out of lib folder to prevent automatic component registration
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
Add python 3.8/3.9 support for Windows GPU and Linux ARM64
Delete jemalloc from cgmanifest.json.
Add onnx node test to Nuphar pipeline.
Change $ANDROID_HOME/ndk-bundle to $ANDROID_NDK_HOME. The later one is more accurate.
Delete Java GPU packaging pipeline
Remove test data download step in Nuget Mac OS pipeline. Because these machines are out of control and out of our network, it's hard to make it reliable and the data secure.
Fix a doc problem in c-api-artifacts-package-and-publish-steps-windows.yml. It shouldn't copy C_API.md, because the file has been moved into a different branch.
Delete the CI build docker file for Ubuntu cuda 9.x and Ubuntu x86 32 bits
And, due to some internal restrictions, I need to rename some of the agent pools
Update gpu packaging pipelines to CUDA11
In the next release we will use CUDA 11. And our CUDA 11 build suddenly became broken because recently CentOS 7 posted an update of glibc. The version of glibc was changed from 2.17-317.el7 to 2.17-322.el7_9. But the newer one isn't compatible with CUDA 11. We have to downgrade it.
1. Merge Nuget CPU pipeline, Java CPU pipeline, C-API pipeline into a single one.
2. Enable compile warnings for cuda files(*.cu) on Windows.
3. Enable static code analyze for the Windows builds in these jobs. For example, this is our first time scanning the JNI code.
4. Fix some warnings in the training code.
5. Enable code sign for Java. Previously we forgot it.
6. Update TPN.txt to remove Jemalloc.
* build for .net5
* only reference cswinrt for .net5
* remove netstandard2.0 references
* upgrade language version
* net5
* remove extra comment closure
* add targetframework
* set target framework
* remove net*
* pep8 errors
* make test project build with .net windows SDK projection
* disable c# builds for non-x64 builds
* fix pep8 errors
* disable for store build
* fix tests
* remove cswinrt and sdk references from package
* bump cswinrt down to 1.0.1
* fix bin path
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
Transitions from the ORT-only DML NuGet (hosted on the onnxruntime_public feed) to the new unified DirectML NuGet (Microsoft.AI.DirectML) on nuget.org. In addition, the Microsoft.AI.MachineLearning (WinML) and Microsoft.ML.OnnxRuntime.DirectML packages now take a dependency on the Microsoft.AI.DirectML package. This means we can remove the extra copy of DML binaries in these packages since they will be installed by the DML package.
* create new nuget packaging pipeline without openmp
* rename package
* update image name
* rename package name
* rename managed package
* reset project attribute
* merge master
* set package name
* set NoOpenMP as cpu build
* shorten line length
Co-authored-by: Randy Shuai <rashuai@microsoft.com>
* Nuget store packaging
* Move DNNL workaround to EP
* Fix warning as error
* Disable store tests
* Skip store tests
* msbuild target
* Cross compile protoc in Store
* Disable DML in store
* Move store builds to CPU queue
* Copy uap10 to final nuget
* Fix pip8 error
* Remove extra dml copies
* Fix argparse
* pep8
* Forward IsStoreBuild
* Apply is_store_build to duplicate generate_nuspec
* runtimes
* Refactor uap10
* Store .NET
* uap
* PR feedback
1. Publish the image ACR, instead of building it every time for every PR
2. Make USE_MKLML and USE_OPENMP be able to co-exist. Currently both of them are enabled in our Linux CI build but indeed only one of them is taking effect.
3. Split nuphar and DNNL to separated pipelines.
4. Fix two warnings in onnxruntime/core/optimizer/matmul_scale_fusion.cc and onnxruntime/test/tvm/tvm_basic_test.cc.
5. Update the manylinux2010_x86_64 image to the latest.
* bump cswinrt version
* add cswinrt
* test dotnetcore 3.0
* rename buildpacakge source
* set folder path to the package source and not the version
* refactor .netframework tests
* build .net core anycpu
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
1. Avoid building ONNX of every history ONNX versions in our CI, it is costly and easy to fail.
2. Run docker command without sudo. Previously the user is not in docker group, now Azure DevOps Service have added it in.
* build e2e cppwinrt tests
* add use nuget task
* make all referenced to package version prop/target-ified
* remove dupe props/targets reference
* work around project.assets.json error by deleting it
* powershell test invocation
* switch to batch script
* print debug info
* update x86->x64
* stdio.h
* pushd/popd
* add csharp tests
* package.config -> packages.config
* typo
* x86 -> anycpu
* debug is default
* add test path
* update csproj as well
* debug
* really replace all package versions
* debug output
* really use [PackageVersion]
* sleep intead of converting async operation to task and waiting
* dont close software bitmap
* switch to powershell script
* remove binding check
* continue on failure
* continuse on error action
* continueOnError and errorActionPreference
* tabbing
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* Add build option to disable traditional ML ops from the binary.
* Fix python tests by splitting tests for ML ops to a separate file. Exclude ML tests from onnx_test_runner and C# tests. Exclude ML op sources.
* Update Edge pkg pipelines with new MLops env variable and fix C# packaging pipeline tests to skip ML ops.
1. Fix the nuget cpu pipeline and put code coverage pipeline back.
2. Reduce onnx_test_runner's default logging level from WARNING to ERROR. Because there are too many log messages now.
3. Enlarge the protobuf read buffer size for onnx_test_runner. It was missed from PR #4020.
- Add support for ENABLE_LANGUAGE_INTEROP_OPS in training build which is enabled for nightly builds
- Fix passing of environment variables to `sudo docker run` in build definitions
- Fix setup.py package naming logic
