- Update docker image release build to use build commit.
- Use valid default in component governance detection step.
- Use smaller docker build context.
* 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
* enable rejecting models based on onnx opset
* enable unreleased opsets in linux and mac CI
* test fixes and more updates
* enable unreleased opsets in CI builds
* enable released opsets in linux cis
* try fix windows ci yml
* yml fixes
* update yml
* yml updates post master merge
* review comments
* bug fix
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.
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.
1. Increase job timeout, while we are investigating why the tests take much longer
2. Upgrade the linux docker image to manylinux2010, by request from Tianlei. (We had an offline discussion with Pranav and Tracy)
3. Remove the installation of "devtoolset-7" in the CUDA image. It was added for CUDA 10.0, it is not needed for CUDA 10.1. We have moved to CUDA 10.1.
Modify gradle build so artifactID has _gpu for GPU builds.
Pass USE_CUDA flag on CUDA build
Adjust publishing pipelines to extract POM from a correct path.
Co-Authored-By: @Craigacp
* try mac pipeline
* fix path separator
* copy prebuilds folder
* split esrp yaml for win/mac
* disable mac signing temporarily
* add linux
* fix indent
* add nodetool in linux
* add nodetool in win-ci-2019
* replace linux build by custom docker scripts
* use manylinux as node 12.16 not working on centos6
* try ubuntu
* loosen timeout for test case - multiple runs calls
- 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
* add windowsai.yml for new Microsoft.AI.MachineLearning nuget
* temporarily add windowsai.yml to gpu.yml
* pass in build arch
* remove install onnx task
* no dml for arm or arm64
* refactor nuget pipeline defs
* update package creation
* pass in build and sources path
* missing hyphens
* copy license file
* fix parameter variable
* disable arm builds for now
* remove commented script block
* download pipeline atifcat name update
* set working dir
* Add bundling nuget script
* path combine
* null path
* combine needs parentheses
* binplace microsoft.* dlls in new nuget package
* update artifact name
* move merged nuget to artifacts directory
* move to merged subfolder in artifacts staging dir
* forward slash to back
* enable arm
* vcvarsall needs x64 vars setup
* Run Tests
* fix tests
* move global variables
* update yml to not have global variable in template
* removed parameters
* fixes
* Add build arch as an env variable
* ne not neq
* %Var% for batch script
* dont pass argument for x64
* disable arm tests
* skip csharp/cxx tests for microsoft nuget package
* remove test-win as it tests only c# cxx and capi
* test build for store apps
* dont build for store
* tools/nuget/generate_nuspec_for_native_nuget.py
* remove args.
* add new props and targets for microsoft.ai
* make windowsai props/targets static
* add dependency
* dont ship dot net props
* Remove c# fom windowsai nuget
* copy license file
* native packages must have win10 as the platform, not win
* cuda header in wrong if branch
* no dml for arm builds
* only build dml for x64/ x86
* User/sheilk/props update (#3616)
* prelim store work
* props
* Fix desktop nuget props/targets
* clean up targets and make store apps work
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* update windowsai.yml with latest
* remove extra dloadhelpers
* Add abi headers to abi dir, and reference native includes
* update windowsai.yml
* minor update
* remove parameters
* add doesrp param
* hard code esrp to true
* add directml for x86/x64
* revert gpu yml changes
* add store builds
* add store builds
* add checks again in old way
* dup job names for store and desktop builds
* move all of the runtime binaries to win10 folder
* only set safeseh on x86
* disable the store builds for now... missing msvcprt.lib
* copy paste deletion...
* switch back to win- (#3646)
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
* use stahlworks
* & not supported in ado
* add cuda to cpu nuget(???) and EnableDelayedExpansion to enable x86 dml package
* revert nocontribops
* add underscore...
* extra win/win10 change
* merged nuget... still not being bundled...
* files in merged directory
* missing parens causing dml to be included in cpu package
* more diagnostic info
* switch dir to get-childitem
* wait for compression to complete
* add winml_adapter to mkml and gpu packages
* enable_wcos
* add mklml binaries
* props and targets missing from mklml
Co-authored-by: Sheil Kumar <sheilk@microsoft.com>
