### Description
<!-- Describe your changes. -->
### 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
1. Enable VCPKG flag in Windows CPU CI build pipelines.
2. Increased the min supported cmake version from 3.26 to 3.28. Because
of it, drop the support for the old way of finding python by
"find_package(PythonLibs)". Therefore, in build.py we no longer set
"PYTHON_EXECUTABLE" cmake var when doing cmake configure.
3. Added "xnnpack-ep" as a feature for ORT's vcpkg config.
4. Added asset cache support for ORT's vcpkg build
5. Added VCPKG triplet files for Android build.
6. Set VCPKG triplet to "universal2-osx" if CMAKE_OSX_ARCHITECTURES was
found in cmake extra defines.
7. Removed a small piece of code in build.py, which was for support CUDA
version < 11.8.
8. Fixed an issue that CMAKE_OSX_ARCHITECTURES sometimes got specified
twice when build.py invoked cmake.
9. Added more model tests to Android build. After this change, we will
test all ONNX versions instead of just the latest one.
10. Fixed issues that are related to build.py's "--build_nuget"
parameter. Also, enable the flag in most Windows CPU CI build jobs.
11. Removed a restriction in build.py that disallowed cross-compiling
Windows ARM64 nuget package on Windows x86.
### Motivation and Context
Adopt vcpkg.
### Description
* Update rocm to 6.3.2;
* Remove dependency on cupy (which does not support rocm 6.3 yet).
### 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. -->
* Update env to cuda 12.6/ubuntu 22.04 (ubuntu 20.04 uses outdated py38
by default)
* Clean old trt8.6 test config
### 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. -->
There is a crash in the WebGPU CI pipeline. It crashed at process
shutdown when unloading onnxruntime_pybind11_state.pyd.
Here is the callstack:
```
dxil.dll!DxcSwapThreadMalloc() Unknown
dxil.dll!DxcThreadMalloc::DxcThreadMalloc(struct IMalloc *) Unknown
dxil.dll!DxcValidator::Release(void) Unknown
[Inline Frame] webgpu_dawn.dll!Microsoft::WRL::ComPtr<IDxcValidator>::InternalRelease() Line 235 C++
[Inline Frame] webgpu_dawn.dll!Microsoft::WRL::ComPtr<IDxcValidator>::{dtor}() Line 290 C++
webgpu_dawn.dll!dawn::native::d3d12::Backend::`scalar deleting destructor'(unsigned int) C++
webgpu_dawn.dll!`eh vector destructor iterator'(void * ptr, unsigned __int64 size, unsigned __int64 count, void(*)(void *) destructor) C++
webgpu_dawn.dll!dawn::native::InstanceBase::~InstanceBase() Line 197 C++
webgpu_dawn.dll!dawn::native::InstanceBase::`scalar deleting destructor'(unsigned int) C++
webgpu_dawn.dll!dawn::native::InstanceBase::DeleteThis() Line 218 C++
ucrtbase.dll!<lambda>(void)() Unknown
ucrtbase.dll!__crt_seh_guarded_call<int>::operator()<<lambda_7777bce6b2f8c936911f934f8298dc43>,<lambda>(void) &,<lambda_3883c3dff614d5e0c5f61bb1ac94921c>>() Unknown
ucrtbase.dll!_execute_onexit_table() Unknown
onnxruntime_pybind11_state.pyd!dllmain_crt_process_detach(const bool is_terminating) Line 182 C++
> onnxruntime_pybind11_state.pyd!dllmain_dispatch(HINSTANCE__ * const instance, const unsigned long reason, void * const reserved) Line 293 C++
ntdll.dll!LdrpCallInitRoutine() Unknown
ntdll.dll!LdrShutdownProcess() Unknown
ntdll.dll!RtlExitUserProcess() Unknown
kernel32.dll!ExitProcessImplementation() Unknown
ucrtbase.dll!exit_or_terminate_process() Unknown
ucrtbase.dll!common_exit() Unknown
python312.dll!00007ff9cab3ec8d() Unknown
python312.dll!00007ff9cab3efbf() Unknown
python312.dll!00007ff9cab3edee() Unknown
python312.dll!00007ff9cab57f4c() Unknown
python312.dll!00007ff9cab57579() Unknown
python312.dll!00007ff9cab573be() Unknown
python312.dll!00007ff9cab5729b() Unknown
python312.dll!00007ff9cabacfcb() Unknown
python312.dll!00007ff9cabacd7d() Unknown
python312.dll!00007ff9cab99e2d() Unknown
python.exe!00007ff78a641230() Unknown
kernel32.dll!BaseThreadInitThunk() Unknown
ntdll.dll!RtlUserThreadStart() Unknown
```
It might be because the destruct order of some global variables was
wrong. I saw DX DLLs were getting destroyed earlier than the WebGPU
instance in our code in onnxruntime_pybind11_state.pyd.
### Description
- Add new build flag in build.py to build onnxruntime.dll supporting
interfaces for all primary EPs( QNN, TensoRT, OpenVino, VitisAI).
- Modify onnxruntime.dll/onnxruntime_shared.dll build settings to remove
dependency of IHV SDK Toolset to be installed on the system.
- Change CMake variables to be explicit when building EP vs ORT. e.g.
onnxruntime_USE_TENSORRT vs onnxruntime_USE_TENSORRT_INTERFACE, to
evolve the build system to build ORT independent of EPs.
### Motivation and Context
Changes in the build system required to evolve the repo to build the
components independently while removing unnecessary dependencies
---------
Co-authored-by: Lei Cao <jslhcl@gmail.com>
Co-authored-by: Karim Vadsariya <kvadsariya@microsoft.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
### Description
This PR updates the version of Dawn to
`b9b4a37041dec3dd62ac92014a6cc1aece48d9f3` (ref:
[chromium](67f86f01dd/DEPS (399)))
in the `deps.txt` file.
The newer version of Dawn includes the previous changes from dawn.patch
so that we can remove the patch file.
There is a little interface changes and code is updated correspondingly.
### Description
Enable coremltools for Linux build. In order to do this, I did:
1. Add uuid-devel to the Linux images and regenerate them.
2. Patch the coremltools code a little bit to add some missing header
files.
### Motivation and Context
To make the code simpler. Later on I will create another PR to remove
the COREML_ENABLE_MLPROGRAM C/C++ macro.
Also, after this PR I will bring more changes to
onnxruntime_provider_coreml.cmake to make it work with vcpkg.
### Description
- Makes QNN EP a shared library **by default** when building with
`--use_qnn` or `--use_qnn shared_lib`. Generates the following build
artifacts:
- **Windows**: `onnxruntime_providers_qnn.dll` and
`onnxruntime_providers_shared.dll`
- **Linux**: `libonnxruntime_providers_qnn.so` and
`libonnxruntime_providers_shared.so`
- **Android**: Not supported. Must build QNN EP as a static library.
- Allows QNN EP to still be built as a static library with `--use_qnn
static_lib`. This is primarily for the Android QNN AAR package.
- Unit tests run for both the static and shared QNN EP builds.
### Detailed changes
- Updates Java bindings to support both shared and static QNN EP builds.
- Provider bridge API:
- Adds logging sink ETW to the provider bridge. Allows EPs to register
ETW callbacks for ORT logging.
- Adds a variety of methods for onnxruntime objects that are needed by
QNN EP.
- QNN EP:
- Adds `ort_api.h` and `ort_api.cc` that encapsulates the API provided
by ORT in a manner that allows the EP to be built as either a shared or
static library.
- Adds custom function to transpose weights for Conv and Gemm (instead
of adding util to provider bridge API).
- Adds custom function to quantize data for LeakyRelu (instead of adding
util to provider bridge API).
- Adds custom ETW tracing for QNN profiling events:
- shared library: defines its own TraceLogging provider handle
- static library: uses ORT's TraceLogging provider handle and existing
telemetry provider.
- ORT-QNN Packages:
- **Python**: Pipelines build QNN EP as a shared library by default.
User can build a local python wheel with QNN EP as a static library by
passing `--use_qnn static_lib`.
- **NuGet**: Pipelines build QNN EP as a shared library by default.
`build.py` currently enforces QNN EP to be built as a shared library.
Can add support for building a QNN NuGet package with static later if
deemed necessary.
- **Android**: Pipelines build QNN EP as a **static library**.
`build.py` enforces QNN EP to be built as a static library. Packaging
multiple shared libraries into an Android AAR package is not currently
supported due to the added need to also distribute a shared libcpp.so
library.
### 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. -->
### 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
Moving Android E2E test steps from Mac-OS13 to unbunt22.04
### Motivation and Context
Deduced the dependency on MacOS, which is deprecating the x64 version.
1. Update onnxruntime binary size checks ci pipeline's docker image. Use
a different docker image that is not manylinux based. The new one is
smaller.
2. Add flatbuffers tools/ci_build/requirements/pybind/requirements.txt
3. Delete
tools/ci_build/github/azure-pipelines/py-package-build-pipeline.yml. The
pipeline was for generating packages for Olive, but it went unused. And
the content is highly duplicated with our official python packaging
pipeline.
4. A lot of YAML files reference pypa/manylinux git repo but do not use
it. This PR removes the references.
Use ruff as the code formatter in place of black and isort since it is
much faster, and as projects like PyTorch and ONNX have adopted ruff
format as well.
This PR include only auto-fixed changes in formatting.
### Description
This PR allows WebGPU EP to be built with Emscripten for WebAssembly,
Including:
- cmake build files update to support correct setup for Emscripten.
- code changes to fix build breaks for wasm
- change in Web CI pipeline to add a build-only target for wasm with
`--use_webgpu`.
