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https://github.com/saymrwulf/onnxruntime.git
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3b4c7df4e9
### 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. -->
97 lines
3 KiB
Bash
Executable file
97 lines
3 KiB
Bash
Executable file
#!/bin/bash
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set -e -x
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# This script invokes build.py
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mkdir -p /build/dist
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EXTRA_ARG=""
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ENABLE_CACHE=false
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# Put 3.10 at the last because Ubuntu 22.04 use python 3.10 and we will upload the intermediate build files of this
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# config to Azure DevOps Artifacts and download them to a Ubuntu 22.04 machine to run the tests.
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PYTHON_EXES=(
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"/opt/python/cp311-cp311/bin/python3.11"
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"/opt/python/cp312-cp312/bin/python3.12"
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"/opt/python/cp313-cp313/bin/python3.13"
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"/opt/python/cp313-cp313t/bin/python3.13t"
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"/opt/python/cp310-cp310/bin/python3.10"
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)
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while getopts "d:p:x:c:e" parameter_Option
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do case "${parameter_Option}"
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in
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#GPU|CPU|NPU.
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d) BUILD_DEVICE=${OPTARG};;
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p)
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# Check if OPTARG is empty or starts with a hyphen, indicating a missing or invalid argument for -p
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if [[ -z "${OPTARG}" || "${OPTARG}" == -* ]]; then
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echo "ERROR: Option -p requires a valid argument, not another option."
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exit 1
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else
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PYTHON_EXES=("${OPTARG}") # Use the provided argument for -p
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fi
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;;
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x) EXTRA_ARG=${OPTARG};;
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c) BUILD_CONFIG=${OPTARG};;
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e) ENABLE_CACHE=true;;
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*) echo "Usage: $0 -d <GPU|CPU|NPU> [-p <python_exe_path>] [-x <extra_build_arg>] [-c <build_config>]"
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exit 1;;
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esac
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done
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BUILD_ARGS=("--build_dir" "/build" "--config" "$BUILD_CONFIG" "--update" "--build" "--skip_submodule_sync" "--parallel" "--use_binskim_compliant_compile_flags" "--build_wheel")
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if [ "$BUILD_CONFIG" != "Debug" ]; then
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BUILD_ARGS+=("--enable_lto")
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fi
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if [ "$ENABLE_CACHE" = true ] ; then
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BUILD_ARGS+=("--use_cache")
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ccache -s;
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fi
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ARCH=$(uname -m)
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echo "EXTRA_ARG:"
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echo "$EXTRA_ARG"
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if [ "$EXTRA_ARG" != "" ]; then
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BUILD_ARGS+=("$EXTRA_ARG")
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fi
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if [ "$ARCH" == "x86_64" ]; then
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#ARM build machines do not have the test data yet.
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BUILD_ARGS+=("--enable_onnx_tests")
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fi
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if [ "$BUILD_DEVICE" == "GPU" ]; then
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SHORT_CUDA_VERSION=$(echo $CUDA_VERSION | sed 's/\([[:digit:]]\+\.[[:digit:]]\+\)\.[[:digit:]]\+/\1/')
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#Enable CUDA and TRT EPs.
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BUILD_ARGS+=("--use_cuda" "--use_tensorrt" "--cuda_version=$SHORT_CUDA_VERSION" "--tensorrt_home=/usr" "--cuda_home=/usr/local/cuda-$SHORT_CUDA_VERSION" "--cudnn_home=/usr/local/cuda-$SHORT_CUDA_VERSION" "--cmake_extra_defines" "CMAKE_CUDA_ARCHITECTURES=75;80;90")
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fi
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if [ "$BUILD_DEVICE" == "NPU" ]; then
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#Enable QNN EP
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BUILD_ARGS+=("--build_shared_lib" "--use_qnn" "--qnn_home=/qnn_sdk")
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fi
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export ONNX_ML=1
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export CMAKE_ARGS="-DONNX_GEN_PB_TYPE_STUBS=ON -DONNX_WERROR=OFF"
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for PYTHON_EXE in "${PYTHON_EXES[@]}"
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do
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rm -rf /build/"$BUILD_CONFIG"
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# that's a workaround for the issue that there's no python3 in the docker image
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# like xnnpack's cmakefile, it uses pythone3 to run a external command
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python3_dir=$(dirname "$PYTHON_EXE")
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${PYTHON_EXE} -m pip install -r /onnxruntime_src/tools/ci_build/github/linux/python/requirements.txt
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PATH=$python3_dir:$PATH ${PYTHON_EXE} /onnxruntime_src/tools/ci_build/build.py "${BUILD_ARGS[@]}"
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cp /build/"$BUILD_CONFIG"/dist/*.whl /build/dist
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done
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if [ "$ENABLE_CACHE" = true ] ; then
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which ccache && ccache -sv && ccache -z
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fi
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