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Added support to build onnxruntime with ACL (#3586)

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* Added support to build onnxruntime with ACL

* Added ACL build instructions
This commit is contained in:
Prabhat 2020-04-20 13:35:28 +05:30 committed by GitHub
parent 75426a3091
commit 381fee47ab
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GPG key ID: 4AEE18F83AFDEB23
5 changed files with 48 additions and 6 deletions
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21
BUILD.md
View file

@ -418,6 +418,27 @@ onnxruntime_perf_test
onnxruntime_test_all
```
#### Build Instructions(Jetson Nano)
1. Build ACL Library (skip if already built)
```
cd ~
git clone https://github.com/Arm-software/ComputeLibrary.git
cd ComputeLibrary
sudo apt install scons
sudo apt install g++-arm-linux-gnueabihf
scons -j8 arch=arm64-v8a Werror=1 debug=0 asserts=0 neon=1 opencl=1 examples=1 build=native
```
2. Set environment variables to set include directory and shared object library path.
```
export CPATH=~/ComputeLibrary/include/:~/ComputeLibrary/
export LD_LIBRARY_PATH=~/ComputeLibrary/build/
```
3. Build onnxruntime with --use_acl flag
```
./build.sh --use_acl
```
---
## Options

2
cmake/CMakeLists.txt
View file

@ -487,7 +487,7 @@ if (onnxruntime_USE_ACL OR onnxruntime_USE_ACL_1902 OR onnxruntime_USE_ACL_1905
endif()
endif()
list(APPEND onnxruntime_EXTERNAL_LIBRARIES arm_compute acl arm_compute_graph arm_compute_core)
list(APPEND onnxruntime_EXTERNAL_LIBRARIES arm_compute arm_compute_graph arm_compute_core)
endif()
# MKLML

1
cmake/onnxruntime_providers.cmake
View file

@ -482,6 +482,7 @@ if (onnxruntime_USE_ACL)
source_group(TREE ${ONNXRUNTIME_ROOT}/core FILES ${onnxruntime_providers_acl_cc_srcs})
add_library(onnxruntime_providers_acl ${onnxruntime_providers_acl_cc_srcs})
onnxruntime_add_include_to_target(onnxruntime_providers_acl onnxruntime_common onnxruntime_framework onnx onnx_proto protobuf::libprotobuf)
target_link_libraries(onnxruntime_providers_acl -L$ENV{LD_LIBRARY_PATH})
add_dependencies(onnxruntime_providers_acl ${onnxruntime_EXTERNAL_DEPENDENCIES})
set_target_properties(onnxruntime_providers_acl PROPERTIES FOLDER "ONNXRuntime")
target_include_directories(onnxruntime_providers_acl PRIVATE ${ONNXRUNTIME_ROOT} ${eigen_INCLUDE_DIRS} ${ACL_INCLUDE_DIR})

2
onnxruntime/core/providers/acl/nn/conv.cc
View file

@ -208,7 +208,7 @@ Status Conv<T>::Compute(OpKernelContext* context) const {
if(optimizable) {
//optimized depthwise convolution
#if defined(ACL_1902) || defined(ACL_1905)
auto layer = std::make_shared<arm_compute::NEDepthwiseConvolutionLayer3x3>();
auto layer = std::make_shared<arm_compute::NEDepthwiseConvolutionLayer>();
#endif
#ifdef ACL_1908
auto layer = std::make_shared<arm_compute::NEDepthwiseConvolutionLayerOptimized>();

28
tools/ci_build/build.py
View file

@ -293,6 +293,10 @@ def parse_arguments():
parser.add_argument(
"--enable_lto", action='store_true',
help="Enable Link Time Optimization")
parser.add_argument(
"--use_acl", nargs="?", const="ACL_1905",
choices=["ACL_1902", "ACL_1905", "ACL_1908"],
help="Build with ACL for ARM architectures.")
return parser.parse_args()
@ -479,7 +483,7 @@ def generate_build_tree(cmake_path, source_dir, build_dir, cuda_home,
"OFF" if args.skip_winml_tests else "ON"),
"-Donnxruntime_GENERATE_TEST_REPORTS=ON",
"-Donnxruntime_DEV_MODE=" + (
"OFF" if args.android else "ON"),
"OFF" if args.android or args.use_acl else "ON"),
"-DPYTHON_EXECUTABLE=" + sys.executable,
"-Donnxruntime_USE_CUDA=" + ("ON" if args.use_cuda else "OFF"),
"-Donnxruntime_CUDNN_HOME=" + (cudnn_home if args.use_cuda else ""),
@ -551,6 +555,13 @@ def generate_build_tree(cmake_path, source_dir, build_dir, cuda_home,
"-Donnxruntime_USE_TELEMETRY=" + (
"ON" if args.use_telemetry else "OFF"),
"-Donnxruntime_ENABLE_LTO=" + ("ON" if args.enable_lto else "OFF"),
"-Donnxruntime_USE_ACL=" + ("ON" if args.use_acl else "OFF"),
"-Donnxruntime_USE_ACL_1902=" + (
"ON" if args.use_acl == "ACL_1902" else "OFF"),
"-Donnxruntime_USE_ACL_1905=" + (
"ON" if args.use_acl == "ACL_1905" else "OFF"),
"-Donnxruntime_USE_ACL_1908=" + (
"ON" if args.use_acl == "ACL_1908" else "OFF"),
]
if args.winml_root_namespace_override:
@ -1165,9 +1176,10 @@ def nuphar_run_python_tests(build_dir, configs):
cwd=cwd, dll_path=dll_path)
def build_python_wheel(source_dir, build_dir, configs, use_cuda, use_ngraph,
use_dnnl, use_tensorrt, use_openvino, use_nuphar,
wheel_name_suffix, nightly_build=False):
def build_python_wheel(
source_dir, build_dir, configs, use_cuda, use_ngraph, use_dnnl,
use_tensorrt, use_openvino, use_nuphar, wheel_name_suffix, use_acl,
nightly_build=False):
for config in configs:
cwd = get_config_build_dir(build_dir, config)
if is_windows():
@ -1190,6 +1202,8 @@ def build_python_wheel(source_dir, build_dir, configs, use_cuda, use_ngraph,
args.append('--use_nuphar')
if wheel_name_suffix:
args.append('--wheel_name_suffix={}'.format(wheel_name_suffix))
elif use_acl:
args.append('--use_acl')
run_subprocess(args, cwd=cwd)
@ -1483,6 +1497,11 @@ def main():
build_dir, configs, onnx_test_data_dir, 'dml',
args.enable_multi_device_test, False, 1)
if args.use_acl:
run_onnx_tests(
build_dir, configs, onnx_test_data_dir, 'acl',
args.enable_multi_device_test, False, 1, 1)
# Run some models are disabled to keep memory utilization
# under control.
if args.use_dnnl:
@ -1516,6 +1535,7 @@ def main():
args.use_openvino,
args.use_nuphar,
args.wheel_name_suffix,
args.use_acl,
nightly_build=nightly_build,
)