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Merged
Prabhat Roy (prabhat00155) merged 3 commits into from
Apr 20, 2020
Merged

Added support to build onnxruntime with ACL #3586

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48e6cad
Added support to build onnxruntime with ACL
Apr 18, 2020
7625a86
Added ACL build instructions
Apr 18, 2020
ce5d6d5
Resolved merge conflicts
Apr 19, 2020
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21 changes: 21 additions & 0 deletions BUILD.md
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Expand Up @@ -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

@prabhat00155 Prabhat Roy (prabhat00155) Apr 19, 2020

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This is an example for someone who wants to build ACL. If they have a pre-built version, they may use it as mentioned above.

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
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2 changes: 1 addition & 1 deletion cmake/CMakeLists.txt
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Expand Up @@ -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
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1 change: 1 addition & 0 deletions cmake/onnxruntime_providers.cmake
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Expand Up @@ -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})

@jywu-mysoft George Wu (jywu-mysoft) Apr 20, 2020

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why using LD_LIBRARY_PATH? that's normally used at run time.

@prabhat00155 Prabhat Roy (prabhat00155) Apr 20, 2020 •
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We need to link the ACL so files. Without this build fails with this error: "Unable to load arm_compute arm_compute_graph arm_compute_core".

@jywu-mysoft George Wu (jywu-mysoft) Apr 22, 2020

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My point was that LD_LIBRARY_PATH should not be used for that purpose.
We should allow user to specify the location of ACL libraries as build option.

@prabhat00155 Prabhat Roy (prabhat00155) Apr 24, 2020

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Even if you make user pass ACL library location, the user will still need to set LD_LIBRARY_PATH in order to use onnxruntime_perf_test otherwise get this error: "error while loading shared libraries: libarm_compute.so: cannot open shared object file: No such file or directory."

@jywu-mysoft George Wu (jywu-mysoft) Apr 25, 2020 •
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yes, but LD_LIBRARY_PATH is used at runtime. it's not meant to be used during build time (which is what the cmake files are for)
at build time, the ACL install location can be anywhere and not set in the user's LD_LIBRARY_PATH
the binary could then be deployed to a target where LD_LIBRARY_PATH would need to be set at run time.
besides, LD_LIBRARY_PATH env variable is specific to Linux/Unix.
Many other EP's have dependency on other libs. (e.g. CUDA, OpenVINO) etc.
But you can grep through all our cmake files and you won't find a single reference to 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})
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2 changes: 1 addition & 1 deletion onnxruntime/core/providers/acl/nn/conv.cc
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Expand Up @@ -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>();

@mcaraman Mike Caraman (mcaraman) Apr 22, 2020

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What is the reason of this change? NEDepthwiseConvolutionLayer3x3 is an optimized version for depthwise 3x3 which increases the performance significantly for mobilenets and other models.

@jywu-mysoft George Wu (jywu-mysoft) Apr 22, 2020 •
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I believe it was accidental.
Prabhat Roy (@prabhat00155) was trying to incorporate some of the changes from #2511
but accidentally reverted changes from
#2774
Prabhat Roy (@prabhat00155) can you please revert this change? thanks.

@prabhat00155 Prabhat Roy (prabhat00155) Apr 23, 2020

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I was getting error(NEDepthwiseConvolutionLayer3x3 not defined) and had to make this change to build. I'll update my ACL repo and retry.

@prabhat00155 Prabhat Roy (prabhat00155) Apr 23, 2020

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Got the issue, this should be only used for ACL_1902. I'll create a new PR to use NEDepthwiseConvolutionLayer3x3 and fix the error.

@prabhat00155 Prabhat Roy (prabhat00155) Apr 23, 2020

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#3664

#endif
#ifdef ACL_1908
auto layer = std::make_shared<arm_compute::NEDepthwiseConvolutionLayerOptimized>();
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28 changes: 24 additions & 4 deletions tools/ci_build/build.py
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Expand Up @@ -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()


Expand Down Expand Up @@ -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 ""),
Expand Down Expand Up @@ -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:
Expand Down Expand Up @@ -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():
Expand All @@ -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)

Expand Down Expand Up @@ -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:
Expand Down Expand Up @@ -1516,6 +1535,7 @@ def main():
args.use_openvino,
args.use_nuphar,
args.wheel_name_suffix,
args.use_acl,
nightly_build=nightly_build,
)

Expand Down