diff options
Diffstat (limited to 'delegate/BuildGuideNative.md')
| -rw-r--r-- | delegate/BuildGuideNative.md | 20 |
1 files changed, 11 insertions, 9 deletions
diff --git a/delegate/BuildGuideNative.md b/delegate/BuildGuideNative.md index 932c74423a..4aa1af3ee9 100644 --- a/delegate/BuildGuideNative.md +++ b/delegate/BuildGuideNative.md @@ -65,7 +65,7 @@ found [here](https://docs.bazel.build/versions/master/install-compile-source.htm compile with CMake. Depending on your operating system and architecture there might be an easier way. ```bash wget -O cmake-3.16.0.tar.gz https://cmake.org/files/v3.16/cmake-3.16.0.tar.gz -tar -xzf cmake-3.16.0.tar.gz -C $BASEDIR/cmake-3.16.0 +tar -xzf cmake-3.16.0.tar.gz -C $BASEDIR/ # If you have an older CMake, remove installed in order to upgrade yes | sudo apt-get purge cmake @@ -89,8 +89,10 @@ git checkout $(../armnn/scripts/get_tensorflow.sh -p) # Minimum version required Now the build process can be started. When calling "cmake", as below, you can specify a number of build flags. But if you have no need to configure your tensorflow build, you can follow the exact commands below: ```bash -cmake $BASEDIR/tensorflow -cmake --build $BASEDIR/tflite-output # This will be your DTFLITE_LIB_ROOT directory +mkdir build # You are already inside $BASEDIR/tensorflow at this point +cd build +cmake $BASEDIR/tensorflow/tensorflow/lite -DTFLITE_ENABLE_XNNPACK=OFF +cmake --build . # This will be your DTFLITE_LIB_ROOT directory ``` ## Build Flatbuffers @@ -123,7 +125,7 @@ To build the Arm Compute Library on your platform, download the Arm Compute Libr the version you want to use. Build it using `scons`. ```bash -cd $HOME/armnn-devenv +cd $BASEDIR git clone https://review.mlplatform.org/ml/ComputeLibrary cd ComputeLibrary/ git checkout $(../armnn/scripts/get_compute_library.sh -p) # e.g. v21.11 @@ -152,7 +154,7 @@ with the additional cmake arguments shown below cd $BASEDIR/armnn/delegate && mkdir build && cd build cmake .. -DCMAKE_BUILD_TYPE=release # A release build rather than a debug build. -DTENSORFLOW_ROOT=$BASEDIR/tensorflow \ # The root directory where tensorflow can be found. - -DTFLITE_LIB_ROOT=$BASEDIR/tflite-output \ # Directory where tensorflow libraries can be found. + -DTFLITE_LIB_ROOT=$BASEDIR/tensorflow/build \ # Directory where tensorflow libraries can be found. -DFLATBUFFERS_ROOT=$BASEDIR/flatbuffers-1.12.0/install \ # Flatbuffers install directory. -DArmnn_DIR=$BASEDIR/armnn/build \ # Directory where the Arm NN library can be found -DARMNN_SOURCE_DIR=$BASEDIR/armnn # The top directory of the Arm NN repository. @@ -199,7 +201,7 @@ cmake .. -DARMCOMPUTE_ROOT=$BASEDIR/ComputeLibrary \ -DBUILD_UNIT_TESTS=0 \ -DBUILD_ARMNN_TFLITE_DELEGATE=1 \ -DTENSORFLOW_ROOT=$BASEDIR/tensorflow \ - -DTFLITE_LIB_ROOT=$BASEDIR/tflite-output \ + -DTFLITE_LIB_ROOT=$BASEDIR/tensorflow/build \ -DFLATBUFFERS_ROOT=$BASEDIR/flatbuffers-1.12.0/install make ``` @@ -227,11 +229,11 @@ wget https://github.com/ARM-software/ML-zoo/blob/master/models/image_classificat ``` ## Execute the benchmarking tool with the Arm NN delegate +You are already at $BASEDIR/benchmarking from the previous stage. ```bash -cd $BASEDIR/benchmarking LD_LIBRARY_PATH=../armnn/build ./benchmark_model --graph=mobilenet_v2_1.0_224_quantized_1_default_1.tflite --external_delegate_path="../armnn/build/delegate/libarmnnDelegate.so" --external_delegate_options="backends:CpuAcc;logging-severity:info" ``` -The "external_delegate_options" here are specific to the Arm NN delegate. They are used to specify a target Arm NN backend or to enable/disable various options in Arm NN. A full description can be found in the parameters of function [tflite_plugin_create_delegate](namespacetflite.xhtml). +The "external_delegate_options" here are specific to the Arm NN delegate. They are used to specify a target Arm NN backend or to enable/disable various options in Arm NN. A full description can be found in the parameters of function tflite_plugin_create_delegate. # Integrate the Arm NN TfLite Delegate into your project @@ -256,4 +258,4 @@ armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()); For further information on using TfLite Delegates please visit the [tensorflow website](https://www.tensorflow.org/lite/guide) -For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function [tflite_plugin_create_delegate](namespacetflite.xhtml). +For more details of the kind of options you can pass to the Arm NN delegate please check the parameters of function tflite_plugin_create_delegate. |