#!/bin/bash #################################### # build tensorflow-lite sample # #################################### set -x set -e EMSDK_WASM_DIR="$EM_CACHE/wasm" BUILD_SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" OUT_DIR=${BUILD_SCRIPT_DIR}/out TENSORFLOW_DIR="${BUILD_SCRIPT_DIR}/tensorflow" TF_LITE_BUILD_DIR=${TENSORFLOW_DIR}/tensorflow/lite/tools/make WAMR_DIR="${BUILD_SCRIPT_DIR}/../../../product-mini/platforms/linux" function Clear_Before_Exit { [[ -f ${TENSORFLOW_DIR}/tf_lite.patch ]] && rm -f ${TENSORFLOW_DIR}/tf_lite.patch # resume the libc.a under EMSDK_WASM_DIR cd ${EMSDK_WASM_DIR} mv libc.a.bak libc.a } # 1.hack emcc cd ${EMSDK_WASM_DIR} # back up libc.a cp libc.a libc.a.bak # delete some objects in libc.a emar d libc.a open.o emar d libc.a mmap.o emar d libc.a munmap.o emranlib libc.a # 2. build tf-lite cd ${BUILD_SCRIPT_DIR} # 2.1 clone tf repo from Github and checkout to 2303ed commit if [ ! -d "tensorflow" ]; then git clone https://github.com/tensorflow/tensorflow.git fi cd ${TENSORFLOW_DIR} git checkout 2303ed4bdb344a1fc4545658d1df6d9ce20331dd # 2.2 copy the tf-lite.patch to tensorflow_root_dir and apply cd ${TENSORFLOW_DIR} cp ${BUILD_SCRIPT_DIR}/tf_lite.patch . git checkout tensorflow/lite/tools/make/Makefile git checkout tensorflow/lite/tools/make/targets/linux_makefile.inc if [[ $(git apply tf_lite.patch 2>&1) =~ "error" ]]; then echo "git apply patch failed, please check tf-lite related changes..." Clear_Before_Exit exit 0 fi cd ${TF_LITE_BUILD_DIR} # 2.3 download dependencies if [ ! -d "${TF_LITE_BUILD_DIR}/downloads" ]; then source download_dependencies.sh fi # 2.4 build tf-lite target if [ -d "${TF_LITE_BUILD_DIR}/gen" ]; then rm -fr ${TF_LITE_BUILD_DIR}/gen fi make -j 4 -C "${TENSORFLOW_DIR}" -f ${TF_LITE_BUILD_DIR}/Makefile $@ # 2.5 copy /make/gen target files to out/ rm -rf ${OUT_DIR} mkdir ${OUT_DIR} cp -r ${TF_LITE_BUILD_DIR}/gen/linux_x86_64/bin/. ${OUT_DIR}/ # 3. build iwasm with pthread and libc_emcc enable cd ${WAMR_DIR} rm -fr build && mkdir build cd build && cmake .. -DWAMR_BUILD_LIB_PTHREAD=1 -DWAMR_BUILD_LIBC_EMCC=1 make # 4. run tensorflow with iwasm cd ${BUILD_SCRIPT_DIR} # 4.1 download tf-lite model if [ ! -f mobilenet_quant_v1_224.tflite ]; then wget "https://storage.googleapis.com/download.tensorflow.org/models/tflite/mobilenet_v1_224_android_quant_2017_11_08.zip" unzip mobilenet_v1_224_android_quant_2017_11_08.zip fi # 4.2 run tf-lite model with iwasm echo "---> run tensorflow benchmark model with iwasm" ${WAMR_DIR}/build/iwasm --heap-size=10475860 \ ${OUT_DIR}/benchmark_model.wasm \ --graph=mobilenet_quant_v1_224.tflite --max_secs=300 Clear_Before_Exit