lite/load_and_run/examples/example.sh
#!/bin/bash
OLD_IFS="$IFS"
IFS=$'\n'
TYPICAL_MODEL_DATD="model_source/resnet50_b1_float32_without_data.mge --input \"data:input_data/resnet50_input.npy\""
DEVICE_DESC=""
WORK_DIR_PATH="."
RUN_ARM_DEVICE="false"
RUN_TARGET="diff_model"
ONLY_PREPARE_MODEL="false"
MODEL_PREAPRED="false"
ONLY_BUILD="false"
LAR_BUILT="false"
CLEAN_ALL="false"

RUN_TARGETS=("diff_model")
RUN_TARGETS+=("diff_device")
RUN_TARGETS+=("fast_run")
RUN_TARGETS+=("io")
RUN_TARGETS+=("layout")
RUN_TARGETS+=("optimize")
RUN_TARGETS+=("plugin")
RUN_TARGETS+=("all")


function usage() {
    echo "$0 args1 args2 .."
    echo "available args detail:"
    echo "-p : prepare example model "
    echo "-b : build load_and_run for x86/armv7/arm64 cpu and CUDA"
    echo "-t : set the ssh arm device "
    echo "-w : set the arm device workspace dir"
    echo "-c : clean all"
    echo "-a : run all test"
    echo "-e : set the running target for test (details use \"-e\" to see)"
    echo "-h : show usage"
    exit -1
}


while getopts "pbcahe:w:t:" arg
do
    case $arg in
        t)
            DEVICE_DESC=$OPTARG
            RUN_ARM_DEVICE="true"
            echo "config arm device DEVICE_DESC to ${DEVICE_DESC}"
            ;;
        w)
            WORK_DIR_PATH=$OPTARG
            echo "config arm device WORK_DIR_PATH to ${WORK_DIR_PATH}"
            ;;
        e)
            tmp_target=null
            for target in ${RUN_TARGETS[@]}; do
                if [ "$target" = "$OPTARG" ]; then
                    echo "CONFIG BUILD RUN_TARGET to : $OPTARG"
                    tmp_target=$OPTARG
                    RUN_TARGET=$OPTARG
                    break
                fi
            done
            if [ "$tmp_target" = "null" ]; then
                echo "ERR args for target (-e)"
                echo "available target usage :"
                for target in ${RUN_TARGETS[@]}; do
                    echo "  -e $target"
                done
                exit -1
            fi
            ;;
        h)
            echo "show usage"
            usage
            ;;
        a)
            echo "config RUN_TARGET=all"
            RUN_TARGET="all"
            ;;
        c)
            echo "clean all directory generated by script"
            CLEAN_ALL="true"

            ;;
        b)
            echo "run build"
            ONLY_BUILD="true"
            ;;
        p)
            echo "prepare model and input"
            ONLY_PREPARE_MODEL="true"
            ;;
        ?)
            echo "unkonw argument"
            usage
            ;;
    esac
done


function prepare_model_and_data(){
    rm -rf model_source && mkdir model_source
    # dump mgb model
    python3 script/resnet50_mgb.py -o model_source/resnet50.pkl
    ../dump_with_testcase.py model_source/resnet50.pkl -o model_source/resnet50_with_data.mgb -d "#rand(0, 255)" --no-assert
    
    # prepare simple add model
    python3 script/add_demo.py --dir model_source
    python3 script/conv_demo.py --dir model_source
    
    #generate trt model
    script/gen_trt_model.sh

    #prepare mge model
    python3 script/resnet50_mge.py --dir model_source
    python3 script/resnet50_mge.py  --dir model_source -d uint8
    python3 script/resnet50_mge.py  --dir model_source --inputs "#rand(0,255)"

    #make input_data
    rm -rf input_data && mkdir input_data
    python3 script/mge_input_data.py

    rm -rf tmpdir && mkdir tmpdir
}

function build_lar(){
    # build cpu and cuda version 
     ../../../scripts/cmake-build/host_build.sh -r -t -e load_and_run
    #WARNING:config the cuda environment before compile
    ../../../scripts/cmake-build/host_build.sh  -c -t -e load_and_run
    
    # # build arm version

    ../../../scripts/cmake-build/cross_build_android_arm_inference.sh -r -a arm64-v8a -e load_and_run
    ../../../scripts/cmake-build/cross_build_android_arm_inference.sh -r -a armeabi-v7a -e load_and_run
    

    # link or for test
    ln -s ../../../build_dir/host/MGE_WITH_CUDA_OFF/MGE_INFERENCE_ONLY_OFF/Release//build/lite/load_and_run/load_and_run lar_cpu
    ln -s ../../../build_dir/host/MGE_WITH_CUDA_ON/MGE_INFERENCE_ONLY_OFF/Release//build/lite/load_and_run/load_and_run lar_cuda
    cp ../../../build_dir/android/arm64-v8a/Release/build/lite/load_and_run/load_and_run ./lar_arm64
    cp ../../../build_dir/android/armeabi-v7a/Release/build/lite/load_and_run/load_and_run ./lar_armv7

    
    
}   

function set_arm_device_and_upload(){
    DEVICE_DESC="${1}"
    WORK_DIR_PATH="${2}"
    RUN_ARM_DEVICE="${3}"
    cmd="rsync -aP -zz  ./lar_arm64 ./lar_armv7  model_source/resnet50_b1_float32_without_data.mge input_data/resnet50_input.npy  $DEVICE_DESC:$WORK_DIR_PATH/"
    echo $cmd
    bash -c "$cmd"
}

function test_different_model(){
    CmdArray=("./lar_cpu model_source/resnet50_with_data.mgb")
    CmdArray+=("./lar_cpu model_source/resnet50_b1_float32_with_data.mge")
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD")
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --lite")
    for cmd in ${CmdArray[@]}; do
        echo "$cmd"
        bash -c "$cmd"
    done
}

function test_different_device(){
    #dispatch时，计算任务会加入一个工作队列，由队列统一管理执行 均值 131.278 ms 标准差 15.197ms m_asyc_exec异步执行
    CmdArray=("./lar_cpu $TYPICAL_MODEL_DATD --cpu")
    #dispatch时，计算任务直接执行 均值 131.875 ms 标准差 7.758ms m_asyc_exec同步执行
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --cpu-default")
    #多线程运行 1～8平均运行时间（ms）：129.611, 84.266, 76.963, 55.212, 69.283, 77.338, 58.386, 64.585
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --multithread 4")
    #主线程锁核，其他任务在线程池中的线程上运行 132.614, 83.095, 69.792, 54.452, 48.890, 48.206, 46.386, 53.908
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --multithread-default 4")
    #cpu多线程绑核(x86上绑核影响不大)
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --multithread 2 --multi-thread-core-ids 1,5")

    #xpu 设置为cpu上运行 132.740 ms  comp_node:cpu
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --cpu")
    #xpu 设置为cuda上运行 6.495 ms comp_node:gpu
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --cuda")
    
    for cmd in ${CmdArray[@]}; do
        echo $cmd
         bash -c "$cmd"
    done

function test_fast_run(){

    CmdArray=("./lar_cuda $TYPICAL_MODEL_DATD --fast-run")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --full-run")
    #fast run 搜参  
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --fast-run --fast-run-algo-policy tmpdir/algo_cache_file")

     #fast run 带参执行 
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --fast-run-algo-policy tmpdir/algo_cache_file")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --fast-run  --reproducible")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --fast-run  --fast-run-shared-batch-size 1")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --fast-run --binary-equal-between-batch")

    for cmd in ${CmdArray[@]}; do
        echo $cmd
         bash -c "$cmd"
    done
}

function test_io(){
    rm -rf tmpdir/bin_io_info tmpdir/bin_out_info tmpdir/bin_out_info_cuda tmpdir/io_info.txt
    mkdir tmpdir/bin_io_info tmpdir/bin_out_info tmpdir/bin_io_info_cuda

    CmdArray=("./lar_cpu $TYPICAL_MODEL_DATD")

    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"input_data/add_demo_input.json\"") 
    #! the model must support input with nhwc shape
    CmdArray+=("./lar_cpu model_source/resnet50_b1_int8_without_data.mge --input \"data:input_data/cat.ppm\"") 

    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\"")

    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --io-dump  tmpdir/io_info.txt --iter 1 --warmup-iter 0")
    
    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --io-dump-stdout --iter 1 --warmup-iter 0")
    
    
    
    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --io-dump-stderr --iter 1 --warmup-iter 0")

    #different data in the given directory the name is the var id which is the same with txt-dump information
    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --bin-io-dump tmpdir/bin_io_info --iter 1 --warmup-iter 0")

    CmdArray+=("./lar_cuda model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --bin-io-dump tmpdir/bin_io_info_cuda --iter 1 --warmup-iter 0")
    
   
    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --bin-out-dump tmpdir/bin_out_info --iter 1 --warmup-iter 0")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --copy-to-host")

    for cmd in ${CmdArray[@]}; do
        echo $cmd
         bash -c "$cmd"
    done

    #compare the binary io information
    python3 ../../../imperative/python/megengine/tools/compare_binary_iodump.py tmpdir/bin_io_info tmpdir/bin_io_info_cuda

}

function test_layout_related(){
    # very little speed up
    CmdArray=("./lar_cuda $TYPICAL_MODEL_DATD --enable-nchw4")
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --enable-chwn4")
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --enable-nchw32")
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --enable-nchw64")

    #speed up 
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --enable-nchw88") 
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --cuda --layout-transform cuda")
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --cuda --layout-transform cuda --layout-transform-dump model_source/resnet50_b1_float32_without_data_with_global_layout_trans_cuda.mge")
    CmdArray+=("./lar_cuda model_source/resnet50_b1_float32_without_data_with_global_layout_trans_cuda.mge")

    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --cpu --layout-transform cpu")
    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --cpu --layout-transform cpu --layout-transform-dump model_source/resnet50_b1_float32_without_data_with_global_layout_trans_cpu.mge")
    CmdArray+=("./lar_cpu model_source/resnet50_b1_float32_without_data_with_global_layout_trans_cpu.mge")
    
    for cmd in ${CmdArray[@]}; do
        echo $cmd
         bash -c "$cmd"
    done

if [ ${RUN_ARM_DEVICE} == "true" ] ; then 
    #speed up
    CmdArray=("./lar_arm64 resnet50_b1_float32_without_data.mge --input \"data:resnet50_input.npy\" --cpu --enable-nchw44")

    #speed up
    CmdArray+=("./lar_arm64 resnet50_b1_float32_without_data.mge --input \"data:resnet50_input.npy\" --cpu --enable-nchw44-dot")

    for cmd in ${CmdArray[@]}; do
        echo $cmd
        ssh -t $DEVICE_DESC "unset LD_PRELOAD && cd $WORK_DIR_PATH && LD_LIBRARY_PATH=./ $cmd" 
    done
else
    echo "SET arm device ON : $RUN_ARM_DEVICE"
fi

}

function test_optimize(){
    CmdArray=("./lar_cpu $TYPICAL_MODEL_DATD --enable-fuse-preprocess")
    #warm up speed up
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --enable-fuse-conv-bias-nonlinearity")
    
    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --enable-fuse-conv-bias-with-z")
    
    CmdArray+=("./lar_cuda model_source/trt_conv_demo_with_data.mgb  --tensorrt")
    
    CmdArray+=("./lar_cuda model_source/trt_conv_demo_with_data.mgb  --tensorrt --tensorrt-cache tmpdir/TRT_cache")
    
    CmdArray+=("./lar_cuda model_source/trt_conv_demo_with_data.mgb  --tensorrt-cache tmpdir/TRT_cache")
    

    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --no-sanity-check --record-comp-seq2")

    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --disable_mem_opt")

    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --workspace_limit 10000")

    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --fake-first")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD  --enable_jit ") 

    for cmd in ${CmdArray[@]}; do
        echo $cmd
         bash -c "$cmd"
    done

}

function test_plugin(){
    
    rm -rf tmpdir/staticMemInfoDir tmpdir/staticMemInfoDirLogs
    mkdir tmpdir/staticMemInfoDir

    CmdArray=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --check-dispatch")

    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --check-var-value 5:0")

    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --range 2")

    CmdArray+=("./lar_cpu model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --profile tmpdir/opr_profile.json
                
                ")
    CmdArray+=("./lar_cuda model_source/add_demo_f32_without_data.mge --input \"data:[2,3,4]\" --profile-host tmpdir/opr_profile_host.json")


    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --model-info")

    CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --verbose")

    CmdArray+=("./lar_cpu model_source/resnet50_with_data.mgb --disable-assert-throw")

    # wait gdb attach to given PID
    # CmdArray+=("./lar_cpu $TYPICAL_MODEL_DATD --wait-gdb")

    CmdArray+=("./lar_cuda $TYPICAL_MODEL_DATD --get-static-mem-info tmpdir/staticMemInfoDir")

    for cmd in ${CmdArray[@]}; do
        echo $cmd
         bash -c "$cmd"
    done

    # view the graph with given url (usally: http://localhost:6006/)
    # mkdir tmpdir/staticMemInfoDirLogs &&  python3 ../../../imperative/python/megengine/tools/graph_info_analyze.py -i tmpdir/staticMemInfoDir -o tmpdir/staticMemInfoDirLogs
    # pip3 install tensorboard && tensorboard --logdir tmpdir/staticMemInfoDirLogs
}

function clean(){
    rm -rf tmpdir model_source input_data lar_cpu lar_cuda lar_arm64 lar_armv7

}

function main(){

if [ ${CLEAN_ALL} == "true" ] ; then
    clean
    exit 0
fi

if [ ${ONLY_PREPARE_MODEL} == "true" ] ; then 
    prepare_model_and_data
    MODEL_PREAPRED="true"
    exit 0
fi

if [ ${ONLY_BUILD} == "true" ] ; then 
    build_lar
    LAR_BUILT="true"
    exit 0
fi

if [ ${RUN_ARM_DEVICE} == "true" ] ; then
    set_arm_device_and_upload $DEVICE_DESC "$WORK_DIR_PATH" "true"
fi

if [ ${MODEL_PREAPRED} != "true" ] ; then
    CHECK_MODEL=$(find . -name add_demo_input.json)
    if [ ${CHECK_MODEL} == "" ] ; then
        prepare_model_and_data
        MODEL_PREAPRED="true"
    fi
fi

if [ ${LAR_BUILT} != "true" ] ; then
    CHECK_LAR=$(find . -name lar_armv7)
    if [ ${CHECK_LAR} == "" ] ; then
        build_lar
        LAR_BUILT="true"
    fi
fi

if [ ${RUN_TARGET} == "diff_model" -o ${RUN_TARGET} == "all" ] ; then
    test_different_model
fi

if [ ${RUN_TARGET} == "diff_device" -o ${RUN_TARGET} == "all" ] ; then
   test_different_device
fi

if [ ${RUN_TARGET} == "fast_run" -o ${RUN_TARGET} == "all" ] ; then
    test_fast_run
fi

if [ ${RUN_TARGET} == "io" -o ${RUN_TARGET} == "all" ] ; then
    test_io
fi

if [ ${RUN_TARGET} == "layout" -o ${RUN_TARGET} == "all" ] ; then
    test_layout_related
fi

if [ ${RUN_TARGET} == "optimize" -o ${RUN_TARGET} == "all" ] ; then
    test_optimize
fi

if [ ${RUN_TARGET} == "plugin" -o ${RUN_TARGET} == "all" ] ; then
    test_plugin
fi



}

main
IFS=$OLD_IFS