!10995 [MS][LITE] separate models for process only and models with multiple inputs in the entrance guard

From: @probiotics_53
Reviewed-by: 
Signed-off-by:

mindspore/lite/test/models_with_several_inputs_or_without_outputs.cfg → mindspore/lite/test/models_for_process_only.cfg

@@ -1,7 +1,6 @@
 lite-model_arbitrary-image-stylization-inceptionv3_dr_transfer_1.tflite
 lite-model_arbitrary-image-stylization-inceptionv3_int8_transfer_1.tflite
-lite-model_arbitrary-image-stylization-inceptionv3_fp16_transfer_1.tflite;2
-# lite-model_arbitrary-image-stylization-inceptionv3-dynamic-shapes_dr_transfer_1.tflite # has nan input for rsqrt
+lite-model_arbitrary-image-stylization-inceptionv3-dynamic-shapes_dr_transfer_1.tflite;2;1,1,1,100:1,64,64,3
 lite-model_cartoongan_dr_1.tflite
 mindspore_efficientnet_b0.mindir
 mindspore_efficientnet_b4minus.mindir
@@ -14,10 +13,8 @@ lite-model_deeplabv3-mobilenetv2-ade20k_1_default_1.tflite
 lite-model_deeplabv3-mobilenetv2_dm05-int8_1_default_1.tflite
 lite-model_deeplabv3-mobilenetv3-cityscapes_1_default_1.tflite
 lite-model_east-text-detector_dr_1.tflite
-magenta_arbitrary-image-stylization-v1-256_fp16_transfer_1.tflite;2
 magenta_arbitrary-image-stylization-v1-256_int8_transfer_1.tflite
 magenta_arbitrary-image-stylization-v1-256_int8_prediction_1.tflite
-# albert_lite_base_squadv1_1.tflite;3 # input need in range [0,2)
 efficientnet_lite0_int8_2.tflite
 efficientnet_lite1_int8_2.tflite
 efficientnet_lite2_int8_2.tflite
@@ -26,14 +23,8 @@ efficientnet_lite4_int8_2.tflite
 mtk_transformer_encoder.tflite
 mtk_transformer_decoder_joint.tflite
 ml_ei_facedetection.onnx
-# mobilebert_1_default_1.tflite;3  # input need in range [0,2)
 quant_aware_bank_card_detection_inception.onnx
 quant_aware_bank_card_recognition_fcny.onnx
 quant_aware_identify_card_detect.onnx
-porseg_tmp.onnx;2
-ml_video_edit_img_segment_adaptise.pb;2
-ml_video_edit_img_segment_adaptise_pb2tflite.tflite;2
-ml_video_edit_video_segment_gauss_adaptis_part2.pb;2
-ml_video_edit_video_segment_gauss_adaptis_part2_pb2tflite.tflite;2
 tiny-yolov3-11.onnx;2;1,416,416,3:1,2
 ml_video_edit_person_divison_pic;2

mindspore/lite/test/models_onnx_fp16.cfg

@@ -22,10 +22,10 @@ residual_distill_bs_32.onnx 30
 ml_face_3d.onnx 2
 gts_version-RFB-320_simplified.onnx 3
 mnist-8.onnx 10
-#crnn_lite_lstm_v2.onnx 0.1
-#psenet_lite_mbv2.onnx 0.1
-#super-resolution-10.onnx 1
-#tinyyolov2-8.onnx 0.3
+crnn_lite_lstm_v2.onnx;32,32,32,1 0.3
+psenet_lite_mbv2.onnx;1,32,32,3 0.6
+super-resolution-10.onnx;1,224,224,1 4.5
+tinyyolov2-8.onnx;1,416,416,3 5.5
 ml_2012_ocr_cn.onnx 200
 #ml_2012_ocr_cn_noLSTM.onnx 1
 candy-9.onnx 5

mindspore/lite/test/models_with_multiple_inputs.cfg

@@ -0,0 +1,10 @@
+lite-model_arbitrary-image-stylization-inceptionv3_fp16_transfer_1.tflite;2
+magenta_arbitrary-image-stylization-v1-256_fp16_transfer_1.tflite;2
+# albert_lite_base_squadv1_1.tflite;3
+# mobilebert_1_default_1.tflite;3
+porseg_tmp.onnx;2
+ml_video_edit_img_segment_adaptise.pb;2
+ml_video_edit_img_segment_adaptise_pb2tflite.tflite;2
+ml_video_edit_video_segment_gauss_adaptis_part2.pb;2
+ml_video_edit_video_segment_gauss_adaptis_part2_pb2tflite.tflite;2
+decoder.onnx;2;1,7,512:1,7

mindspore/lite/test/run_benchmark_nets.sh

@@ -179,7 +179,8 @@ function Run_Converter() {
         if [[ $fp16_line_info == \#* ]]; then
           continue
         fi
-        model_name=`echo ${fp16_line_info}|awk -F ' ' '{print $1}'`
+        model_info=`echo ${fp16_line_info}|awk -F ' ' '{print $1}'`
+        model_name=${model_info%%;*}
         echo 'cp '${ms_models_path}'/'${model_name}'.ms' ${ms_models_path}'/'${model_name}'.fp16.ms'
         cp ${ms_models_path}/${model_name}.ms ${ms_models_path}/${model_name}.fp16.ms
         if [ $? = 0 ]; then
@@ -279,7 +280,42 @@ function Run_Converter() {
         fi
     done < ${models_mindspore_mixbit_config}
 
-    # Convert models which has several inputs or does not need to be cared about the accuracy:
+    # Convert models which has multiple inputs:
+    while read line; do
+        if [[ $line == \#* ]]; then
+          continue
+        fi
+        model_name=${line%%;*}
+        model_type=${model_name##*.}
+        case $model_type in
+          pb)
+            model_fmk="TF"
+            ;;
+          tflite)
+            model_fmk="TFLITE"
+            ;;
+          caffemodel)
+            model_name=${model_name%.*}
+            model_fmk="CAFFE"
+            ;;
+          onnx)
+            model_fmk="ONNX"
+            ;;
+          mindir)
+            model_fmk="MINDIR"
+            ;;
+        esac
+        echo ${model_name} >> "${run_converter_log_file}"
+        echo './converter_lite  --fmk='${model_fmk}' --modelFile='${models_path}'/'${model_name}' --outputFile='${ms_models_path}'/'${model_name} >> "${run_converter_log_file}"
+        ./converter_lite  --fmk=${model_fmk} --modelFile=${models_path}/${model_name} --outputFile=${ms_models_path}/${model_name}
+        if [ $? = 0 ]; then
+            converter_result='converter '${model_type}' '${model_name}' pass';echo ${converter_result} >> ${run_converter_result_file}
+        else
+            converter_result='converter '${model_type}' '${model_name}' failed';echo ${converter_result} >> ${run_converter_result_file};return 1
+        fi
+    done < ${models_with_multiple_inputs_config}
+
+    # Convert models which does not need to be cared about the accuracy:
     while read line; do
         if [[ $line == \#* ]]; then
           continue
@@ -318,7 +354,7 @@ function Run_Converter() {
         else
             converter_result='converter '${model_type}' '${model_name}' failed';echo ${converter_result} >> ${run_converter_result_file};return 1
         fi
-    done < ${models_only_for_process_config}
+    done < ${models_for_process_only_config}
 }
 
 # Run on x86 platform:
@@ -592,7 +628,7 @@ function Run_x86() {
         fi
     done < ${models_mindspore_mixbit_config}
 
-    # Run converted models which has several inputs or does not need to be cared about the accuracy:
+    # Run converted models which has multiple inputs:
     while read line; do
         if [[ $line == \#* ]]; then
           continue
@@ -603,31 +639,51 @@ function Run_x86() {
         input_files=''
         output_file=''
         data_path="/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/"
-        if [[ -z "$input_num" || $input_num == 1 ]] && [ -e ${data_path}'input/'${model_name}'.ms.bin' ]; then
-          input_files=${data_path}'input/'$model_name'.ms.bin'
-        elif [[ ! -z "$input_num" && $input_num -gt 1 ]]; then
-          for i in $(seq 1 $input_num)
-          do
-            input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
-          done
+        for i in $(seq 1 $input_num)
+        do
+          input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
+        done
+        output_file=${data_path}'output/'${model_name}'.ms.out'
+        if [[ ${model_name##*.} == "caffemodel" ]]; then
+          model_name=${model_name%.*}
         fi
-        if [ -e ${data_path}'output/'${model_name}'.ms.out' ]; then
-          output_file=${data_path}'output/'${model_name}'.ms.out'
+        echo ${model_name} >> "${run_x86_log_file}"
+        echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-inference-linux-x64' >> "{run_x86_log_file}"
+        cd ${x86_path}/mindspore-lite-${version}-inference-linux-x64 || return 1
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile='${output_file} >> "${run_x86_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=${output_file} >> "${run_x86_log_file}"
+        if [ $? = 0 ]; then
+            run_result='x86: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
+        else
+            run_result='x86: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
+    done < ${models_with_multiple_inputs_config}
+
+    # Run converted models which does not need to be cared about the accuracy:
+    while read line; do
+        if [[ $line == \#* ]]; then
+          continue
+        fi
+        model_name=`echo ${line} | awk -F ';' '{print $1}'`
+        input_num=`echo ${line} | awk -F ';' '{print $2}'`
+        input_shapes=`echo ${line} | awk -F ';' '{print $3}'`
+        input_files=''
+        output_file=''
+        data_path="/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/"
         if [[ ${model_name##*.} == "caffemodel" ]]; then
           model_name=${model_name%.*}
         fi
         echo ${model_name} >> "${run_x86_log_file}"
         echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-inference-linux-x64' >> "{run_x86_log_file}"
         cd ${x86_path}/mindspore-lite-${version}-inference-linux-x64 || return 1
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile='${output_file}' --loopCount=1 --warmUpLoopCount=0' >> "${run_x86_log_file}"
-        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=${output_file} --loopCount=1 --warmUpLoopCount=0 >> "${run_x86_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inputShapes='${input_shapes}' --loopCount=2 --warmUpLoopCount=0' >> "${run_x86_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inputShapes=${input_shapes} --loopCount=2 --warmUpLoopCount=0 >> "${run_x86_log_file}"
         if [ $? = 0 ]; then
             run_result='x86: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
         else
             run_result='x86: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
-    done < ${models_only_for_process_config}
+    done < ${models_for_process_only_config}
 }
 
 # Run on x86 sse platform:
@@ -865,7 +921,7 @@ function Run_x86_sse() {
         fi
     done < ${models_mindspore_mixbit_config}
 
-    # Run converted models which has several inputs or does not need to be cared about the accuracy:
+    # Run converted models with multiple inputs:
     while read line; do
         model_name=${line%%;*}
         if [[ $model_name == \#* ]]; then
@@ -877,31 +933,49 @@ function Run_x86_sse() {
         input_files=''
         output_file=''
         data_path="/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/"
-        if [[ -z "$input_num" || $input_num == 1 ]] && [ -e ${data_path}'input/'${model_name}'.ms.bin' ]; then
-          input_files=${data_path}'input/'$model_name'.ms.bin'
-        elif [[ ! -z "$input_num" && $input_num -gt 1 ]]; then
-          for i in $(seq 1 $input_num)
-          do
-            input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
-          done
+        for i in $(seq 1 $input_num)
+        do
+          input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
+        done
+        output_file=${data_path}'output/'${model_name}'.ms.out'
+        if [[ ${model_name##*.} == "caffemodel" ]]; then
+          model_name=${model_name%.*}
         fi
-        if [ -e ${data_path}'output/'${model_name}'.ms.out' ]; then
-          output_file=${data_path}'output/'${model_name}'.ms.out'
+        echo ${model_name} >> "${run_x86_sse_log_file}"
+        echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-inference-linux-x64-sse' >> "{run_x86_sse_log_file}"
+        cd ${x86_path}/mindspore-lite-${version}-inference-linux-x64-sse || return 1
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile='${output_file} >> "${run_x86_sse_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=${output_file} >> "${run_x86_sse_log_file}"
+        if [ $? = 0 ]; then
+            run_result='x86_sse: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
+        else
+            run_result='x86_sse: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
+        fi
+    done < ${models_with_multiple_inputs_config}
+
+    # Run converted models which does not need to be cared about the accuracy:
+    while read line; do
+        model_name=${line%%;*}
+        if [[ $model_name == \#* ]]; then
+          continue
         fi
+        model_name=`echo ${line} | awk -F ';' '{print $1}'`
+        input_num=`echo ${line} | awk -F ';' '{print $2}'`
+        input_shapes=`echo ${line} | awk -F ';' '{print $3}'`
         if [[ ${model_name##*.} == "caffemodel" ]]; then
           model_name=${model_name%.*}
         fi
         echo ${model_name} >> "${run_x86_sse_log_file}"
         echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-inference-linux-x64-sse' >> "{run_x86_sse_log_file}"
         cd ${x86_path}/mindspore-lite-${version}-inference-linux-x64-sse || return 1
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile='${output_file}' --loopCount=1 --warmUpLoopCount=0' >> "${run_x86_sse_log_file}"
-        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=${output_file} --loopCount=1 --warmUpLoopCount=0 >> "${run_x86_sse_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inputShapes='${input_shapes}' --loopCount=2 --warmUpLoopCount=0' >> "${run_x86_sse_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inputShapes=${input_shapes} --loopCount=2 --warmUpLoopCount=0 >> "${run_x86_sse_log_file}"
         if [ $? = 0 ]; then
             run_result='x86_sse: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
         else
             run_result='x86_sse: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
-    done < ${models_only_for_process_config}
+    done < ${models_for_process_only_config}
 }
 
 # Run on x86 avx platform:
@@ -1139,7 +1213,7 @@ function Run_x86_avx() {
         fi
     done < ${models_mindspore_mixbit_config}
 
-    # Run converted models which has several inputs or does not need to be cared about the accuracy:
+    # Run converted models which has multiple inputs:
     while read line; do
         model_name=${line%%;*}
         if [[ $model_name == \#* ]]; then
@@ -1151,31 +1225,49 @@ function Run_x86_avx() {
         input_files=''
         output_file=''
         data_path="/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/"
-        if [[ -z "$input_num" || $input_num == 1 ]] && [ -e ${data_path}'input/'${model_name}'.ms.bin' ]; then
-          input_files=${data_path}'input/'$model_name'.ms.bin'
-        elif [[ ! -z "$input_num" && $input_num -gt 1 ]]; then
-          for i in $(seq 1 $input_num)
-          do
-            input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
-          done
+        for i in $(seq 1 $input_num)
+        do
+          input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
+        done
+        output_file=${data_path}'output/'${model_name}'.ms.out'
+        if [[ ${model_name##*.} == "caffemodel" ]]; then
+          model_name=${model_name%.*}
+        fi
+        echo ${model_name} >> "${run_x86_avx_log_file}"
+        echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-inference-linux-x64-avx' >> "{run_x86_avx_log_file}"
+        cd ${x86_path}/mindspore-lite-${version}-inference-linux-x64-avx || return 1
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile='${output_file} >> "${run_x86_avx_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=${output_file} >> "${run_x86_avx_log_file}"
+        if [ $? = 0 ]; then
+            run_result='x86_avx: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
+        else
+            run_result='x86_avx: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
-        if [ -e ${data_path}'output/'${model_name}'.ms.out' ]; then
-          output_file=${data_path}'output/'${model_name}'.ms.out'
+    done < ${models_with_multiple_inputs_config}
+
+    # Run converted models which does not need to be cared about the accuracy:
+    while read line; do
+        model_name=${line%%;*}
+        if [[ $model_name == \#* ]]; then
+          continue
         fi
+        model_name=`echo ${line} | awk -F ';' '{print $1}'`
+        input_num=`echo ${line} | awk -F ';' '{print $2}'`
+        input_shapes=`echo ${line} | awk -F ';' '{print $3}'`
         if [[ ${model_name##*.} == "caffemodel" ]]; then
           model_name=${model_name%.*}
         fi
         echo ${model_name} >> "${run_x86_avx_log_file}"
         echo 'cd  '${x86_path}'/mindspore-lite-'${version}'-inference-linux-x64-avx' >> "{run_x86_avx_log_file}"
         cd ${x86_path}/mindspore-lite-${version}-inference-linux-x64-avx || return 1
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile='${output_file}' --loopCount=1 --warmUpLoopCount=0' >> "${run_x86_avx_log_file}"
-        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=${output_file} --loopCount=1 --warmUpLoopCount=0 >> "${run_x86_avx_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inputShapes='${input_shapes}' --loopCount=2 --warmUpLoopCount=0' >> "${run_x86_avx_log_file}"
+        export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:./lib:./third_party/libjpeg-turbo/lib:./third_party/opencv/lib;./benchmark/benchmark --modelFile=${ms_models_path}/${model_name}.ms --inputShapes=${input_shapes} --loopCount=2 --warmUpLoopCount=0 >> "${run_x86_avx_log_file}"
         if [ $? = 0 ]; then
             run_result='x86_avx: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
         else
             run_result='x86_avx: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
-    done < ${models_only_for_process_config}
+    done < ${models_for_process_only_config}
 }
 
 # Run on arm64 platform:
@@ -1439,14 +1531,17 @@ function Run_arm64() {
         if [[ $fp16_line_info == \#* ]]; then
           continue
         fi
-        model_name=`echo ${fp16_line_info}|awk -F ' ' '{print $1}'`
+        model_info=`echo ${fp16_line_info}|awk -F ' ' '{print $1}'`
         accuracy_limit=`echo ${fp16_line_info}|awk -F ' ' '{print $2}'`
+        model_name=${model_info%%;*}
+        length=${#model_name}
+        input_shapes=${model_info:length+1}
         echo "---------------------------------------------------------" >> "${run_arm64_log_file}"
         echo "fp16 run: ${model_name}, accuracy limit:${accuracy_limit}" >> "${run_arm64_log_file}"
 
         echo 'cd  /data/local/tmp/benchmark_test' > adb_run_cmd.txt
         echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test' >> adb_run_cmd.txt
-        echo './benchmark --modelFile='${model_name}'.fp16.ms --inDataFile=/data/local/tmp/input_output/input/'${model_name}'.ms.bin --benchmarkDataFile=/data/local/tmp/input_output/output/'${model_name}'.ms.out --enableFp16=true --accuracyThreshold='${accuracy_limit} >> adb_run_cmd.txt
+        echo './benchmark --modelFile='${model_name}'.fp16.ms --inDataFile=/data/local/tmp/input_output/input/'${model_name}'.ms.bin --benchmarkDataFile=/data/local/tmp/input_output/output/'${model_name}'.ms.out --enableFp16=true --accuracyThreshold='${accuracy_limit} ' --inputShapes='${input_shapes} >> adb_run_cmd.txt
 
         cat adb_run_cmd.txt >> "${run_arm64_log_file}"
         adb -s ${device_id} shell < adb_run_cmd.txt >> "${run_arm64_log_file}"
@@ -1695,7 +1790,7 @@ function Run_arm64() {
         fi
     done < ${models_npu_config}
 
-    # Run converted models which has several inputs or does not need to be cared about the accuracy:
+    # Run converted models which has multiple inputs:
     while read line; do
         model_name=${line%%;*}
         if [[ $model_name == \#* ]]; then
@@ -1707,18 +1802,11 @@ function Run_arm64() {
         input_files=''
         output_file=''
         data_path="/data/local/tmp/input_output/"
-        model_x86_path="/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/"
-        if [[ -z "$input_num" || $input_num == 1 ]] && [ -e ${model_x86_path}'input/'${model_name}'.ms.bin' ]; then
-          input_files=${data_path}'input/'$model_name'.ms.bin'
-        elif [[ ! -z "$input_num" && $input_num -gt 1 ]]; then
-          for i in $(seq 1 $input_num)
-          do
-            input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
-          done
-        fi
-        if [ -e ${model_x86_path}'output/'${model_name}'.ms.out' ]; then
-          output_file=${data_path}'output/'${model_name}'.ms.out'
-        fi
+        for i in $(seq 1 $input_num)
+        do
+          input_files=$input_files${data_path}'input/'$model_name'.ms.bin_'$i','
+        done
+        output_file=${data_path}'output/'${model_name}'.ms.out'
         if [[ ${model_name##*.} == "caffemodel" ]]; then
           model_name=${model_name%.*}
         fi
@@ -1732,7 +1820,31 @@ function Run_arm64() {
         else
             run_result='arm64: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
-    done < ${models_only_for_process_config}
+    done < ${models_with_multiple_inputs_config}
+
+    # Run converted models which does not need to be cared about the accuracy:
+    while read line; do
+        model_name=${line%%;*}
+        if [[ $model_name == \#* ]]; then
+          continue
+        fi
+        model_name=`echo ${line} | awk -F ';' '{print $1}'`
+        input_num=`echo ${line} | awk -F ';' '{print $2}'`
+        input_shapes=`echo ${line} | awk -F ';' '{print $3}'`
+        if [[ ${model_name##*.} == "caffemodel" ]]; then
+          model_name=${model_name%.*}
+        fi
+        echo ${model_name} >> "${run_arm64_log_file}"
+        echo 'cd  /data/local/tmp/benchmark_test' > adb_run_cmd.txt
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inputShapes='${input_shapes}' --warmUpLoopCount=0 --loopCount=2' >> "${run_arm64_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inputShapes='${input_shapes}' --warmUpLoopCount=0 --loopCount=2' >> adb_run_cmd.txt
+        adb -s ${device_id} shell < adb_run_cmd.txt >> "${run_arm64_log_file}"
+        if [ $? = 0 ]; then
+            run_result='arm64: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
+        else
+            run_result='arm64: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
+        fi
+    done < ${models_for_process_only_config}
 }
 
 # Run on arm32 platform:
@@ -1876,7 +1988,8 @@ models_mindspore_weightquant_config=${basepath}/models_mindspore_weightquant.cfg
 models_arm32_config=${basepath}/models_arm32.cfg
 models_npu_config=${basepath}/models_npu.cfg
 models_compatibility_config=${basepath}/models_compatibility.cfg
-models_only_for_process_config=${basepath}/models_with_several_inputs_or_without_outputs.cfg
+models_with_multiple_inputs_config=${basepath}/models_with_multiple_inputs.cfg
+models_for_process_only_config=${basepath}/models_for_process_only.cfg
 
 ms_models_path=${basepath}/ms_models