add models to the entrance guard and modify tf script

mindspore/lite/test/models_caffe.cfg

@@ -108,4 +108,11 @@ ml_hand_3d_regression
 ml_ARengine23_bodypose
 ml_ocr_bank_card_detection_inception
 ml_ocr_bank_card_recognition_fcny
-hiai_cv_aestheticsEngineModel_osp
+hiai_cv_aestheticsEngineModel_osp
+bank_card_recognition_fcny
+bank_card_detection_inception
+ml_ocr_identify_card_fcny
+ml_ocr_identify_card_detect
+identify_card_detect
+ml_2012_ocr_rec_caffe
+ml_2012_ocr_detection_caffe

mindspore/lite/test/models_caffe_fp16.cfg

@@ -103,4 +103,12 @@ ml_hand_3d_regression 3
 ml_ARengine23_bodypose 56
 ml_ocr_bank_card_detection_inception 20
 ml_ocr_bank_card_recognition_fcny 0.5
-hiai_cv_aestheticsEngineModel_osp 1.1
+hiai_cv_aestheticsEngineModel_osp 1.5
+ml_face_hat 0.5
+bank_card_recognition_fcny 17
+bank_card_detection_inception 12
+ml_ocr_identify_card_fcny 0.5
+ml_ocr_identify_card_detect 2
+identify_card_detect 0.5
+ml_2012_ocr_detection_caffe 1
+ml_2012_ocr_rec_caffe 0.5

mindspore/lite/test/models_onnx.cfg

@@ -71,3 +71,4 @@ mtk_detect_mbv1_640_480_nopostprocess_simplified_onnx.onnx;1,480,640,3
 mtk_face_features_v2.onnx;1,256,192,3
 mtk_face_recognition_v3.onnx
 mtk_face_recognition_v2.onnx
+ml_2012_ocr_detection.onnx

mindspore/lite/test/models_onnx_fp16.cfg

@@ -60,14 +60,15 @@ ml_location_lane_counter.onnx 6
 #The encoder an decoder model are used in ml_asr scene, both have value overflow. Not suitable for fp16.
 #But added for guarding process.
 encoder.onnx;1,32,83 1262
-mtk_emotions-d2012-75.onnx 4.73
-mtk_detect-mbv1-shortcut-400-400.onnx 0.042
-mtk_detect-mbv2-shortcut-400-400.onnx 0.1
-mtk_detect_mbv1_640_480.onnx 0.07
-mtk_detect-deeper-halfdeeper-mbv1-shortcut-400-400_nopostprocess_simplified_onnx.onnx 1.52
-mtk_detect-mbv1-shortcut-400-400_nopostprocess_simplified_onnx.onnx 6.2
-mtk_detect-deeper-halfdeeper-mbv1-lastearlySSD-shortcut-400-400_nopostprocess_simplified_onnx.onnx 2.2
-mtk_detect_mbv1_640_480_nopostprocess_simplified_onnx.onnx;1,480,640,3 1.8
-mtk_face_features_v2.onnx;1,256,192,3 0.04
-mtk_face_recognition_v3.onnx 0.21
-mtk_face_recognition_v2.onnx 2.45
+mtk_emotions-d2012-75.onnx 5
+mtk_detect-mbv1-shortcut-400-400.onnx 0.5
+mtk_detect-mbv2-shortcut-400-400.onnx 0.5
+mtk_detect_mbv1_640_480.onnx 0.5
+mtk_detect-deeper-halfdeeper-mbv1-shortcut-400-400_nopostprocess_simplified_onnx.onnx 2
+mtk_detect-mbv1-shortcut-400-400_nopostprocess_simplified_onnx.onnx 6.5
+mtk_detect-deeper-halfdeeper-mbv1-lastearlySSD-shortcut-400-400_nopostprocess_simplified_onnx.onnx 2.5
+mtk_detect_mbv1_640_480_nopostprocess_simplified_onnx.onnx;1,480,640,3 2
+mtk_face_features_v2.onnx;1,256,192,3 0.5
+mtk_face_recognition_v3.onnx 0.5
+mtk_face_recognition_v2.onnx 2.5
+ml_2012_ocr_detection.onnx 0.5

mindspore/lite/test/models_tf.cfg

@@ -1,66 +1,59 @@
-decoder_step_201217.pb 5
-decoder_step_201217_modified.pb 5
-unet_model_reconstruct.pb 1;1,256,256,3
-encoder_201228.pb 3;1:1,22:1
-female_model_step2_int16_noiseout.pb 66
-encoder_0111_control_flow.pb 4;1:1,44:1:1
-encoder_0111.pb 4;1:1,44:1:1
-ml_video_edit_generate_filter.pb 1
-densenet.pb 1;1,224,224,3
-inception_resnet_v2.pb 1;1,299,299,3
-inception_v3.pb 1;1,299,299,3
-inception_v4.pb 1;1,299,299,3
-mnasnet_1.0_224.pb 1
-mnasnet_1.3_224.pb 1
-mobilenet_v1_0.25_128_frozen.pb 1;1,128,128,3
-mobilenet_v2_1.0_224_frozen.pb 1;1,224,224,3
-nasnet_large.pb 1;1,331,331,3
-nasnet_mobile.pb 1;1,224,224,3
-squeezenet.pb 1;1,224,224,3
-ml_ei_headpose.pb 1;1,64,64,3
-ml_ei_landmark.pb 1;1,160,160,3
-ml_face_openclose.pb 1;1,32,32,3
-ml_object_detect.pb 1;1,288,288,3
-ml_ocr_jk.pb 1
-ml_video_edit_enhance.pb 1
-ml_vision_guide_detection1.pb 1
-ml_vision_guide_detection3.pb 1
-scan_hms_angle.pb 1
-scan_hms_detect.pb 1
-hiai_AADB_HADB_MBV2_model.pb 1;1,224,224,3
-hiai_cn_recognize_modify_padv2.pb 1;1,32,512,1
-hiai_cpu_face_emotion.pb 1
-hiai_cpu_face_gazing.pb 1
-hiai_cpu_face_headpose.pb 1
-hiai_ctpn_feature_map.pb 1
-hiai_cv_focusShootOCRModel_02.pb 1
-hiai_cv_focusShootOCRModel_08.pb 1
-hiai_cv_poseEstimation.pb 1
-hiai_detectmodel_06_23_960_480_1180700.pb 1
-hiai_dress_detect.pb 1;1,960,960,3
-hiai_face_model_npu.pb 1
-hiai_frozen_inference_graph.pb 1;1,300,300,3
-hiai_ghostnet.pb 1
-hiai_iMaxDN_RGB.pb 1
-hiai_iMaxSR_RGB.pb 1
-hiai_label_and_video.pb 1;1,224,224,3
-hiai_latin_ocr.pb 1
-hiai_latin_ocr_1.pb 1
-hiai_lm_inference_graph.pb 1
-hiai_model_0909_kd_rot_ps_softmax.pb 1;1,224,224,3
-hiai_PoseEstimation_Pcm.pb 1
-model_normalize_object_scene_ps_20200519.pb 1;1,224,224,3
-mtk_AADB_HADB_MBV2_model.pb 1;1,224,224,3
-mtk_AADB_HADB_MBV3_model.pb 1;1,224,224,3
-mtk_age_gender.pb 1
-mtk_model_ckpt.pb 1
-mtk_model_face_dress.pb 1;1,128,128,3
-mtk_model_normalize_object_scene_ps_20200519.pb 1;1,224,224,3
-ml_ocr_latin.pb 1
-ml_noya_tts_melgan.pb 1;16,16,80
-ml_video_edit_oneclick_adaptis.pb 3
+unet_model_reconstruct.pb;1,256,256,3
+ml_video_edit_generate_filter.pb
+densenet.pb;1,224,224,3
+inception_resnet_v2.pb;1,299,299,3
+inception_v3.pb;1,299,299,3
+inception_v4.pb;1,299,299,3
+mnasnet_1.0_224.pb
+mnasnet_1.3_224.pb
+mobilenet_v1_0.25_128_frozen.pb;1,128,128,3
+mobilenet_v2_1.0_224_frozen.pb;1,224,224,3
+nasnet_large.pb;1,331,331,3
+nasnet_mobile.pb;1,224,224,3
+squeezenet.pb;1,224,224,3
+ml_ei_headpose.pb;1,64,64,3
+ml_ei_landmark.pb;1,160,160,3
+ml_face_openclose.pb;1,32,32,3
+ml_object_detect.pb;1,288,288,3
+ml_ocr_jk.pb
+ml_video_edit_enhance.pb
+ml_vision_guide_detection1.pb
+ml_vision_guide_detection3.pb
+scan_hms_angle.pb
+scan_hms_detect.pb
+hiai_AADB_HADB_MBV2_model.pb;1,224,224,3
+hiai_cn_recognize_modify_padv2.pb;1,32,512,1
+hiai_cpu_face_emotion.pb
+hiai_cpu_face_gazing.pb
+hiai_cpu_face_headpose.pb
+hiai_ctpn_feature_map.pb
+hiai_cv_focusShootOCRModel_02.pb
+hiai_cv_focusShootOCRModel_08.pb
+hiai_cv_poseEstimation.pb
+hiai_detectmodel_06_23_960_480_1180700.pb
+hiai_dress_detect.pb;1,960,960,3
+hiai_face_model_npu.pb
+hiai_frozen_inference_graph.pb;1,300,300,3
+hiai_ghostnet.pb
+hiai_iMaxDN_RGB.pb
+hiai_iMaxSR_RGB.pb
+hiai_label_and_video.pb;1,224,224,3
+hiai_latin_ocr.pb
+hiai_latin_ocr_1.pb
+hiai_lm_inference_graph.pb
+hiai_model_0909_kd_rot_ps_softmax.pb;1,224,224,3
+hiai_PoseEstimation_Pcm.pb
+model_normalize_object_scene_ps_20200519.pb;1,224,224,3
+mtk_AADB_HADB_MBV2_model.pb;1,224,224,3
+mtk_AADB_HADB_MBV3_model.pb;1,224,224,3
+mtk_age_gender.pb
+mtk_model_ckpt.pb
+mtk_model_face_dress.pb;1,128,128,3
+mtk_model_normalize_object_scene_ps_20200519.pb;1,224,224,3
+ml_ocr_latin.pb
+ml_noya_tts_melgan.pb;16,16,80
 # Q_hand_0812.pb is not suitable for float16. Out of float16 range.
 Q_hand_0812.pb
-tacotron_encoder_stf.pb 5;1:1,62:1,62:1,62:1,62
-Q_inception-249970-672-11-16.pb 1
-Q_dila-small-mix-full-fineturn-390000-nopixel-nosigmoid.pb 1
+Q_inception-249970-672-11-16.pb
+Q_dila-small-mix-full-fineturn-390000-nopixel-nosigmoid.pb
+Q_crnn_screen_slim400w_more_20w.pb

mindspore/lite/test/models_tf_fp16.cfg

@@ -5,3 +5,7 @@ ml_ocr_jk.pb 0.5
 ml_ocr_latin.pb 135
 scan_hms_angle.pb 1.5
 scan_hms_detect.pb 2.5
+ml_face_openclose.pb;1,32,32,3 0.5
+ml_object_detect.pb;1,288,288,3 2
+Q_crnn_screen_slim400w_more_20w.pb 137
+Q_inception-249970-672-11-16.pb 6.5

mindspore/lite/test/models_tflite_fp16.cfg

@@ -163,4 +163,5 @@ hiai_AADB_HADB_MBV2_model_f16.tflite 2.4
 hiai_AADB_HADB_MBV2_model_fp32.tflite 4.1
 mtk_age_gender_fp16.tflite 25.5
 #hiai_cv_labelDetectorModel_v3.tflite 5.1
-#hiai_detect_curve_model_float32.tflite 8.98
+#hiai_detect_curve_model_float32.tflite 8.98
+Q_language_model_hrmini_Q4_b4_17w.tflite 3.5

mindspore/lite/test/models_with_multiple_inputs.cfg

@@ -11,3 +11,16 @@ decoder.onnx;2;1,7,512:1,7
 fasterrcnn_crop.pb;1;420,630,3
 ml_video_edit_person_divison_video;2
 hdc_tb_cn_neg.tflite;3
+decoder_step_201217.pb;5
+decoder_step_201217_modified.pb;5
+encoder_201228.pb;3;1:1,22:1
+encoder_0111_control_flow.pb;4;1:1,44:1:1
+encoder_0111.pb;4;1:1,44:1:1
+ml_video_edit_oneclick_adaptis.pb;3
+tacotron_encoder_stf.pb;5;1:1,62:1,62:1,62:1,62
+female_model_step2_int16_noiseout.pb;66
+ml_female_model_step6_noiseout.pb;66
+ml_male_model_step6_noiseout.pb;66
+ml_tts_decoder_control_flow.pb;5
+ml_tts_decoder.pb;5
+ml_tts_encoder_control_flow.pb;4;1:1,22:1:1

mindspore/lite/test/models_with_multiple_inputs_fp16.cfg

@@ -9,4 +9,8 @@ decoder_step_201217.pb;5 187
 ml_video_edit_art_transfer.onnx;3 3
 decoder.onnx;2;1,7,512:1,7 113
 decoder_step_201217_modified.pb;5 0.5
-encoder_0111_control_flow.pb;4;1:1,44:1:1 10
+#encoder_0111_control_flow.pb;4;1:1,44:1:1 10
+ml_female_model_step6_noiseout.pb;66 2
+ml_male_model_step6_noiseout.pb;66 2.5
+ml_tts_decoder_control_flow.pb;5 1
+ml_tts_decoder.pb;5 117

mindspore/lite/test/run_benchmark_nets.sh

@@ -15,12 +15,10 @@ function Run_Converter() {
 
     # Convert tf models:
     while read line; do
-        tf_line_info=${line}
-        if [[ $tf_line_info == \#* ]]; then
+        model_name=${line%;*}
+        if [[ $model_name == \#* ]]; then
           continue
         fi
-        model_name=`echo ${tf_line_info}|awk -F ' ' '{print $1}'`
-        input_num=`echo ${tf_line_info}|awk -F ' ' '{print $2}'`
         echo ${model_name} >> "${run_converter_log_file}"
         echo './converter_lite  --fmk=TF --modelFile='${models_path}'/'${model_name}' --outputFile='${ms_models_path}'/'${model_name}'' >> "${run_converter_log_file}"
         ./converter_lite  --fmk=TF --modelFile=$models_path/${model_name} --outputFile=${ms_models_path}/${model_name}
@@ -398,31 +396,15 @@ function Run_x86() {
 
     # Run tf converted models:
     while read line; do
-        model_name_and_input_num=${line%;*}
-        length=${#model_name_and_input_num}
+        model_name=${line%;*}
+        length=${#model_name}
         input_shapes=${line:length+1}
-        tf_line_info=${model_name_and_input_num}
-        if [[ $tf_line_info == \#* ]]; then
+        if [[ $model_name == \#* ]]; then
           continue
         fi
-        model_name=`echo ${tf_line_info}|awk -F ' ' '{print $1}'`
-        input_num=`echo ${tf_line_info}|awk -F ' ' '{print $2}'`
-        input_files=''
-        for i in $(seq 1 $input_num)
-        do
-          input_files=$input_files'/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/'$model_name'.ms_'$i'.bin,'
-        done
         echo ${model_name} >> "${run_x86_log_file}"
-        echo './benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/'${input_files}' --inputShapes='${input_shapes}' --benchmarkDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/output/'${model_name}'.ms.out' >> "${run_x86_log_file}"
-        ./benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} --benchmarkDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/output/${model_name}.ms.out >> "${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} >> ${run_benchmark_result_file}; return 1
-        fi
-        # run benchmark test with input data
-        echo './benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/'${input_files}' --inputShapes='${input_shapes} >> "${run_x86_log_file}"
-        ./benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=${input_files} --inputShapes=${input_shapes} >> "${run_x86_log_file}"
+        echo './benchmark --modelFile='${ms_models_path}'/'${model_name}'.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/'${model_name}'.ms.bin --inputShapes='${input_shapes}' --benchmarkDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/output/'${model_name}'.ms.out' >> "${run_x86_log_file}"
+        ./benchmark --modelFile=${ms_models_path}/${model_name}.ms --inDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/input/${model_name}.ms.bin --inputShapes=${input_shapes} --benchmarkDataFile=/home/workspace/mindspore_dataset/mslite/models/hiai/input_output/output/${model_name}.ms.out >> "${run_x86_log_file}"
         if [ $? = 0 ]; then
             run_result='x86: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
         else
@@ -1296,34 +1278,27 @@ function Run_arm64() {
 
     # Run tf converted models:
     while read line; do
-        model_name_and_input_num=${line%;*}
-        length=${#model_name_and_input_num}
+        model_name=${line%;*}
+        length=${#model_name}
         input_shapes=${line:length+1}
-        tf_line_info=${model_name_and_input_num}
-        if [[ $tf_line_info == \#* ]]; then
+        if [[ $model_name == \#* ]]; then
           continue
         fi
-        model_name=`echo ${tf_line_info}|awk -F ' ' '{print $1}'`
-        input_num=`echo ${tf_line_info}|awk -F ' ' '{print $2}'`
-        input_files=''
-        for i in $(seq 1 $input_num)
-        do
-          input_files=$input_files'/data/local/tmp/input_output/input/'$model_name'.ms_'$i'.bin,'
-        done
         echo ${model_name} >> "${run_arm64_fp32_log_file}"
         echo 'cd  /data/local/tmp/benchmark_test' > adb_run_cmd.txt
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --inDataFile='${input_files}' --benchmarkDataFile=/data/local/tmp/input_output/output/'${model_name}'.ms.out' >> "${run_arm64_fp32_log_file}"
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --inDataFile='${input_files}' --benchmarkDataFile=/data/local/tmp/input_output/output/'${model_name}'.ms.out' >> adb_run_cmd.txt
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inDataFile=/data/local/tmp/input_output/input/'${model_name}'.ms.bin --inputShapes='${input_shapes}' --benchmarkDataFile=/data/local/tmp/input_output/output/'${model_name}'.ms.out' >> "${run_arm64_fp32_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inDataFile=/data/local/tmp/input_output/input/'${model_name}'.ms.bin --inputShapes='${input_shapes}' --benchmarkDataFile=/data/local/tmp/input_output/output/'${model_name}'.ms.out' >> adb_run_cmd.txt
         adb -s ${device_id} shell < adb_run_cmd.txt >> "${run_arm64_fp32_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
-        # run benchmark test with input data
+        # run benchmark test without clib data
+        echo ${model_name} >> "${run_arm64_fp32_log_file}"
         echo 'cd  /data/local/tmp/benchmark_test' > adb_run_cmd.txt
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --inDataFile='${input_files}' --warmUpLoopCount=1 --loopCount=2' >> "${run_arm64_fp32_log_file}"
-        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --inputShapes='${input_shapes}' --modelFile='${model_name}'.ms --inDataFile='${input_files}' --warmUpLoopCount=1 --loopCount=2' >> adb_run_cmd.txt
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inputShapes='${input_shapes}' --warmUpLoopCount=1 --loopCount=2' >> "{run_arm64_fp32_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inputShapes='${input_shapes}' --warmUpLoopCount=1 --loopCount=2' >> adb_run_cmd.txt
         adb -s ${device_id} shell < adb_run_cmd.txt >> "${run_arm64_fp32_log_file}"
         if [ $? = 0 ]; then
             run_result='arm64: '${model_name}' pass'; echo ${run_result} >> ${run_benchmark_result_file}
@@ -1627,6 +1602,17 @@ function Run_arm64() {
         else
             run_result='arm64: '${model_name}' failed'; echo ${run_result} >> ${run_benchmark_result_file}; return 1
         fi
+        # run benchmark test without clib data
+        echo ${model_name} >> "${run_arm64_fp32_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 --inDataFile='${input_files}' --inputShapes='${input_shapes} ' --warmUpLoopCount=1 --loopCount=2' >> "${run_arm64_fp32_log_file}"
+        echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/data/local/tmp/benchmark_test;./benchmark --modelFile='${model_name}'.ms --inDataFile='${input_files}' --inputShapes='${input_shapes} ' --warmUpLoopCount=1 --loopCount=2' >> adb_run_cmd.txt
+        adb -s ${device_id} shell < adb_run_cmd.txt >> "${run_arm64_fp32_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_with_multiple_inputs_config}
 
     # Run converted models which does not need to be cared about the accuracy:
@@ -1845,7 +1831,7 @@ function Run_arm64_fp16() {
     while read line; do
         fp16_line_info=${line}
         if [[ $fp16_line_info == \#* ]]; then
-          continue-
+          continue
         fi
         model_info=`echo ${fp16_line_info}|awk -F ' ' '{print $1}'`
         accuracy_limit=`echo ${fp16_line_info}|awk -F ' ' '{print $2}'`