Merge pull request #4856 from LDOUBLEV/tipc_test_allclose

fix finite

test_tipc/configs/det_r50_vd_sast_icdar15_v2.0/det_r50_vd_sast_icdar2015.yml

@@ -62,7 +62,7 @@ Train:
     data_dir: ./train_data/icdar2015/text_localization/
     label_file_list:
       - ./train_data/icdar2015/text_localization/train_icdar2015_label.txt
-    ratio_list: [0.1, 0.45, 0.3, 0.15]
+    ratio_list: [1.0]
     transforms:
       - DecodeImage: # load image
           img_mode: BGR

test_tipc/configs/en_server_pgnetA/train_infer_python.txt

@@ -4,7 +4,7 @@ python:python3.7
 gpu_list:0|0,1
 Global.use_gpu:True|True
 Global.auto_cast:null
-Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=500
+Global.epoch_num:lite_train_lite_infer=5|whole_train_whole_infer=500
 Global.save_model_dir:./output/
 Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=14
 Global.pretrained_model:null
@@ -42,7 +42,7 @@ inference:tools/infer/predict_e2e.py
 --enable_mkldnn:True|False
 --cpu_threads:1|6
 --rec_batch_num:1
---use_tensorrt:False|True
+--use_tensorrt:False
 --precision:fp32|fp16|int8
 --e2e_model_dir:
 --image_dir:./inference/ch_det_data_50/all-sum-510/

test_tipc/prepare.sh

@@ -25,7 +25,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
     # pretrain lite train data
     wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams  --no-check-certificate
     wget -nc -P ./pretrain_models/  https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar  --no-check-certificate
-    if [ ${model_name} == "ch_PPOCRv2_det" ]; then
+    if [ ${model_name} =~ "ch_PPOCRv2_det" ]; then
         wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_distill_train.tar --no-check-certificate
         cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../
     fi
@@ -50,7 +50,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then
     if [ ${model_name} == "det_r50_vd_sast_icdar15_v2.0" ] || [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then
         wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate
         wget -nc -P ./train_data/ wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar --no-check-certificate
-        cd ./train_data && tar xf total_text_lite.tar && ln -s total_text && cd ../
+        cd ./train_data && tar xf total_text_lite.tar && ln -s total_text_lite total_text  && cd ../
     fi
     if [ ${model_name} == "det_mv3_db_v2.0" ]; then
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar  --no-check-certificate
@@ -78,15 +78,15 @@ elif [ ${MODE} = "whole_train_whole_infer" ];then
         cd ./pretrain_models/ && tar xf ch_PP-OCRv2_det_distill_train.tar && cd ../
     fi
     if [ ${model_name} == "en_server_pgnetA" ]; then
-        wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/total_text.tar --no-check-certificate
+        wget -nc -P ./train_data/  https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar  --no-check-certificate
         wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/pgnet/en_server_pgnetA.tar --no-check-certificate
         cd ./pretrain_models/ && tar xf en_server_pgnetA.tar && cd ../
-        cd ./train_data && tar xf total_text.tar && ln -s total_text && cd ../
+        cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text  && cd ../
     fi
     if [ ${model_name} == "det_r50_vd_sast_totaltext_v2.0" ]; then
         wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ResNet50_vd_ssld_pretrained.pdparams --no-check-certificate
-        wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dataset/total_text.tar --no-check-certificate
+        wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/total_text_lite.tar  --no-check-certificate
-        cd ./train_data && tar xf total_text.tar && ln -s total_text && cd ../
+        cd ./train_data && tar xf total_text.tar && ln -s total_text_lite total_text  && cd ../
     fi
 elif [ ${MODE} = "lite_train_whole_infer" ];then
     wget -nc -P  ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate
@@ -135,7 +135,7 @@ elif [ ${MODE} = "whole_infer" ];then
         wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_infer.tar --no-check-certificate
         cd ./inference && tar xf ${eval_model_name}.tar && tar xf rec_inference.tar && cd ../
     fi 
-    if [ ${model_name} = "ch_PPOCRv2_det" ]; then
+    if [ ${model_name} =~ "ch_PPOCRv2_det" ]; then
         eval_model_name="ch_PP-OCRv2_det_infer"
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar --no-check-certificate
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar --no-check-certificate

tools/infer/utility.py

@@ -195,6 +195,7 @@ def create_predictor(args, mode, logger):
                     max_batch_size=args.max_batch_size,
                     min_subgraph_size=args.min_subgraph_size)
                 # skip the minmum trt subgraph
+            use_dynamic_shape = True
             if mode == "det":
                 min_input_shape = {
                     "x": [1, 3, 50, 50],
@@ -260,6 +261,8 @@ def create_predictor(args, mode, logger):
                 max_input_shape.update(max_pact_shape)
                 opt_input_shape.update(opt_pact_shape)
             elif mode == "rec":
+                if args.rec_algorithm != "CRNN":
+                    use_dynamic_shape = False
                 min_input_shape = {"x": [1, 3, 32, 10]}
                 max_input_shape = {"x": [args.rec_batch_num, 3, 32, 1536]}
                 opt_input_shape = {"x": [args.rec_batch_num, 3, 32, 320]}
@@ -268,14 +271,8 @@ def create_predictor(args, mode, logger):
                 max_input_shape = {"x": [args.rec_batch_num, 3, 48, 1024]}
                 opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]}
             else:
-                min_input_shape = {"x": [1, 3, 10, 10]}
+                use_dynamic_shape = False
-                max_input_shape = {"x": [1, 3, 512, 512]}
+            if use_dynamic_shape:
-                opt_input_shape = {"x": [1, 3, 256, 256]}
-            if mode == "rec":
-                if args.rec_algorithm == "CRNN":
-                    config.set_trt_dynamic_shape_info(
-                        min_input_shape, max_input_shape, opt_input_shape)
-            else:
                 config.set_trt_dynamic_shape_info(
                     min_input_shape, max_input_shape, opt_input_shape)