Merge branch 'dygraph' into dygraph

test_tipc/configs/det_r50_vd_sast_totaltext_v2.0/train_infer_python.txt

@@ -43,7 +43,7 @@ inference:tools/infer/predict_det.py
 --cpu_threads:1|6
 --rec_batch_num:1
 --use_tensorrt:False
---precision:fp32|fp16|int8
+--precision:fp32|int8
 --det_model_dir:
 --image_dir:./inference/ch_det_data_50/all-sum-510/
 null:null

test_tipc/prepare.sh

@@ -179,7 +179,7 @@ elif [ ${MODE} = "whole_infer" ];then
         cd ./inference/ && tar xf rec_r34_vd_tps_bilstm_ctc_v2.0_train.tar && cd ../
     fi
     if [ ${model_name} == "ch_ppocr_server_v2.0_rec" ]; then
-        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/ch_ppocr_server_v2.0_rec_train.tar --no-check-certificate
+        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_server_v2.0_rec_train.tar --no-check-certificate
         cd ./inference/ && tar xf ch_ppocr_server_v2.0_rec_train.tar && cd ../
     fi
     if [ ${model_name} == "ch_ppocr_mobile_v2.0_rec" ]; then
@@ -239,18 +239,23 @@ fi
 
 if [ ${MODE} = "klquant_whole_infer" ]; then
     wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/icdar2015_lite.tar --no-check-certificate
-    cd ./train_data/ && tar xf icdar2015_lite.tar
-    ln -s ./icdar2015_lite ./icdar2015 && cd ../
+    cd ./train_data/ && tar xf icdar2015_lite.tar && rm -rf ./icdar2015 && ln -s ./icdar2015_lite ./icdar2015 && cd ../
     if [ ${model_name} = "ch_ppocr_mobile_v2.0_det_KL" ]; then
         wget -nc  -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_infer.tar --no-check-certificate
         wget -nc -P ./inference https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ch_det_data_50.tar  --no-check-certificate
         cd ./inference && tar xf ch_ppocr_mobile_v2.0_det_infer.tar && tar xf ch_det_data_50.tar && cd ../ 
     fi
-    if [ ${model_name} = "ch_PPOCRv2_det" ]; then
-        eval_model_name="ch_PP-OCRv2_det_infer"
+    if [ ${model_name} = "PPOCRv2_ocr_rec_kl" ]; then
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar  --no-check-certificate
+        wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/rec_inference.tar  --no-check-certificate
+        wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/test/ic15_data.tar --no-check-certificate
+        cd ./train_data/ && tar xf ic15_data.tar && cd ../
+        cd ./inference && tar xf rec_inference.tar && tar xf ch_PP-OCRv2_rec_infer.tar && cd ../
+    fi
+    if [ ${model_name} = "PPOCRv2_ocr_det_kl" ]; then
         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
-        cd ./inference && tar xf ${eval_model_name}.tar && tar xf ch_det_data_50.tar && cd ../
+        wget -nc -P ./inference https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_det_infer.tar  --no-check-certificate
+        cd ./inference && tar xf ch_PP-OCRv2_det_infer.tar && tar xf ch_det_data_50.tar && cd ../
     fi 
     if [ ${model_name} = "ch_ppocr_mobile_v2.0_rec_KL" ]; then
         wget -nc -P ./inference/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_rec_infer.tar --no-check-certificate

test_tipc/test_train_inference_python.sh

@@ -183,7 +183,7 @@ function func_inference(){
                     if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
                         continue
                     fi
-                    if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [ ${_flag_quant} = "True" ]; then
+                    if [[ ${use_trt} = "False" && ${precision} =~ "int8" ]] && [ ${_flag_quant} = "True" ]; then
                         continue
                     fi
                     for batch_size in ${batch_size_list[*]}; do
@@ -227,7 +227,12 @@ if [ ${MODE} = "whole_infer" ] || [ ${MODE} = "klquant_whole_infer" ]; then
     for infer_model in ${infer_model_dir_list[*]}; do
         # run export
         if [ ${infer_run_exports[Count]} != "null" ];then
-            save_infer_dir=$(dirname $infer_model)
+            if [ ${MODE} = "klquant_whole_infer" ]; then
+                save_infer_dir="${infer_model}_klquant"
+            fi
+            if [ ${MODE} = "whole_infer" ]; then
+                save_infer_dir="${infer_model}"
+            fi
             set_export_weight=$(func_set_params "${export_weight}" "${infer_model}")
             set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_dir}")
             export_cmd="${python} ${infer_run_exports[Count]} ${set_export_weight} ${set_save_infer_key}"
@@ -259,7 +264,6 @@ else
             env=""
         elif [ ${#gpu} -le 1 ];then
             env="export CUDA_VISIBLE_DEVICES=${gpu}"
-            eval ${env}
         elif [ ${#gpu} -le 15 ];then
             IFS=","
             array=(${gpu})
@@ -280,6 +284,7 @@ else
                 set_amp_config=" "
             fi          
             for trainer in ${trainer_list[*]}; do 
+                eval ${env}
                 flag_quant=False
                 if [ ${trainer} = ${pact_key} ]; then
                     run_train=${pact_trainer}
@@ -332,7 +337,6 @@ else
                     cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}"
                 fi
                 # run train
-                eval "unset CUDA_VISIBLE_DEVICES"
                 eval $cmd
                 status_check $? "${cmd}" "${status_log}"
 

tools/infer/predict_det.py

@@ -101,16 +101,21 @@ class TextDetector(object):
         else:
             logger.info("unknown det_algorithm:{}".format(self.det_algorithm))
             sys.exit(0)
+
+        self.preprocess_op = create_operators(pre_process_list)
+        self.postprocess_op = build_post_process(postprocess_params)
+        self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor(
+            args, 'det', logger)
+
         if self.use_onnx:
+            img_h, img_w = self.input_tensor.shape[2:]
+            if img_h is not None and img_w is not None and img_h > 0 and img_w > 0:
                 pre_process_list[0] = {
                     'DetResizeForTest': {
-                    'image_shape': [640, 640]
+                        'image_shape': [img_h, img_w]
                     }
                 }
         self.preprocess_op = create_operators(pre_process_list)
-        self.postprocess_op = build_post_process(postprocess_params)
-        self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor(
-            args, 'det', logger)
 
         if args.benchmark:
             import auto_log

tools/infer/predict_rec.py

@@ -109,7 +109,10 @@ class TextRecognizer(object):
         assert imgC == img.shape[2]
         imgW = int((32 * max_wh_ratio))
         if self.use_onnx:
-            imgW = 100
+            w = self.input_tensor.shape[3:][0]
+            if w is not None and w > 0:
+                imgW = w
+
         h, w = img.shape[:2]
         ratio = w / float(h)
         if math.ceil(imgH * ratio) > imgW:

tools/infer/utility.py

@@ -15,6 +15,7 @@
 import argparse
 import os
 import sys
+import platform
 import cv2
 import numpy as np
 import paddle
@@ -313,6 +314,10 @@ def create_predictor(args, mode, logger):
 
 
 def get_infer_gpuid():
+    sysstr = platform.system()
+    if sysstr == "Windows":
+        return 0
+
     if not paddle.fluid.core.is_compiled_with_rocm():
         cmd = "env | grep CUDA_VISIBLE_DEVICES"
     else: