clean pylint & shell check

model_zoo/official/cv/crnn/ascend310_infer/build.sh

@@ -17,7 +17,7 @@
 if [ ! -d out ]; then
   mkdir out
 fi
-cd out
+cd out || exit
 cmake .. \
     -DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
 make

model_zoo/official/cv/crnn/scripts/run_infer_310.sh

@@ -63,7 +63,7 @@ fi
 
 function compile_app()
 {
-    cd ../ascend310_infer
+    cd ../ascend310_infer || exit
     if [ -f "Makefile" ]; then
         make clean
     fi
@@ -73,7 +73,7 @@ function compile_app()
         echo "compile app code failed"
         exit 1
     fi
-    cd -
+    cd - || exit
 }
 
 function infer()

model_zoo/official/cv/ctpn/scripts/run_infer_310.sh

@@ -73,7 +73,7 @@ function compile_app()
         echo "compile app code failed"
         exit 1
     fi
-    cd -
+    cd - || exit
 }
 
 function infer()

model_zoo/official/cv/deeptext/ascend310_infer/build.sh

@@ -17,7 +17,7 @@
 if [ ! -d out ]; then
   mkdir out
 fi
-cd out
+cd out || exit
 cmake .. \
     -DMINDSPORE_PATH="`pip show mindspore-ascend | grep Location | awk '{print $2"/mindspore"}' | xargs realpath`"
 make

model_zoo/official/cv/deeptext/postprocess.py

@@ -16,12 +16,11 @@
 """Evaluation for Deeptext"""
 import argparse
 import os
-
+from PIL import Image
 import numpy as np
+import mmcv
 from src.config import config
 from src.utils import metrics
-from PIL import Image
-import mmcv
 
 parser = argparse.ArgumentParser(description="Deeptext evaluation")
 parser.add_argument("--result_path", type=str, required=True, help="result file path")

model_zoo/official/cv/deeptext/scripts/run_infer_310.sh

@@ -62,7 +62,7 @@ fi
 
 function compile_app()
 {
-    cd ../ascend310_infer
+    cd ../ascend310_infer || exit
     if [ -f "Makefile" ]; then
         make clean
     fi
@@ -72,7 +72,7 @@ function compile_app()
         echo "compile app code failed"
         exit 1
     fi
-    cd -
+    cd - || exit
 }
 
 function infer()

model_zoo/official/cv/faster_rcnn/ascend310_infer/src/build.sh

@@ -19,7 +19,7 @@ build_type="Release"
 function preparePath() {
     rm -rf $1
     mkdir -p $1
-    cd $1
+    cd $1 || exit
 }
 
 function buildA300() {

model_zoo/official/cv/maskrcnn/scripts/run_infer_310.sh

@@ -66,9 +66,9 @@ function air_to_om()
 
 function compile_app()
 {
-    cd ../ascend310_infer/src
+    cd ../ascend310_infer/src || exit
     sh build.sh &> build.log
-    cd -
+    cd - || exit
 }
 
 function infer()

model_zoo/official/cv/resnet152/scripts/run_eval.sh

@@ -57,7 +57,7 @@ mkdir ./eval
 cp ../*.py ./eval
 cp *.sh ./eval
 cp -r ../src ./eval
-cd ./eval 
+cd ./eval || exit
 env > env.log
 echo "start evaluation for device $DEVICE_ID"
 python eval.py --data_url=$PATH1 --checkpoint_path=$PATH2 &> eval.log &

model_zoo/official/cv/unet/scripts/run_infer_310.sh

@@ -70,7 +70,7 @@ function preprocess_data()
 
 function compile_app()
 {
-    cd ../ascend310_infer/src
+    cd ../ascend310_infer/ || exit
     if [ -f "Makefile" ]; then
         make clean
     fi

model_zoo/official/cv/vgg16/scripts/run_distribute_train.sh

@@ -62,7 +62,8 @@ do
     end=`expr $start \+ $gap`
     cmdopt=$start"-"$end
 
-    export DEVICE_ID=`expr $i \+ $start_idx`
+    device_id=`expr $i \+ $start_idx`
+    export DEVICE_ID=$device_id
     export RANK_ID=$i
     rm -rf ./train_parallel$DEVICE_ID
     mkdir ./train_parallel$DEVICE_ID

model_zoo/official/cv/yolov4/scripts/run_infer_310.sh

@@ -60,7 +60,7 @@ fi
 
 function compile_app()
 {
-    cd ../ascend310_infer/src
+    cd ../ascend310_infer/src || exit
     if [ -f "Makefile" ]; then
         make clean
     fi

model_zoo/official/nlp/fasttext/src/dataset.py

@@ -21,8 +21,8 @@ import pprint
 import ast
 import html
 import numpy as np
-import spacy
 from sklearn.feature_extraction import FeatureHasher
+import spacy
 from mindspore.mindrecord import FileWriter
 
 

model_zoo/research/cv/FaceQualityAssessment/scripts/run_eval.sh

@@ -61,7 +61,7 @@ export RANK_ID=0
 rm -rf ${current_exec_path}/device$USE_DEVICE_ID
 echo 'start device '$USE_DEVICE_ID
 mkdir ${current_exec_path}/device$USE_DEVICE_ID
-cd ${current_exec_path}/device$USE_DEVICE_ID
+cd ${current_exec_path}/device$USE_DEVICE_ID || exit
 dev=`expr $USE_DEVICE_ID + 0`
 export DEVICE_ID=$dev
 python ${dirname_path}/${SCRIPT_NAME} \

model_zoo/research/cv/FaceQualityAssessment/train.py

@@ -102,7 +102,7 @@ def main(args):
             else:
                 param_dict_new[key] = values
         load_param_into_net(network, param_dict_new)
-        cfg.logger.info('load model %s success.' % cfg.pretrained)
+        cfg.logger.info('load model %s success.', cfg.pretrained)
 
     # optimizer and lr scheduler
     lr = warmup_step(cfg, gamma=0.9)

model_zoo/research/cv/FaceRecognition/eval.py

@@ -328,6 +328,6 @@ if __name__ == '__main__':
     log_path = os.path.join(arg.ckpt_path, 'logs')
     arg.logger = get_logger(log_path, arg.local_rank)
 
-    arg.logger.info('Config\n\n{}\n'.format(pformat(arg)))
+    arg.logger.info('Config: {}'.format(pformat(arg)))
 
     main(arg)

model_zoo/research/cv/FaceRecognition/scripts/run_standalone_train_base.sh

@@ -42,7 +42,7 @@ mkdir ${EXECUTE_PATH}/log_standalone_graph
 
 rm -rf ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID
 mkdir -p ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID
-cd ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID
+cd ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID || exit
 echo "start training for rank $RANK_ID, device $USE_DEVICE_ID"
 env > ${EXECUTE_PATH}/log_standalone_graph/face_recognition_$USE_DEVICE_ID.log
 python ${EXECUTE_PATH}/../train.py \

model_zoo/research/cv/FaceRecognition/scripts/run_standalone_train_beta.sh

@@ -42,7 +42,7 @@ mkdir ${EXECUTE_PATH}/log_standalone_graph
 
 rm -rf ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID
 mkdir -p ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID
-cd ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID
+cd ${EXECUTE_PATH}/data_standalone_log_$USE_DEVICE_ID || exit
 echo "start training for rank $RANK_ID, device $USE_DEVICE_ID"
 env > ${EXECUTE_PATH}/log_standalone_graph/face_recognition_$USE_DEVICE_ID.log
 python ${EXECUTE_PATH}/../train.py \

model_zoo/research/cv/FaceRecognitionForTracking/train.py

@@ -90,13 +90,13 @@ def main():
     cfg.logger.info('start create dataloader')
     de_dataset, steps_per_epoch, class_num = get_de_dataset(cfg)
     cfg.steps_per_epoch = steps_per_epoch
-    cfg.logger.info('step per epoch: %d' % cfg.steps_per_epoch)
+    cfg.logger.info('step per epoch: {}'.format(cfg.steps_per_epoch))
     de_dataloader = de_dataset.create_tuple_iterator()
-    cfg.logger.info('class num original: %d' % class_num)
+    cfg.logger.info('class num original: {}'.format(class_num))
     if class_num % 16 != 0:
         class_num = (class_num // 16 + 1) * 16
     cfg.class_num = class_num
-    cfg.logger.info('change the class num to: %d' % cfg.class_num)
+    cfg.logger.info('change the class num to: {}'.format(cfg.class_num))
     cfg.logger.info('end create dataloader')
 
     # backbone and loss
@@ -119,7 +119,7 @@ def main():
             else:
                 param_dict_new[key] = values
         load_param_into_net(network, param_dict_new)
-        cfg.logger.info('load model %s success' % cfg.pretrained)
+        cfg.logger.info('load model %s success', cfg.pretrained)
 
     # mixed precision training
     network.add_flags_recursive(fp16=True)

model_zoo/research/nlp/ternarybert/scripts/run_train.sh

@@ -15,7 +15,7 @@
 # ============================================================================
 
 mkdir -p ms_log
-PROJECT_DIR=$(cd "$(dirname "$0")"; pwd)
+PROJECT_DIR=$(cd "$(dirname "$0")" || exit; pwd)
 CUR_DIR=`pwd`
 export GLOG_log_dir=${CUR_DIR}/ms_log
 export GLOG_logtostderr=0