!14889 clean static checking

From: @zhao_ting_v
Reviewed-by: @wuxuejian,@liangchenghui
Signed-off-by: @wuxuejian

model_zoo/official/cv/centerface/dependency/centernet/src/lib/datasets/dataset/coco_hp.py

@@ -28,8 +28,8 @@ from __future__ import print_function
 
 import os
 import numpy as np
-import pycocotools.coco as coco
 import cv2
+import pycocotools.coco as coco
 
 class CenterfaceDataset():
     """

model_zoo/official/cv/cnn_direction_model/src/dataset.py

@@ -16,6 +16,8 @@
 Data operations, will be used in train.py and eval.py
 """
 import os
+import cv2
+import numpy as np
 
 import mindspore.dataset as ds
 import mindspore.dataset.vision.c_transforms as C
@@ -24,9 +26,6 @@ from src.dataset_utils import lucky, noise_blur, noise_speckle, noise_gamma, noi
     randcrop, resize, rdistort, rgeometry, rotate_about_center, whole_rdistort, warp_perspective, random_contrast, \
     unify_img_label
 
-import cv2
-import numpy as np
-
 cv2.setNumThreads(0)
 
 image_height = None

model_zoo/official/cv/cnn_direction_model/train.py

@@ -16,11 +16,6 @@
 import argparse
 import os
 import random
-
-from src.cnn_direction_model import CNNDirectionModel
-from src.config import config1 as config
-from src.dataset import create_dataset_train
-
 import numpy as np
 
 import mindspore as ms
@@ -35,6 +30,10 @@ from mindspore.train.callback import ModelCheckpoint, CheckpointConfig, LossMoni
 from mindspore.train.model import Model, ParallelMode
 from mindspore.train.serialization import load_checkpoint, load_param_into_net
 
+from src.cnn_direction_model import CNNDirectionModel
+from src.config import config1 as config
+from src.dataset import create_dataset_train
+
 parser = argparse.ArgumentParser(description='Image classification')
 parser.add_argument('--run_distribute', type=bool, default=False, help='Run distribute')
 parser.add_argument('--device_num', type=int, default=1, help='Device num.')

model_zoo/official/cv/crnn/src/dataset.py

@@ -15,11 +15,11 @@
 """Dataset preprocessing."""
 import os
 import numpy as np
+from PIL import Image, ImageFile
 import mindspore.common.dtype as mstype
 import mindspore.dataset as ds
 import mindspore.dataset.transforms.c_transforms as C
 import mindspore.dataset.vision.c_transforms as vc
-from PIL import Image, ImageFile
 from src.config import config1, label_dict
 from src.ic03_dataset import IC03Dataset
 from src.ic13_dataset import IC13Dataset

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

@@ -67,13 +67,13 @@ do
     cp ../*.py ./eval
     cp *.sh ./eval
     cp -r ../src ./eval
-    cd ./eval
+    cd ./eval || exit
     env > env.log
     CHECKPOINT_FILE_PATH=$file
     echo "start eval for checkpoint file: ${CHECKPOINT_FILE_PATH}"
     python eval.py --device_id=$DEVICE_ID --image_path=$IMAGE_PATH --dataset_path=$DATASET_PATH --checkpoint_path=$CHECKPOINT_FILE_PATH &> log
     echo "end eval for checkpoint file: ${CHECKPOINT_FILE_PATH}"
-    cd ./submit
+    cd ./submit || exit
     file_base_name=$(basename $file)
     zip -r ../../submit_${file_base_name%.*}.zip *.txt
     cd ../../

model_zoo/official/cv/ctpn/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
@@ -113,9 +113,9 @@ function cal_acc()
     if [ -f "ubmit.zip" ]; then
         rm -f submit.zip
     fi
-    cd output
+    cd output || exit
     zip -r ../submit.zip *.txt
-    cd -
+    cd - || exit
 }
 
 compile_app

model_zoo/official/cv/deeplabv3/ascend310_infer/build.sh

@@ -17,7 +17,8 @@ if [ -d out ]; then
     rm -rf out
 fi
 
-mkdir out && cd out
+mkdir out
+cd out || exit
 
 if [ -f "Makefile" ]; then
   make clean

model_zoo/official/cv/deeplabv3/scripts/run_infer_310.sh

@@ -60,13 +60,13 @@ fi
 
 function compile_app()
 {
-    cd ../ascend310_infer
+    cd ../ascend310_infer || exit
     bash build.sh &> build.log
 }
 
 function infer()
 {
-    cd -
+    cd - || exit
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi

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

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
-path_cur=$(cd "`dirname $0`"; pwd)
+path_cur=$(cd "`dirname $0`" || exit; pwd)
 build_type="Release"
 
 function preparePath() {

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

@@ -67,9 +67,9 @@ 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/faster_rcnn/src/util.py

@@ -15,9 +15,9 @@
 """coco eval for fasterrcnn"""
 import json
 import numpy as np
+import mmcv
 from pycocotools.coco import COCO
 from pycocotools.cocoeval import COCOeval
-import mmcv
 
 _init_value = np.array(0.0)
 summary_init = {

model_zoo/official/cv/inceptionv4/scripts/run_distribute_train_gpu.sh

@@ -18,7 +18,7 @@ rm -rf device
 mkdir device
 cp ./*.py ./device
 cp -r ./src ./device
-cd ./device
+cd ./device || exit
 
 DATA_DIR=$1
 

model_zoo/official/cv/inceptionv4/scripts/run_eval_gpu.sh

@@ -18,7 +18,7 @@ rm -rf evaluation
 mkdir evaluation
 cp ./*.py ./evaluation
 cp -r ./src ./evaluation
-cd ./evaluation
+cd ./evaluation || exit
 
 export DEVICE_ID=0
 export RANK_SIZE=1

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

@@ -13,13 +13,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
-path_cur=$(cd "`dirname $0`"; pwd)
+path_cur=$(cd "`dirname $0`" || exit; pwd)
 build_type="Release"
 
 function preparePath() {
     rm -rf $1
     mkdir -p $1
-    cd $1
+    cd $1 || exit
 }
 
 function buildA300() {

model_zoo/official/cv/maskrcnn/src/dataset.py

@@ -19,13 +19,13 @@ from __future__ import division
 import os
 import numpy as np
 from numpy import random
-
+import cv2
 import mmcv
+
 import mindspore.dataset as de
 import mindspore.dataset.vision.c_transforms as C
 from mindspore.mindrecord import FileWriter
 from src.config import config
-import cv2
 
 def bbox_overlaps(bboxes1, bboxes2, mode='iou'):
     """Calculate the ious between each bbox of bboxes1 and bboxes2.

model_zoo/official/cv/maskrcnn/src/util.py

@@ -15,10 +15,10 @@
 """coco eval for maskrcnn"""
 import json
 import numpy as np
+import mmcv
 from pycocotools.coco import COCO
 from pycocotools.cocoeval import COCOeval
 from pycocotools import mask as maskUtils
-import mmcv
 
 from src.config import config
 

model_zoo/official/cv/maskrcnn_mobilenetv1/src/dataset.py

@@ -19,13 +19,14 @@ from __future__ import division
 import os
 import numpy as np
 from numpy import random
-
 import mmcv
+import cv2
+
 import mindspore.dataset as de
 import mindspore.dataset.vision.c_transforms as C
 from mindspore.mindrecord import FileWriter
 from src.config import config
-import cv2
+
 
 def bbox_overlaps(bboxes1, bboxes2, mode='iou'):
     """Calculate the ious between each bbox of bboxes1 and bboxes2.

model_zoo/official/cv/maskrcnn_mobilenetv1/src/util.py

@@ -15,10 +15,10 @@
 """coco eval for maskrcnn_mobilenetv1"""
 import json
 import numpy as np
+import mmcv
 from pycocotools.coco import COCO
 from pycocotools.cocoeval import COCOeval
 from pycocotools import mask as maskUtils
-import mmcv
 
 from src.config import config
 

model_zoo/official/cv/openpose/eval.py

@@ -18,9 +18,9 @@ import argparse
 import warnings
 import sys
 import numpy as np
-from tqdm import tqdm
 import cv2
 from scipy.ndimage.filters import gaussian_filter
+from tqdm import tqdm
 from pycocotools.coco import COCO as LoadAnn
 from pycocotools.cocoeval import COCOeval as MapEval
 

model_zoo/official/cv/psenet/src/ETSNET/pse/adaptor.cpp

@@ -21,6 +21,7 @@
 #include <iostream>
 #include <queue>
 #include <vector>
+#include <utility>
 #include <opencv2/opencv.hpp>
 #include <opencv2/core/core.hpp>
 #include <opencv2/highgui/highgui.hpp>
@@ -35,21 +36,21 @@ using cv::Point;
 namespace py = pybind11;
 
 namespace pse_adaptor {
-    void get_kernals(const int *data, vector<int64> data_shape, vector<Mat> *kernals) {
+    void get_kernels(const int *data, vector<int64> data_shape, vector<Mat> *kernels) {
         for (int i = 0; i < data_shape[0]; ++i) {
-            Mat kernal = Mat::zeros(data_shape[1], data_shape[2], CV_8UC1);
-            for (int x = 0; x < kernal.rows; ++x) {
-                for (int y = 0; y < kernal.cols; ++y) {
-                    kernal.at<char>(x, y) = data[i * data_shape[1] * data_shape[2] + x * data_shape[2] + y];
+            Mat kernel = Mat::zeros(data_shape[1], data_shape[2], CV_8UC1);
+            for (int x = 0; x < kernel.rows; ++x) {
+                for (int y = 0; y < kernel.cols; ++y) {
+                    kernel.at<char>(x, y) = data[i * data_shape[1] * data_shape[2] + x * data_shape[2] + y];
                 }
             }
-            kernals->emplace_back(kernal);
+            kernels->emplace_back(kernel);
         }
     }
 
-    void growing_text_line(const vector<Mat> &kernals, vector<vector<int>> *text_line, float min_area) {
+    void growing_text_line(const vector<Mat> &kernels, vector<vector<int>> *text_line, float min_area) {
         Mat label_mat;
-        int label_num = connectedComponents(kernals[kernals.size() - 1], label_mat, 4);
+        int label_num = connectedComponents(kernels[kernels.size() - 1], label_mat, 4);
         vector<int> area(label_num + 1, 0);
         for (int x = 0; x < label_mat.rows; ++x) {
             for (int y = 0; y < label_mat.cols; ++y) {
@@ -76,7 +77,7 @@ namespace pse_adaptor {
         int dx[] = {-1, 1, 0, 0};
         int dy[] = {0, 0, -1, 1};
 
-        for (int kernal_id = kernals.size() - 2; kernal_id >= 0; --kernal_id) {
+        for (int kernel_id = kernels.size() - 2; kernel_id >= 0; --kernel_id) {
             while (!queue.empty()) {
                 Point point = queue.front();
                 queue.pop();
@@ -90,7 +91,7 @@ namespace pse_adaptor {
 
                     if (tmp_x < 0 || tmp_x >= static_cast<int>(text_line->size())) continue;
                     if (tmp_y < 0 || tmp_y >= static_cast<int>(text_line->at(1).size())) continue;
-                    if (kernals[kernal_id].at<char>(tmp_x, tmp_y) == 0) continue;
+                    if (kernels[kernel_id].at<char>(tmp_x, tmp_y) == 0) continue;
                     if (text_line->at(tmp_x)[tmp_y] > 0) continue;
 
                     Point point_tmp(tmp_x, tmp_y);
@@ -110,10 +111,10 @@ namespace pse_adaptor {
     vector<vector<int>> pse(py::array_t<int, py::array::c_style | py::array::forcecast> quad_n9, float min_area) {
         auto buf = quad_n9.request();
         auto data = static_cast<int *>(buf.ptr);
-        vector<Mat> kernals;
-        get_kernals(data, buf.shape, &kernals);
+        vector<Mat> kernels;
+        get_kernels(data, buf.shape, &kernels);
         vector<vector<int>> text_line;
-        growing_text_line(kernals, &text_line, min_area);
+        growing_text_line(kernels, &text_line, min_area);
 
         return text_line;
     }

model_zoo/official/cv/psenet/src/dataset.py

@@ -17,17 +17,17 @@
 import math
 import os
 import random
-
-import Polygon as plg
 import cv2
+from PIL import Image
 import numpy as np
+import Polygon as plg
 import pyclipper
-from PIL import Image
-from src.config import config
 
 import mindspore.dataset as ds
 import mindspore.dataset.vision.py_transforms as py_transforms
 
+from src.config import config
+
 __all__ = ['train_dataset_creator', 'test_dataset_creator']
 
 

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

@@ -55,7 +55,7 @@ fi
 
 function compile_app()
 {
-    cd ../ascend310_infer/src/
+    cd ../ascend310_infer/src/ || exit
     if [ -f "Makefile" ]; then
         make clean
     fi
@@ -64,7 +64,7 @@ function compile_app()
 
 function infer()
 {
-    cd -
+    cd - || exit
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi

model_zoo/official/cv/resnet/src/resnet.py

@@ -15,12 +15,12 @@
 """ResNet."""
 import math
 import numpy as np
+from scipy.stats import truncnorm
 import mindspore.nn as nn
 import mindspore.common.dtype as mstype
 from mindspore.ops import operations as P
 from mindspore.ops import functional as F
 from mindspore.common.tensor import Tensor
-from scipy.stats import truncnorm
 
 
 def _conv_variance_scaling_initializer(in_channel, out_channel, kernel_size):

model_zoo/official/cv/resnet/src/resnet_gpu_benchmark.py

@@ -14,11 +14,11 @@
 # ============================================================================
 """ResNet."""
 import numpy as np
+from scipy.stats import truncnorm
 import mindspore.nn as nn
 import mindspore.common.dtype as mstype
 from mindspore.ops import operations as P
 from mindspore.common.tensor import Tensor
-from scipy.stats import truncnorm
 
 format_ = "NHWC"
 # tranpose shape to NCHW, default init is NHWC.

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

@@ -69,7 +69,7 @@ do
     cp ../*.py ./device$i
     cp *.sh ./device$i
     cp -r ../src ./device$i
-    cd ./device$i
+    cd ./device$i || exit
     export DEVICE_ID=$i
     export RANK_ID=$i
     echo "start training for device $i"

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

@@ -60,7 +60,7 @@ mkdir ./train
 cp ../*.py ./train
 cp *.sh ./train
 cp -r ../src ./train
-cd ./train 
+cd ./train || exit
 echo "start training for device $DEVICE_ID"
 env > env.log
 if [ $# == 1 ]

model_zoo/official/cv/resnet152/src/resnet.py

@@ -1,12 +1,12 @@
 """ResNet"""
 
 import numpy as np
+from scipy.stats import truncnorm
 import mindspore.nn as nn
 import mindspore.common.dtype as mstype
 from mindspore.ops import operations as P
 from mindspore.ops import functional as F
 from mindspore.common.tensor import Tensor
-from scipy.stats import truncnorm
 
 
 def _conv_variance_scaling_initializer(in_channel, out_channel, kernel_size):

model_zoo/official/cv/resnext101/src/dataset.py

@@ -16,11 +16,11 @@
 dataset processing.
 """
 import os
+from PIL import Image, ImageFile
 from mindspore.common import dtype as mstype
 import mindspore.dataset as de
 import mindspore.dataset.transforms.c_transforms as C
 import mindspore.dataset.vision.c_transforms as V_C
-from PIL import Image, ImageFile
 from src.utils.sampler import DistributedSampler
 
 ImageFile.LOAD_TRUNCATED_IMAGES = True

model_zoo/official/cv/resnext50/src/dataset.py

@@ -16,11 +16,11 @@
 dataset processing.
 """
 import os
+from PIL import Image, ImageFile
 from mindspore.common import dtype as mstype
 import mindspore.dataset as de
 import mindspore.dataset.transforms.c_transforms as C
 import mindspore.dataset.vision.c_transforms as V_C
-from PIL import Image, ImageFile
 from src.utils.sampler import DistributedSampler
 
 ImageFile.LOAD_TRUNCATED_IMAGES = True

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

@@ -17,7 +17,8 @@ if [ -d out ]; then
     rm -rf out
 fi
 
-mkdir out && cd out
+mkdir out
+cd out || exit
 
 if [ -f "Makefile" ]; then
   make clean

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

@@ -58,13 +58,13 @@ fi
 
 function compile_app()
 {
-    cd ../ascend310_infer
+    cd ../ascend310_infer || exit
     bash build.sh &> build.log
 }
 
 function infer()
 {
-    cd -
+    cd - || exit
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi

model_zoo/official/cv/tinydarknet/scripts/run_standalone_train.sh

@@ -19,5 +19,5 @@ rm -rf ./train_single
 mkdir ./train_single
 cp -r ./src ./train_single
 cp ./train.py ./train_single
-cd ./train_single
+cd ./train_single || exit
 python ./train.py --device_id=$DEVICE_ID > ./train.log 2>&1 &

model_zoo/official/cv/unet/eval.py

@@ -17,6 +17,7 @@ import os
 import argparse
 import logging
 import numpy as np
+from scipy.special import softmax
 import mindspore
 import mindspore.nn as nn
 import mindspore.ops.operations as F
@@ -29,8 +30,6 @@ from src.unet_medical import UNetMedical
 from src.unet_nested import NestedUNet, UNet
 from src.config import cfg_unet
 
-from scipy.special import softmax
-
 device_id = int(os.getenv('DEVICE_ID'))
 context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", save_graphs=False, device_id=device_id)
 

model_zoo/official/cv/unet/postprocess.py

@@ -16,11 +16,10 @@
 import os
 import argparse
 import numpy as np
+from scipy.special import softmax
 
 from src.data_loader import create_dataset
 from src.config import cfg_unet
-from scipy.special import softmax
-
 
 class dice_coeff():
     def __init__(self):

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

@@ -76,7 +76,7 @@ function compile_app()
 
 function infer()
 {
-    cd -
+    cd - || exit
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi

model_zoo/official/cv/unet3d/scripts/run_standalone_eval.sh

@@ -75,7 +75,7 @@ mkdir ./eval
 cp ../*.py ./eval
 cp *.sh ./eval
 cp -r ../src ./eval
-cd ./eval
+cd ./eval || exit
 echo "start eval for checkpoint file: ${CHECKPOINT_FILE_PATH}"
 python eval.py --data_url=$IMAGE_PATH --seg_url=$SEG_PATH --ckpt_path=$CHECKPOINT_FILE_PATH > eval.log 2>&1 &
 echo "end eval for checkpoint file: ${CHECKPOINT_FILE_PATH}"

model_zoo/official/cv/vgg16/src/dataset.py

@@ -16,11 +16,11 @@
 dataset processing.
 """
 import os
+from PIL import Image, ImageFile
 from mindspore.common import dtype as mstype
 import mindspore.dataset as de
 import mindspore.dataset.transforms.c_transforms as C
 import mindspore.dataset.vision.c_transforms as vision
-from PIL import Image, ImageFile
 from src.utils.sampler import DistributedSampler
 
 ImageFile.LOAD_TRUNCATED_IMAGES = True

model_zoo/official/cv/warpctc/src/dataset.py

@@ -16,11 +16,11 @@
 import os
 import math as m
 import numpy as np
+from PIL import Image
 import mindspore.common.dtype as mstype
 import mindspore.dataset as ds
 import mindspore.dataset.transforms.c_transforms as c
 import mindspore.dataset.vision.c_transforms as vc
-from PIL import Image
 from src.config import config as cf
 
 

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

@@ -69,7 +69,7 @@ function compile_app()
 
 function infer()
 {
-    cd -
+    cd - || exit
     if [ -d result_Files ]; then
         rm -rf ./result_Files
     fi

model_zoo/official/nlp/fasttext/scripts/run_distribute_train_8p.sh

@@ -15,7 +15,7 @@
 # ============================================================================
 
 echo "=============================================================================================================="
-echo "Please run the scipt as: "
+echo "Please run the script as: "
 echo "sh run_distributed_train.sh DATASET_PATH RANK_TABLE_PATH"
 echo "for example: sh run_distributed_train.sh /home/workspace/ag /home/workspace/rank_table_file.json"
 echo "It is better to use absolute path."
@@ -53,7 +53,7 @@ for((i=0;i<=7;i++));
 do
     rm -rf ${current_exec_path}/device$i
     mkdir ${current_exec_path}/device$i
-    cd ${current_exec_path}/device$i
+    cd ${current_exec_path}/device$i || exit
     cp ../../*.py ./
     cp -r ../../src ./
     cp -r ../*.sh ./
@@ -61,6 +61,6 @@ do
     export DEVICE_ID=$i
     echo "start training for rank $i, device $DEVICE_ID"
     python ../../train.py --data_path $DATASET --data_name $DATANAME > log_fasttext.log 2>&1 &
-    cd ${current_exec_path}
+    cd ${current_exec_path} || exit
 done
-cd ${current_exec_path}
+cd ${current_exec_path} || exit

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

@@ -14,11 +14,12 @@
 # ============================================================================
 """Data operations, will be used in train.py."""
 
+import numpy as np
 import mindspore.common.dtype as mstype
 import mindspore.dataset as de
 import mindspore.dataset.transforms.c_transforms as deC
 from src.config import config
-import numpy as np
+
 de.config.set_seed(1)
 
 def random_teacher_force(source_ids, target_ids, target_mask):

model_zoo/official/nlp/lstm/script/run_eval_ascend.sh

@@ -26,7 +26,7 @@ CKPT_FILE=$3
 
 rm -rf eval
 mkdir -p eval
-cd eval
+cd eval || exit
 mkdir -p ms_log
 CUR_DIR=`pwd`
 export GLOG_log_dir=${CUR_DIR}/ms_log

model_zoo/official/nlp/lstm/script/run_train_ascend.sh

@@ -25,7 +25,7 @@ ACLIMDB_DIR=$2
 GLOVE_DIR=$3
 
 mkdir -p train
-cd train
+cd train || exit
 mkdir -p ms_log
 CUR_DIR=`pwd`
 export GLOG_log_dir=${CUR_DIR}/ms_log

model_zoo/official/nlp/tinybert/src/gd_config.py

@@ -15,8 +15,8 @@
 """
 network config setting, will be used in dataset.py, run_general_distill.py and run_task_distill.py
 """
-import mindspore.common.dtype as mstype
 from easydict import EasyDict as edict
+import mindspore.common.dtype as mstype
 from .tinybert_model import BertConfig
 
 common_cfg = edict({

model_zoo/official/recommend/naml/ascend310_infer/build.sh

@@ -17,7 +17,7 @@
 if [ ! -d out ]; then
   mkdir out
 fi
-cd out
+cd out || exit
 export CXXFLAGS=-D_GLIBCXX_USE_CXX11_ABI=0
 cmake .. -DCMAKE_CXX_COMPILER=g++ -DCMAKE_SKIP_RPATH=TRUE
 make

model_zoo/official/recommend/naml/script/run_infer_310.sh

@@ -78,7 +78,7 @@ function air_to_om()
 
 function compile_app()
 {
-    cd ../ascend310_infer
+    cd ../ascend310_infer || exit
     if [ -f "Makefile" ]; then
         make clean
     fi
@@ -88,7 +88,7 @@ function compile_app()
         echo "compile app code failed"
         exit 1
     fi
-    cd -
+    cd - || exit
 }
 
 function infer()

model_zoo/research/audio/deepspeech2/src/callback.py

@@ -17,9 +17,9 @@
 Defined callback for DeepSpeech.
 """
 import time
+import numpy as np
 from mindspore.train.callback import Callback
 from mindspore import Tensor
-import numpy as np
 
 
 class TimeMonitor(Callback):

model_zoo/research/audio/wavenet/evaluate.py

@@ -17,10 +17,10 @@ import os
 from os.path import join
 import argparse
 import glob
-from hparams import hparams, hparams_debug_string
-import audio
 import numpy as np
 from scipy.io import wavfile
+from hparams import hparams, hparams_debug_string
+import audio
 from tqdm import tqdm
 from mindspore import context, Tensor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net

model_zoo/research/audio/wavenet/export.py

@@ -17,12 +17,12 @@ import json
 from os.path import join
 import argparse
 from warnings import warn
+import numpy as np
 from hparams import hparams, hparams_debug_string
 from mindspore import context, Tensor
 from mindspore.train.serialization import load_checkpoint, load_param_into_net, export
 from wavenet_vocoder import WaveNet
 from wavenet_vocoder.util import is_mulaw_quantize, is_scalar_input
-import numpy as np
 from src.loss import PredictNet
 
 parser = argparse.ArgumentParser(description='TTS training')

model_zoo/research/audio/wavenet/src/callback.py

@@ -15,9 +15,9 @@
 Defined callback for DeepFM.
 """
 import time
+import numpy as np
 from mindspore.train.callback import Callback
 from mindspore import Tensor
-import numpy as np
 
 
 class TimeMonitor(Callback):

model_zoo/research/audio/wavenet/wavenet_vocoder/conv.py

@@ -15,11 +15,11 @@
 """Extended Conv1D."""
 
 import math
+import numpy as np
 from mindspore import nn, Tensor
 from mindspore.ops import operations as P
 import mindspore.common.dtype as mstype
 from mindspore import context
-import numpy as np
 
 class Conv1d(nn.Conv1d):
     """

model_zoo/research/cv/FaceDetection/scripts/run_distribute_train.sh

@@ -69,7 +69,7 @@ for((i=0;i<=$RANK_SIZE-1;i++));
 do
     echo 'start rank '$i
     mkdir ${current_exec_path}/device$i
-    cd ${current_exec_path}/device$i
+    cd ${current_exec_path}/device$i  || exit
     export RANK_ID=$i
     dev=`expr $i + 0`
     export DEVICE_ID=$dev

model_zoo/research/cv/FaceDetection/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/FaceDetection/scripts/run_export.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/FaceDetection/scripts/run_standalone_train.sh

@@ -66,7 +66,7 @@ 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/eval.py

@@ -17,8 +17,8 @@ import os
 import warnings
 import argparse
 import numpy as np
-from tqdm import tqdm
 import cv2
+from tqdm import tqdm
 
 import mindspore.nn as nn
 from mindspore import Tensor

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

@@ -75,7 +75,7 @@ for((i=0;i<=$RANK_SIZE-1;i++));
 do
     echo 'start rank '$i
     mkdir ${current_exec_path}/device$i
-    cd ${current_exec_path}/device$i
+    cd ${current_exec_path}/device$i || exit
     export RANK_ID=$i
     dev=`expr $i + 0`
     export DEVICE_ID=$dev

model_zoo/research/cv/FaceQualityAssessment/scripts/run_export.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/scripts/run_standalone_train.sh

@@ -72,7 +72,7 @@ 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 {} success'.format(cfg.pretrained))
+        cfg.logger.info('load model %s success' % str(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%s\n' % pformat(arg))
+    arg.logger.info('Config\n\n%s\n' % str(pformat(arg)))
 
     main(arg)

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

@@ -42,7 +42,7 @@ export RANK_SIZE=8
 export RANK_TABLE_FILE=$PATH1
 
 EXECUTE_PATH=$(pwd)
-echo *******************EXECUTE_PATH= $EXECUTE_PATH
+echo *******************EXECUTE_PATH=$EXECUTE_PATH
 if [ -d "${EXECUTE_PATH}/log_parallel_graph" ]; then
   echo "[INFO] Delete old data_parallel log files"
   rm -rf ${EXECUTE_PATH}/log_parallel_graph
@@ -53,7 +53,7 @@ for((i=0;i<=7;i++));
 do
     rm -rf ${EXECUTE_PATH}/data_parallel_log_$i
     mkdir -p ${EXECUTE_PATH}/data_parallel_log_$i
-    cd ${EXECUTE_PATH}/data_parallel_log_$i
+    cd ${EXECUTE_PATH}/data_parallel_log_$i || exit
     export RANK_ID=$i
     export DEVICE_ID=$i
     echo "start training for rank $RANK_ID, device $DEVICE_ID"

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

@@ -42,7 +42,7 @@ export RANK_SIZE=8
 export RANK_TABLE_FILE=$PATH1
 
 EXECUTE_PATH=$(pwd)
-echo *******************EXECUTE_PATH= $EXECUTE_PATH
+echo *******************EXECUTE_PATH=$EXECUTE_PATH
 if [ -d "${EXECUTE_PATH}/log_parallel_graph" ]; then
   echo "[INFO] Delete old data_parallel log files"
   rm -rf ${EXECUTE_PATH}/log_parallel_graph
@@ -53,7 +53,7 @@ for((i=0;i<=7;i++));
 do
     rm -rf ${EXECUTE_PATH}/data_parallel_log_$i
     mkdir -p ${EXECUTE_PATH}/data_parallel_log_$i
-    cd ${EXECUTE_PATH}/data_parallel_log_$i
+    cd ${EXECUTE_PATH}/data_parallel_log_$i || exit
     export RANK_ID=$i
     export DEVICE_ID=$i
     echo "start training for rank $RANK_ID, device $DEVICE_ID"

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

@@ -39,7 +39,7 @@ if [ -d "${EXECUTE_PATH}/log_inference" ]; then
 fi
 mkdir ${EXECUTE_PATH}/log_inference
 
-cd ${EXECUTE_PATH}/log_inference
+cd ${EXECUTE_PATH}/log_inference || exit
 env > ${EXECUTE_PATH}/log_inference/face_recognition.log
 python ${EXECUTE_PATH}/../eval.py &> ${EXECUTE_PATH}/log_inference/face_recognition.log &
 

model_zoo/research/cv/FaceRecognition/scripts/run_export.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/FaceRecognitionForTracking/scripts/run_distribute_train.sh

@@ -75,7 +75,7 @@ for((i=0;i<=$RANK_SIZE-1;i++));
 do
     echo 'start rank '$i
     mkdir ${current_exec_path}/device$i
-    cd ${current_exec_path}/device$i
+    cd ${current_exec_path}/device$i  || exit
     export RANK_ID=$i
     dev=`expr $i + 0`
     export DEVICE_ID=$dev

model_zoo/research/cv/FaceRecognitionForTracking/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/FaceRecognitionForTracking/scripts/run_export.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/FaceRecognitionForTracking/scripts/run_standalone_train.sh

@@ -72,7 +72,7 @@ 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/IPT/src/data/srdata.py

@@ -17,11 +17,9 @@ import os
 import glob
 import random
 import pickle
-
-from src.data import common
-
 import numpy as np
 import imageio
+from src.data import common
 
 
 def search(root, target="JPEG"):

model_zoo/research/cv/IPT/src/metrics.py

@@ -34,7 +34,7 @@ def calc_psnr(sr, hr, scale, rgb_range, y_only=False, dataset=None):
     gray_coeffs = np.array([65.738, 129.057, 25.064]
                            ).reshape((1, 3, 1, 1)) / 256
     diff = np.multiply(diff, gray_coeffs).sum(1)
-    if hr.size == 1:
+    if np.size(hr) == 1:
         return 0
     if scale != 1:
         shave = scale

model_zoo/research/cv/centernet/scripts/run_standalone_eval_ascend.sh

@@ -37,10 +37,10 @@ then
 else
     echo "NMS module was not found, install it now..."
     git clone https://github.com/xingyizhou/CenterNet.git
-    cd CenterNet/src/lib/external/
+    cd CenterNet/src/lib/external/ || exit
     make
     python setup.py install
-    cd -
+    cd - || exit
     rm -rf CenterNet
 fi
 

model_zoo/research/cv/centernet/scripts/run_standalone_eval_cpu.sh

@@ -36,10 +36,10 @@ then
 else
     echo "NMS module was not found, install it now..."
     git clone https://github.com/xingyizhou/CenterNet.git
-    cd CenterNet/src/lib/external/
+    cd CenterNet/src/lib/external/ || exit
     make
     python setup.py install
-    cd -
+    cd - || exit
     rm -rf CenterNet
 fi
 

model_zoo/research/cv/resnet50_adv_pruning/mindpsore_hub_conf.py

@@ -13,9 +13,9 @@
 # limitations under the License.
 # ============================================================================
 """hub config."""
-from src.resnet_imgnet import resnet50
-from mindspore import Tensor
 import numpy as np
+from mindspore import Tensor
+from src.resnet_imgnet import resnet50
 
 
 def get_index(filename):

model_zoo/research/nlp/ternarybert/scripts/run_eval.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

model_zoo/research/nlp/ternarybert/src/config.py

@@ -15,8 +15,8 @@
 
 """config script"""
 
-import mindspore.common.dtype as mstype
 from easydict import EasyDict as edict
+import mindspore.common.dtype as mstype
 from .tinybert_model import BertConfig
 from .assessment_method import Accuracy, F1, Pearsonr, Matthews
 

model_zoo/research/nlp/textrcnn/src/dataset.py

@@ -15,8 +15,8 @@
 """dataset api"""
 import os
 from itertools import chain
-import gensim
 import numpy as np
+import gensim
 
 from mindspore.mindrecord import FileWriter
 import mindspore.dataset as ds

model_zoo/research/nlp/tprr/src/reader_eval.py

@@ -18,8 +18,8 @@ from collections import defaultdict
 import random
 from time import time
 import json
-from tqdm import tqdm
 import numpy as np
+from tqdm import tqdm
 
 from transformers import AlbertTokenizer
 

model_zoo/research/nlp/tprr/src/rerank_and_reader_utils.py

@@ -26,9 +26,9 @@ import gzip
 import string
 import pickle
 import sqlite3
+import numpy as np
 from tqdm import tqdm
 
-import numpy as np
 from transformers import BasicTokenizer
 
 

model_zoo/research/nlp/tprr/src/reranker_eval.py

@@ -18,8 +18,8 @@ import json
 import random
 from collections import defaultdict
 from time import time
-from tqdm import tqdm
 import numpy as np
+from tqdm import tqdm
 
 from mindspore import Tensor, ops
 from mindspore import dtype as mstype