!10272 fix static check warnings

From: @xutianchun
Reviewed-by: @HilbertDavid
Signed-off-by: @HilbertDavid

mindspore/lite/examples/train_lenet/src/dataset.cc

@@ -15,17 +15,17 @@
  */
 
 #include "src/dataset.h"
-#include <assert.h>
 #include <arpa/inet.h>
 #include <map>
 #include <iostream>
 #include <fstream>
 #include <memory>
+#include "src/utils.h"
 
 using LabelId = std::map<std::string, int>;
 
 char *ReadFile(const std::string &file, size_t *size) {
-  assert(size != nullptr);
+  MS_ASSERT(size != nullptr);
   std::string realPath(file);
   std::ifstream ifs(realPath);
   if (!ifs.good()) {

mindspore/lite/examples/train_lenet/src/net_runner.cc

@@ -20,6 +20,7 @@
 #include <iostream>
 #include <fstream>
 #include "include/context.h"
+#include "src/utils.h"
 
 unsigned int NetRunner::seed_ = time(NULL);
 // Definition of callback function after forwarding operator.
@@ -61,10 +62,10 @@ void NetRunner::InitAndFigureInputs() {
   context.thread_num_ = 1;
 
   session_ = mindspore::session::TrainSession::CreateSession(ms_file_, &context);
-  assert(nullptr != session_);
+  MS_ASSERT(nullptr != session_);
 
   auto inputs = session_->GetInputs();
-  assert(inputs.size() > 1);
+  MS_ASSERT(inputs.size() > 1);
   data_index_ = 0;
   label_index_ = 1;
   batch_size_ = inputs[data_index_]->shape()[0];
@@ -91,8 +92,8 @@ std::vector<int> NetRunner::FillInputData(const std::vector<DataLabelTuple> &dat
   auto inputs = session_->GetInputs();
   char *input_data = reinterpret_cast<char *>(inputs.at(data_index_)->MutableData());
   auto labels = reinterpret_cast<float *>(inputs.at(label_index_)->MutableData());
-  assert(total_size > 0);
-  assert(input_data != nullptr);
+  MS_ASSERT(total_size > 0);
+  MS_ASSERT(input_data != nullptr);
   std::fill(labels, labels + inputs.at(label_index_)->ElementsNum(), 0.f);
   for (int i = 0; i < batch_size_; i++) {
     if (serially) {
@@ -122,7 +123,7 @@ float NetRunner::CalculateAccuracy(int max_tests) const {
     auto labels = FillInputData(test_set, (max_tests == -1));
     session_->RunGraph();
     auto outputsv = SearchOutputsForSize(batch_size_ * num_of_classes_);
-    assert(outputsv != nullptr);
+    MS_ASSERT(outputsv != nullptr);
     auto scores = reinterpret_cast<float *>(outputsv->MutableData());
     for (int b = 0; b < batch_size_; b++) {
       int max_idx = 0;
@@ -147,7 +148,7 @@ int NetRunner::InitDB() {
   num_of_classes_ = ds_.num_of_classes();
   if (ds_.test_data().size() == 0) {
     std::cout << "No relevant data was found in " << data_dir_ << std::endl;
-    assert(ds_.test_data().size() != 0);
+    MS_ASSERT(ds_.test_data().size() != 0);
   }
 
   return ret;
@@ -155,7 +156,7 @@ int NetRunner::InitDB() {
 
 float NetRunner::GetLoss() const {
   auto outputsv = SearchOutputsForSize(1);  // Search for Loss which is a single value tensor
-  assert(outputsv != nullptr);
+  MS_ASSERT(outputsv != nullptr);
   auto loss = reinterpret_cast<float *>(outputsv->MutableData());
   return loss[0];
 }

mindspore/lite/examples/train_lenet/src/utils.h

@@ -0,0 +1,27 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_LITE_EXAMPLES_TRAIN_LENET_SRC_UTILS_H_
+#define MINDSPORE_LITE_EXAMPLES_TRAIN_LENET_SRC_UTILS_H_
+
+#ifdef DEBUG
+#include <cassert>
+#define MS_ASSERT(f) assert(f)
+#else
+#define MS_ASSERT(f) ((void)0)
+#endif
+
+#endif  // MINDSPORE_LITE_EXAMPLES_TRAIN_LENET_SRC_UTILS_H_

mindspore/lite/examples/transfer_learning/src/dataset.cc

@@ -15,13 +15,13 @@
  */
 
 #include "src/dataset.h"
-#include <assert.h>
 #include <dirent.h>
 #include <arpa/inet.h>
 #include <map>
 #include <iostream>
 #include <fstream>
 #include <memory>
+#include "src/utils.h"
 
 #pragma pack(push, 1)
 
@@ -52,7 +52,7 @@ float CH_STD[3] = {0.229, 0.224, 0.225};
 using LabelId = std::map<std::string, int>;
 
 static char *ReadBitmapFile(const std::string &filename, size_t *size) {
-  assert(size != nullptr);
+  MS_ASSERT(size != nullptr);
   *size = 0;
   bmp_header bitmap_header;
   std::ifstream ifs(filename);
@@ -71,7 +71,7 @@ static char *ReadBitmapFile(const std::string &filename, size_t *size) {
   ifs.seekg(bitmap_header.offset, std::ios::beg);
 
   unsigned char *bmp_image = reinterpret_cast<unsigned char *>(malloc(bitmap_header.image_size_bytes));
-  if (!bmp_image) {
+  if (bmp_image == nullptr) {
     ifs.close();
     return nullptr;
   }
@@ -80,7 +80,7 @@ static char *ReadBitmapFile(const std::string &filename, size_t *size) {
 
   size_t buffer_size = bitmap_header.width * bitmap_header.height * 3;
   float *hwc_bin_image = new (std::nothrow) float[buffer_size];
-  if (!hwc_bin_image) {
+  if (hwc_bin_image == nullptr) {
     free(bmp_image);
     ifs.close();
     return nullptr;
@@ -114,7 +114,7 @@ static char *ReadBitmapFile(const std::string &filename, size_t *size) {
 }
 
 char *ReadFile(const std::string &file, size_t *size) {
-  assert(size != nullptr);
+  MS_ASSERT(size != nullptr);
   std::string realPath(file);
   std::ifstream ifs(realPath);
   if (!ifs.good()) {
@@ -203,6 +203,7 @@ std::vector<FileTuple> DataSet::ReadDir(const std::string dpath) {
         }
       }
     }
+    closedir(dp);
   }
   return vec;
 }

mindspore/lite/examples/transfer_learning/src/net_runner.cc

@@ -20,6 +20,7 @@
 #include <iostream>
 #include <fstream>
 #include "include/context.h"
+#include "src/utils.h"
 
 static unsigned int seed = time(NULL);
 
@@ -68,10 +69,10 @@ void NetRunner::InitAndFigureInputs() {
   context.thread_num_ = 1;
 
   session_ = mindspore::session::TrainSession::CreateSession(ms_file_, &context);
-  assert(nullptr != session_);
+  MS_ASSERT(nullptr != session_);
 
   auto inputs = session_->GetInputs();
-  assert(inputs.size() > 1);
+  MS_ASSERT(inputs.size() > 1);
   data_index_ = 0;
   label_index_ = 1;
   batch_size_ = inputs[data_index_]->shape()[0];
@@ -99,8 +100,8 @@ std::vector<int> NetRunner::FillInputData(const std::vector<DataLabelTuple> &dat
   auto inputs = session_->GetInputs();
   char *input_data = reinterpret_cast<char *>(inputs.at(data_index_)->MutableData());
   auto labels = reinterpret_cast<float *>(inputs.at(label_index_)->MutableData());
-  assert(total_size > 0);
-  assert(input_data != nullptr);
+  MS_ASSERT(total_size > 0);
+  MS_ASSERT(input_data != nullptr);
   std::fill(labels, labels + inputs.at(label_index_)->ElementsNum(), 0.f);
   for (int i = 0; i < batch_size_; i++) {
     if (serially >= 0) {
@@ -128,7 +129,7 @@ float NetRunner::CalculateAccuracy(const std::vector<DataLabelTuple> &dataset) c
     auto labels = FillInputData(dataset, i);
     session_->RunGraph();
     auto outputsv = SearchOutputsForSize(batch_size_ * num_of_classes_);
-    assert(outputsv != nullptr);
+    MS_ASSERT(outputsv != nullptr);
     auto scores = reinterpret_cast<float *>(outputsv->MutableData());
     for (int b = 0; b < batch_size_; b++) {
       int max_idx = 0;
@@ -158,7 +159,7 @@ int NetRunner::InitDB() {
 
   if (ds_.test_data().size() == 0) {
     std::cout << "No relevant data was found in " << data_dir_ << std::endl;
-    assert(ds_.test_data().size() != 0);
+    MS_ASSERT(ds_.test_data().size() != 0);
   }
 
   return ret;
@@ -166,7 +167,7 @@ int NetRunner::InitDB() {
 
 float NetRunner::GetLoss() const {
   auto outputsv = SearchOutputsForSize(1);  // Search for Loss which is a single value tensor
-  assert(outputsv != nullptr);
+  MS_ASSERT(outputsv != nullptr);
   auto loss = reinterpret_cast<float *>(outputsv->MutableData());
   return loss[0];
 }

mindspore/lite/examples/transfer_learning/src/utils.h

@@ -0,0 +1,27 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_LITE_EXAMPLES_TRANSFER_LEARNING_SRC_UTILS_H_
+#define MINDSPORE_LITE_EXAMPLES_TRANSFER_LEARNING_SRC_UTILS_H_
+
+#ifdef DEBUG
+#include <cassert>
+#define MS_ASSERT(f) assert(f)
+#else
+#define MS_ASSERT(f) ((void)0)
+#endif
+
+#endif  // MINDSPORE_LITE_EXAMPLES_TRANSFER_LEARNING_SRC_UTILS_H_