[coverity] fix coverity issues

 - Added const auto & to avoid copy of an object
 - Added missing lock

Signed-off-by: hyeonseok lee <hs89.lee@samsung.com>

Author: lhs8928

nntrainer/dataset/iteration_queue.cpp

@@ -76,17 +76,17 @@ ScopedView<Sample> IterationQueue::requestEmptySlot() {
     current_iterator++;
   }
 
-  auto view =
-    ScopedView<Sample>(&(*current_iterator),
-                       [current_being_filed = this->being_filled] {
-                         current_being_filed->markSampleFilled();
-                       },
-                       [this, current_being_filled = this->being_filled] {
-                         std::unique_lock lg(empty_mutex);
-                         this->markEmpty(current_being_filled);
-                         num_being_filled--;
-                         notify_emptied_cv.notify_all();
-                       });
+  auto view = ScopedView<Sample>(
+    &(*current_iterator),
+    [current_being_filed = this->being_filled] {
+      current_being_filed->markSampleFilled();
+    },
+    [this, current_being_filled = this->being_filled] {
+      std::unique_lock lg(empty_mutex);
+      this->markEmpty(current_being_filled);
+      num_being_filled--;
+      notify_emptied_cv.notify_all();
+    });
   return view;
 }
 
@@ -168,23 +168,22 @@ void IterationQueue::markEmpty(MarkableIteration *iteration) {
 IterationQueue::MarkableIteration::MarkableIteration(
   const std::vector<ml::train::TensorDim> &input_dims,
   const std::vector<ml::train::TensorDim> &label_dims, IterationQueue *iq) :
-  num_observed(0),
-  iteration(input_dims, label_dims),
-  iq(iq) {}
+  num_observed(0), iteration(input_dims, label_dims), iq(iq) {}
 
 IterationQueue::MarkableIteration::MarkableIteration(MarkableIteration &&rhs) :
-  num_observed(rhs.num_observed),
-  iteration(std::move(rhs.iteration)),
-  iq(rhs.iq) {}
+  iteration(std::move(rhs.iteration)), iq(rhs.iq) {
+  std::lock_guard notify_lock_guard(notify_mutex);
+  num_observed = rhs.num_observed;
+}
 
 void IterationQueue::MarkableIteration::reset() {
   std::lock_guard notify_lock_guard(notify_mutex);
   num_observed = 0;
   iteration.setEndSample();
 }
 
-IterationQueue::MarkableIteration &IterationQueue::MarkableIteration::
-operator=(MarkableIteration &&rhs) {
+IterationQueue::MarkableIteration &
+IterationQueue::MarkableIteration::operator=(MarkableIteration &&rhs) {
   if (this == &rhs) {
     return *this;
   }

test/unittest/models/models_test_utils.cpp

@@ -142,8 +142,9 @@ class IterationForGolden {
     auto to_tensors = [](sharedConstTensors &sts) {
       std::vector<Tensor> ts;
       ts.reserve(sts.size());
-      std::transform(sts.begin(), sts.end(), std::back_inserter(ts),
-                     [](const auto &ts) { return *ts; });
+      std::transform(
+        sts.begin(), sts.end(), std::back_inserter(ts),
+        [](const auto &ts) -> const auto & { return *ts; });
       return ts;
     };
 
@@ -303,17 +304,14 @@ void NodeWatcher::backward(int iteration, bool verify_deriv, bool verify_grad) {
 }
 
 GraphWatcher::GraphWatcher(const std::string &config, const bool opt) :
-  nn(new nntrainer::NeuralNetwork()),
-  expected_losses{},
-  optimize(opt) {
+  nn(new nntrainer::NeuralNetwork()), expected_losses{}, optimize(opt) {
   nn->loadFromConfig(config);
   initialize();
 }
 
 GraphWatcher::GraphWatcher(std::unique_ptr<nntrainer::NeuralNetwork> &&net,
                            const bool opt) :
-  nn(std::move(net)),
-  optimize(opt) {
+  nn(std::move(net)), optimize(opt) {
   initialize();
 }