fixed unnecessary conversions in test_solver, and rearraged common.hp…

…p a bit

include/caffe/common.hpp

@@ -6,12 +6,11 @@
 #include <boost/shared_ptr.hpp>
 #include <glog/logging.h>
 
+#include <cmath>
 #include <map>
 #include <set>
 #include <string>
 
-#include <cmath>
-
 #include "caffe/util/device_alternate.hpp"
 
 // Disable the copy and assignment operator for a class.
@@ -73,6 +72,7 @@ using boost::shared_ptr;
 // Common functions and classes from std that caffe often uses.
 using std::fstream;
 using std::ios;
+using std::isnan;
 using std::iterator;
 using std::make_pair;
 using std::map;
@@ -81,7 +81,6 @@ using std::pair;
 using std::set;
 using std::string;
 using std::vector;
-using std::isnan;
 
 // A global initialization function that you should call in your main function.
 // Currently it initializes google flags and google logging.

src/caffe/test/test_solver.cpp

@@ -96,18 +96,14 @@ TYPED_TEST(SolverTest, TestInitTrainTestNets) {
      "  } "
      "} ";
   this->InitSolverFromProtoString(proto);
-  ASSERT_TRUE(static_cast<bool>(this->solver_->net()));
-  EXPECT_TRUE(static_cast<bool>(this->solver_->net()->has_layer("loss")));
-  EXPECT_FALSE(static_cast<bool>(this->solver_->net()->has_layer("accuracy")));
+  ASSERT_TRUE(this->solver_->net() != NULL);
+  EXPECT_TRUE(this->solver_->net()->has_layer("loss"));
+  EXPECT_FALSE(this->solver_->net()->has_layer("accuracy"));
   ASSERT_EQ(2, this->solver_->test_nets().size());
-  EXPECT_TRUE(static_cast<bool>(
-      this->solver_->test_nets()[0]->has_layer("loss")));
-  EXPECT_TRUE(static_cast<bool>(
-      this->solver_->test_nets()[0]->has_layer("accuracy")));
-  EXPECT_FALSE(static_cast<bool>(
-      this->solver_->test_nets()[1]->has_layer("loss")));
-  EXPECT_TRUE(static_cast<bool>(
-      this->solver_->test_nets()[1]->has_layer("accuracy")));
+  EXPECT_TRUE(this->solver_->test_nets()[0]->has_layer("loss"));
+  EXPECT_TRUE(this->solver_->test_nets()[0]->has_layer("accuracy"));
+  EXPECT_FALSE(this->solver_->test_nets()[1]->has_layer("loss"));
+  EXPECT_TRUE(this->solver_->test_nets()[1]->has_layer("accuracy"));
 }
 
 }  // namespace caffe