merged

dlib/dnn/core.h

@@ -1511,7 +1511,7 @@ namespace dlib
 
         // ==================================================================
         // first validate the way the parameter gradients are computed
-        for (long i = 0; i < params_grad.size(); ++i)
+        for (unsigned long i = 0; i < params_grad.size(); ++i)
         {
             layer_details_type l1(l);
 

dlib/dnn/loss.h

@@ -35,7 +35,7 @@ namespace dlib
             DLIB_CASSERT(output_tensor.num_samples()%sample_expansion_factor == 0,"");
 
             const float* out_data = output_tensor.host();
-            for (unsigned long i = 0; i < output_tensor.num_samples(); ++i)
+            for (long i = 0; i < output_tensor.num_samples(); ++i)
             {
                 *iter++ = out_data[i];
             }
@@ -67,7 +67,7 @@ namespace dlib
             double loss = 0;
             const float* out_data = output_tensor.host();
             float* g = grad.host();
-            for (unsigned long i = 0; i < output_tensor.num_samples(); ++i)
+            for (long i = 0; i < output_tensor.num_samples(); ++i)
             {
                 const float y = *truth++;
                 DLIB_CASSERT(y == +1 || y == -1, "y: " << y);

dlib/dnn/trainer.h

@@ -123,7 +123,7 @@ namespace dlib
             {
                 running_stats<double> rs;
 
-                unsigned long j = 0;
+                size_t j = 0;
 
                 // Load two tensors worth of data at once so we can overlap the computation
                 // and data transfer between the host and the device.
@@ -140,7 +140,7 @@ namespace dlib
                     j += mini_batch_size;
                 }
 
-                unsigned long i = 0;
+                size_t i = 0;
                 using namespace std::chrono;
                 auto last_time = system_clock::now();
                 while (i < data.size())
@@ -211,7 +211,7 @@ namespace dlib
             for (unsigned long epoch_iteration = 0; epoch_iteration < num_epochs; ++epoch_iteration)
             {
                 running_stats<double> rs;
-                unsigned long j = 0;
+                size_t j = 0;
 
                 // Load two tensors worth of data at once so we can overlap the computation
                 // and data transfer between the host and the device.
@@ -228,7 +228,7 @@ namespace dlib
                     j += mini_batch_size;
                 }
 
-                unsigned long i = 0;
+                size_t i = 0;
                 using namespace std::chrono;
                 auto last_time = system_clock::now();
                 while (i < data.size())
@@ -318,7 +318,7 @@ namespace dlib
         }
 
         unsigned long num_epochs;
-        unsigned long mini_batch_size;
+        size_t mini_batch_size;
         bool verbose;
 
         net_type net;

dlib/use_cpp_11.cmake

@@ -39,6 +39,7 @@ else()
    if (";${CMAKE_CXX_COMPILE_FEATURES};" MATCHES ";cxx_rvalue_references;" AND
        ";${CMAKE_CXX_COMPILE_FEATURES};" MATCHES ";cxx_variadic_templates;" AND
        ";${CMAKE_CXX_COMPILE_FEATURES};" MATCHES ";cxx_lambdas;" AND
+       ";${CMAKE_CXX_COMPILE_FEATURES};" MATCHES ";cxx_defaulted_move_initializers;" AND
        ";${CMAKE_CXX_COMPILE_FEATURES};" MATCHES ";cxx_auto_type;")
       set(COMPILER_CAN_DO_CPP_11 1)
       # Set which standard to use unless someone has already set it to something