diff --git a/dlib/cmake b/dlib/cmake
index 33c2edfc3..f851a4ee5 100644
--- a/dlib/cmake
+++ b/dlib/cmake
@@ -78,6 +78,8 @@ elseif (MSVC OR "${CMAKE_CXX_COMPILER_ID}" STREQUAL "MSVC") # else if using Visu
         message(STATUS "Enabling SSE2 instructions")
         add_definitions(-DDLIB_HAVE_SSE2)
     endif()
+	# DNN module produces long type names for NN definitions - disable this warning for MSVC
+	set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4503")
 endif()
 
 
diff --git a/dlib/dnn/layers.h b/dlib/dnn/layers.h
index 355c0c044..d427b58ba 100644
--- a/dlib/dnn/layers.h
+++ b/dlib/dnn/layers.h
@@ -1985,44 +1985,34 @@ namespace dlib
 
 // ----------------------------------------------------------------------------------------
     namespace impl{
-        // helper classes for layer concat processing
-        template <template<typename> class... TAG_TYPES>
-        struct concat_helper_impl {
-        };
-        template <template<typename> class TAG_TYPE>
-        struct concat_helper_impl<TAG_TYPE>{
-            constexpr static size_t tag_count() {return 1;}
-            static void list_tags(std::ostream& out) 
-            { 
-                out << tag_id<TAG_TYPE>::id; 
-            }
-
-            template<typename SUBNET>
-            static void resize_out(resizable_tensor& out, const SUBNET& sub, long sum_k)
-            {
-                auto& t = layer<TAG_TYPE>(sub).get_output();
-                out.set_size(t.num_samples(), t.k() + sum_k, t.nr(), t.nc());
-            }
-            template<typename SUBNET>
-            static void concat(tensor& out, const SUBNET& sub, size_t k_offset)
-            {
-                auto& t = layer<TAG_TYPE>(sub).get_output();
-                tt::copy_tensor(out, k_offset, t, 0, t.k());
-            }
-            template<typename SUBNET>
-            static void split(const tensor& input, SUBNET& sub, size_t k_offset)
-            {
-                auto& t = layer<TAG_TYPE>(sub).get_gradient_input();
-                tt::copy_tensor(t, 0, input, k_offset, t.k());
-            }
-        };
+//        // helper classes for layer concat processing
+//        template <template<typename> class... TAG_TYPES>
+//        struct concat_helper_impl {
+//            // this specialization will be used only by MSVC
+//            constexpr static size_t tag_count() {return 0;}
+//            static void list_tags(std::ostream& out)
+//            {
+//            }
+//            template<typename SUBNET>
+//            static void resize_out(resizable_tensor&, const SUBNET&, long)
+//            {
+//            }
+//            template<typename SUBNET>
+//            static void concat(tensor&, const SUBNET&, size_t)
+//            {
+//            }
+//            template<typename SUBNET>
+//            static void split(const tensor&, SUBNET&, size_t)
+//            {
+//            }
+//        };
         template <template<typename> class TAG_TYPE, template<typename> class... TAG_TYPES>
-        struct concat_helper_impl<TAG_TYPE, TAG_TYPES...>{
+        struct concat_helper_impl{
 
             constexpr static size_t tag_count() {return 1 + concat_helper_impl<TAG_TYPES...>::tag_count();}
-            static void list_tags(std::ostream& out) 
-            { 
-                out << tag_id<TAG_TYPE>::id << ","; 
+            static void list_tags(std::ostream& out)
+            {
+                out << tag_id<TAG_TYPE>::id << (tag_count() > 1 ? "," : "");
                 concat_helper_impl<TAG_TYPES...>::list_tags(out);
             }
 
@@ -2049,6 +2039,33 @@ namespace dlib
                 concat_helper_impl<TAG_TYPES...>::split(input, sub, k_offset);
             }
         };
+        template <template<typename> class TAG_TYPE>
+        struct concat_helper_impl<TAG_TYPE>{
+            constexpr static size_t tag_count() {return 1;}
+            static void list_tags(std::ostream& out) 
+            { 
+                out << tag_id<TAG_TYPE>::id;
+            }
+
+            template<typename SUBNET>
+            static void resize_out(resizable_tensor& out, const SUBNET& sub, long sum_k)
+            {
+                auto& t = layer<TAG_TYPE>(sub).get_output();
+                out.set_size(t.num_samples(), t.k() + sum_k, t.nr(), t.nc());
+            }
+            template<typename SUBNET>
+            static void concat(tensor& out, const SUBNET& sub, size_t k_offset)
+            {
+                auto& t = layer<TAG_TYPE>(sub).get_output();
+                tt::copy_tensor(out, k_offset, t, 0, t.k());
+            }
+            template<typename SUBNET>
+            static void split(const tensor& input, SUBNET& sub, size_t k_offset)
+            {
+                auto& t = layer<TAG_TYPE>(sub).get_gradient_input();
+                tt::copy_tensor(t, 0, input, k_offset, t.k());
+            }
+        };
     }
     // concat layer
     template<