Made add_loss_layer's batch operator() more general.

dlib/dnn/core.h

@@ -1923,12 +1923,13 @@ namespace dlib
             return temp_label;
         }
 
+        template <typename iterable_type>
         std::vector<label_type> operator() (
-            const std::vector<input_type>& data,
+            const iterable_type& data,
             size_t batch_size = 128
         )
         {
-            std::vector<label_type> results(data.size());
+            std::vector<label_type> results(std::distance(data.begin(), data.end()));
             auto o = results.begin();
             for (auto i = data.begin(); i < data.end(); i+=batch_size, o+=batch_size)
             {

dlib/dnn/core_abstract.h

@@ -688,13 +688,17 @@ namespace dlib
                   label_type.
         !*/
 
+        template <typename iterable_type>
         std::vector<label_type> operator() (
-            const std::vector<input_type>& data,
+            const iterable_type& data,
             size_t batch_size = 128
         );
         /*!
             requires
                 - batch_size > 0
+                - data must have a .begin() and .end() that supply iterators over a
+                  sequence of input_type elements.  E.g. data could have a type of
+                  std::vector<input_type>
             ensures
                 - runs all the objects in data through the network and returns their
                   predicted labels.  This means this function returns a vector V such that: