Made layer_details() part of the SUBNET interface so that user defined layer

details objects can access each other.  Also added the input_layer() global
function for accessing the input layer specifically.

dlib/dnn/core.h

@@ -503,9 +503,13 @@ namespace dlib
             subnet_wrapper(const subnet_wrapper&) = delete;
             subnet_wrapper& operator=(const subnet_wrapper&) = delete;
 
-            subnet_wrapper(T& /*l_*/) {}
-            // Nothing here because in this case T is one of the input layer types 
+            subnet_wrapper(T& l_) : l(l_) {}
+            // Not much here because in this case T is one of the input layer types 
             // that doesn't have anything in it.
+            typedef T layer_details_type;
+            const layer_details_type& layer_details() const { return l; }
+        private:
+            T& l;
         };
 
         template <typename T>
@@ -518,12 +522,16 @@ namespace dlib
 
             typedef T wrapped_type;
             const static size_t num_computational_layers = T::num_computational_layers;
+            const static size_t num_layers = T::num_layers;
+            typedef typename T::layer_details_type layer_details_type;
 
             subnet_wrapper(T& l_) : l(l_),subnetwork(l.subnet()) {}
 
             const tensor& get_output() const { return l.private_get_output(); }
             tensor& get_gradient_input() { return l.private_get_gradient_input(); }
 
+            const layer_details_type& layer_details() const { return l.layer_details(); }
+
             const subnet_wrapper<typename T::subnet_type,false>& subnet() const { return subnetwork; }
             subnet_wrapper<typename T::subnet_type,false>& subnet() { return subnetwork; }
 
@@ -542,12 +550,16 @@ namespace dlib
 
             typedef T wrapped_type;
             const static size_t num_computational_layers = T::num_computational_layers;
+            const static size_t num_layers = T::num_layers;
+            typedef typename T::layer_details_type layer_details_type;
 
             subnet_wrapper(T& l_) : l(l_),subnetwork(l.subnet()) {}
 
             const tensor& get_output() const { return l.get_output(); }
             tensor& get_gradient_input() { return l.get_gradient_input(); }
 
+            const layer_details_type& layer_details() const { return l.layer_details(); }
+
             const subnet_wrapper<typename T::subnet_type,false>& subnet() const { return subnetwork; }
             subnet_wrapper<typename T::subnet_type,false>& subnet() { return subnetwork; }
 
@@ -1358,6 +1370,7 @@ namespace dlib
     public:
         typedef SUBNET subnet_type;
         typedef typename subnet_type::input_type input_type;
+        typedef int layer_details_type; // not really used anywhere, but required by subnet_wrapper.
         const static size_t num_layers = subnet_type::num_layers + 1;
         const static size_t num_computational_layers = subnet_type::num_computational_layers;
         const static unsigned int sample_expansion_factor = subnet_type::sample_expansion_factor;
@@ -1554,6 +1567,7 @@ namespace dlib
     public:
         typedef SUBNET subnet_type;
         typedef typename SUBNET::input_type input_type;
+        typedef int layer_details_type; // not really used anywhere, but required by subnet_wrapper.
         const static size_t comp_layers_in_each_group = (REPEATED_LAYER<SUBNET>::num_computational_layers-SUBNET::num_computational_layers);
         const static size_t comp_layers_in_repeated_group = comp_layers_in_each_group*num;
         const static size_t num_computational_layers = comp_layers_in_repeated_group + SUBNET::num_computational_layers;
@@ -1825,6 +1839,7 @@ namespace dlib
     public:
         typedef INPUT_LAYER subnet_type;
         typedef typename subnet_type::input_type input_type;
+        typedef int layer_details_type; // not really used anywhere, but required by subnet_wrapper.
         const static size_t num_computational_layers = 0;
         const static size_t num_layers = 2;
         const static unsigned int sample_expansion_factor = subnet_type::sample_expansion_factor;
@@ -2544,6 +2559,16 @@ namespace dlib
         return impl::layer_helper_match<Match,T,i>::layer(n);
     }
 
+// ----------------------------------------------------------------------------------------
+
+    template <typename net_type>
+    auto input_layer (
+        net_type& net
+    ) -> decltype(layer<net_type::num_layers-1>(net))&
+    {
+        return layer<net_type::num_layers-1>(net);
+    }
+
 // ----------------------------------------------------------------------------------------
 
     template <template<typename> class TAG_TYPE, typename SUBNET>
@@ -2552,6 +2577,7 @@ namespace dlib
     public:
         typedef SUBNET subnet_type;
         typedef typename subnet_type::input_type input_type;
+        typedef int layer_details_type; // not really used anywhere, but required by subnet_wrapper.
         const static size_t num_layers = subnet_type::num_layers + 1;
         const static size_t num_computational_layers = subnet_type::num_computational_layers;
         const static unsigned int sample_expansion_factor = subnet_type::sample_expansion_factor;

dlib/dnn/core_abstract.h

@@ -1332,6 +1332,22 @@ namespace dlib
             - returns layer<i>(layer<Match>(n))
     !*/
 
+// ----------------------------------------------------------------------------------------
+
+    template <typename net_type>
+    auto& input_layer (
+        net_type& net
+    );
+    /*!
+        requires
+            - net_type is an object of type add_layer, add_loss_layer, add_skip_layer, or
+              add_tag_layer.
+        ensures
+            - returns the input later of the given network object.  Specifically, this
+              function is equivalent to calling:
+                layer<net_type::num_layers-1>(net);
+    !*/
+
 // ----------------------------------------------------------------------------------------
 
     template <

dlib/dnn/layers_abstract.h

@@ -82,6 +82,18 @@ namespace dlib
                   above, if *this was layer1 then subnet() would return the network that
                   begins with layer2.
         !*/
+
+        const layer_details_type& layer_details(
+        ) const; 
+        /*!
+            ensures
+                - returns the layer_details_type instance that defines the behavior of the
+                  layer at the top of this network.  I.e. returns the layer details that
+                  defines the behavior of the layer nearest to the network output rather
+                  than the input layer.  For computational layers, this is the object
+                  implementing the EXAMPLE_COMPUTATIONAL_LAYER_ interface that defines the
+                  layer's behavior.
+        !*/
     };
 
 // ----------------------------------------------------------------------------------------