Fixed bug in scale_ layer that would trigger when the num_samples() dimension

of a tensor changed.  I.e. if you ran mini-batches with different sample sizes
you would get an assert triggering.  This has been fixed.

dlib/dnn/layers.h

@@ -2287,11 +2287,8 @@ namespace dlib
         }
 
         template <typename SUBNET>
-        void setup (const SUBNET& sub)
+        void setup (const SUBNET& /*sub*/)
         {
-            auto&& src = sub.get_output();
-            reshape_scales = alias_tensor(src.num_samples()*src.k());
-            reshape_src = alias_tensor(src.num_samples()*src.k(),src.nr()*src.nc());
         }
 
         template <typename SUBNET>
@@ -2320,6 +2317,12 @@ namespace dlib
             // read from.
             tt::scale_channels(true, layer<tag>(sub).get_gradient_input(), gradient_input, scales);
 
+            if (reshape_src.num_samples() != src.num_samples())
+            {
+                reshape_scales = alias_tensor(src.num_samples()*src.k());
+                reshape_src = alias_tensor(src.num_samples()*src.k(),src.nr()*src.nc());
+            }
+
             auto&& scales_grad = sub.get_gradient_input();
             auto sgrad = reshape_scales(scales_grad);
             tt::dot_prods(true, sgrad, reshape_src(src), reshape_src(gradient_input));