Added max_pool_ layer.

dlib/dnn/layers.h

@@ -176,6 +176,126 @@ namespace dlib
     template <typename SUBNET>
     using con = add_layer<con_, SUBNET>;
 
+// ----------------------------------------------------------------------------------------
+
+    class max_pool_
+    {
+    public:
+
+        max_pool_ (
+        ) : 
+            _nr(3),
+            _nc(3),
+            _stride_y(1),
+            _stride_x(1)
+        {}
+
+        max_pool_(
+            long nr_,
+            long nc_,
+            int stride_y_ = 1,
+            int stride_x_ = 1
+        ) : 
+            _nr(nr_),
+            _nc(nc_),
+            _stride_y(stride_y_),
+            _stride_x(stride_x_)
+        {}
+
+        long nr() const { return _nr; }
+        long nc() const { return _nc; }
+        long stride_y() const { return _stride_y; }
+        long stride_x() const { return _stride_x; }
+
+        max_pool_ (
+            const max_pool_& item
+        ) : 
+            _nr(item._nr),
+            _nc(item._nc),
+            _stride_y(item._stride_y),
+            _stride_x(item._stride_x)
+        {
+            // this->mp is non-copyable so we have to write our own copy to avoid trying to
+            // copy it and getting an error.
+            mp.setup(_nr, _nc, _stride_y, _stride_x);
+        }
+
+        max_pool_& operator= (
+            const max_pool_& item
+        )
+        {
+            if (this == &item)
+                return *this;
+
+            // this->mp is non-copyable so we have to write our own copy to avoid trying to
+            // copy it and getting an error.
+            _nr = item._nr;
+            _nc = item._nc;
+            _stride_y = item._stride_y;
+            _stride_x = item._stride_x;
+
+            mp.setup(_nr, _nc, _stride_y, _stride_x);
+            return *this;
+        }
+
+        template <typename SUBNET>
+        void setup (const SUBNET& /*sub*/)
+        {
+            mp.setup(_nr, _nc, _stride_y, _stride_x);
+        }
+
+        template <typename SUBNET>
+        void forward(const SUBNET& sub, resizable_tensor& output)
+        {
+            mp(output, sub.get_output());
+        } 
+
+        template <typename SUBNET>
+        void backward(const tensor& computed_output, const tensor& gradient_input, SUBNET& sub, tensor& /*params_grad*/)
+        {
+            mp.get_gradient(gradient_input, computed_output, sub.get_output(), sub.get_gradient_input());
+        }
+
+        const tensor& get_layer_params() const { return params; }
+        tensor& get_layer_params() { return params; }
+
+        friend void serialize(const max_pool_& item, std::ostream& out)
+        {
+            serialize("max_pool_", out);
+            serialize(item._nr, out);
+            serialize(item._nc, out);
+            serialize(item._stride_y, out);
+            serialize(item._stride_y, out);
+        }
+
+        friend void deserialize(max_pool_& item, std::istream& in)
+        {
+            std::string version;
+            deserialize(version, in);
+            if (version != "max_pool_")
+                throw serialization_error("Unexpected version found while deserializing dlib::max_pool_.");
+            deserialize(item._nr, in);
+            deserialize(item._nc, in);
+            deserialize(item._stride_y, in);
+            deserialize(item._stride_y, in);
+
+            item.mp.setup(item._nr, item._nc, item._stride_y, item._stride_x);
+        }
+
+    private:
+
+        long _nr;
+        long _nc;
+        int _stride_y;
+        int _stride_x;
+
+        tt::max_pool mp;
+        resizable_tensor params;
+    };
+
+    template <typename SUBNET>
+    using max_pool = add_layer<max_pool_, SUBNET>;
+
 // ----------------------------------------------------------------------------------------
 
     class bn_

dlib/dnn/layers_abstract.h

@@ -522,7 +522,7 @@ namespace dlib
 
 // ----------------------------------------------------------------------------------------
 
-// TODO, add spec for bn_ and affine_ layers.  
+// TODO, add spec for max_pool_, bn_, and affine_ layers.  
 
 // ----------------------------------------------------------------------------------------