From 2f34414e494ef364cd52927764cbc959cf048bdf Mon Sep 17 00:00:00 2001
From: Davis King <davis@dlib.net>
Date: Tue, 8 Dec 2015 21:32:48 -0500
Subject: [PATCH] Added affine_ layer.

---
 dlib/dnn/layers.h | 81 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 81 insertions(+)

diff --git a/dlib/dnn/layers.h b/dlib/dnn/layers.h
index 2033c0d9c..39b6aa0d3 100644
--- a/dlib/dnn/layers.h
+++ b/dlib/dnn/layers.h
@@ -423,6 +423,87 @@ namespace dlib
     template <typename SUBNET>
     using dropout = add_layer<dropout_, SUBNET>;
 
+// ----------------------------------------------------------------------------------------
+
+    class affine_
+    {
+    public:
+        affine_(
+        ) 
+        {
+        }
+
+        template <typename SUBNET>
+        void setup (const SUBNET& sub)
+        {
+            gamma = alias_tensor(1,
+                            sub.get_output().k(),
+                            sub.get_output().nr(),
+                            sub.get_output().nc());
+            beta = gamma;
+
+            params.set_size(gamma.size()+beta.size());
+
+            gamma(params,0) = 1;
+            beta(params,gamma.size()) = 0;
+        }
+
+        void forward_inplace(const tensor& input, tensor& output)
+        {
+            auto g = gamma(params,0);
+            auto b = beta(params,gamma.size());
+            tt::affine_transform(output, input, g, b);
+        } 
+
+        void backward_inplace(
+            const tensor& computed_output,
+            const tensor& gradient_input, 
+            tensor& data_grad, 
+            tensor& params_grad
+        )
+        {
+            auto g = gamma(params,0);
+            auto b = beta(params,gamma.size());
+            auto g_grad = gamma(params_grad,0);
+            auto b_grad = beta(params_grad,gamma.size());
+
+            // We are computing the gradient of dot(gradient_input, computed_output*g + b)
+            tt::multiply(data_grad, gradient_input, g);
+
+            tt::multiply(g_grad, gradient_input, computed_output);
+            tt::add_bias_gradient(b_grad, gradient_input);
+        }
+
+        const tensor& get_layer_params() const { return params; }
+        tensor& get_layer_params() { return params; }
+
+        friend void serialize(const affine_& item, std::ostream& out)
+        {
+            serialize("affine_", out);
+            serialize(item.params, out);
+            serialize(item.gamma, out);
+            serialize(item.beta, out);
+        }
+
+        friend void deserialize(affine_& item, std::istream& in)
+        {
+            std::string version;
+            deserialize(version, in);
+            if (version != "affine_")
+                throw serialization_error("Unexpected version found while deserializing dlib::affine_.");
+            deserialize(item.params, in);
+            deserialize(item.gamma, in);
+            deserialize(item.beta, in);
+        }
+
+    private:
+        resizable_tensor params; 
+        alias_tensor gamma, beta;
+    };
+
+    template <typename SUBNET>
+    using affine = add_layer<affine_, SUBNET>;
+
 // ----------------------------------------------------------------------------------------
 
     class relu_