Addition of the MSE loss function

src/nf.f90

@@ -4,6 +4,7 @@ module nf
   use nf_layer, only: layer
   use nf_layer_constructors, only: &
     conv2d, dense, flatten, input, maxpool2d, reshape
+  use nf_loss, only: mse, quadratic
   use nf_network, only: network
   use nf_optimizers, only: sgd, rmsprop, adam, adagrad
   use nf_activation, only: activation_function, elu, exponential,  &

src/nf/nf_loss.f90

@@ -8,6 +8,7 @@ module nf_loss
 
   private
   public :: loss_type
+  public :: mse
   public :: quadratic
 
   type, abstract :: loss_type
@@ -29,6 +30,12 @@ pure function loss_derivative_interface(true, predicted) result(res)
     end function loss_derivative_interface
   end interface
 
+  type, extends(loss_type) :: mse
+  contains
+    procedure, nopass :: eval => mse_eval
+    procedure, nopass :: derivative => mse_derivative
+  end type mse
+
   type, extends(loss_type) :: quadratic
   contains
     procedure, nopass :: eval => quadratic_eval
@@ -37,6 +44,32 @@ end function loss_derivative_interface
 
   interface
 
+    pure module function mse_eval(true, predicted) result(res)
+      !! Mean Square Error loss function:
+      !!
+      !!   L  = sum((predicted - true)**2) / size(true)
+      !!
+      real, intent(in) :: true(:)
+        !! True values, i.e. labels from training datasets
+      real, intent(in) :: predicted(:)
+        !! Values predicted by the network
+      real :: res
+        !! Resulting loss value
+    end function mse_eval
+
+    pure module function mse_derivative(true, predicted) result(res)
+      !! First derivative of the Mean Square Error loss function:
+      !!
+      !!   L  = 2 * (predicted - true) / size(true)
+      !!
+      real, intent(in) :: true(:)
+        !! True values, i.e. labels from training datasets
+      real, intent(in) :: predicted(:)
+        !! Values predicted by the network
+      real :: res(size(true))
+        !! Resulting loss values
+    end function mse_derivative
+
     pure module function quadratic_eval(true, predicted) result(res)
       !! Quadratic loss function:
       !!
@@ -47,7 +80,7 @@ pure module function quadratic_eval(true, predicted) result(res)
       real, intent(in) :: predicted(:)
         !! Values predicted by the network
       real :: res
-        !! Resulting loss values
+        !! Resulting loss value
     end function quadratic_eval
 
     pure module function quadratic_derivative(true, predicted) result(res)

src/nf/nf_loss_submodule.f90

@@ -18,4 +18,18 @@ pure module function quadratic_derivative(true, predicted) result(res)
     res = predicted - true
   end function quadratic_derivative
 
+  pure module function mse_eval(true, predicted) result(res)
+    real, intent(in) :: true(:)
+    real, intent(in) :: predicted(:)
+    real :: res
+    res = sum((predicted - true)**2) / size(true)
+  end function mse_eval
+
+  pure module function mse_derivative(true, predicted) result(res)
+    real, intent(in) :: true(:)
+    real, intent(in) :: predicted(:)
+    real :: res(size(true))
+    res = 2 * (predicted - true) / size(true)
+  end function mse_derivative
+
 end submodule nf_loss_submodule