Enable network % forward() for 3-d input data

Author: milancurcic

src/nf_network.f90

@@ -11,14 +11,22 @@ module nf_network
   public :: network
 
   type :: network
+
     type(layer), allocatable :: layers(:)
+
   contains
+
     procedure :: backward
-    procedure :: forward
     procedure :: output
     procedure :: print_info
     procedure :: train
     procedure :: update
+
+    procedure, private :: forward_1d
+    procedure, private :: forward_3d
+
+    generic :: forward => forward_1d, forward_3d
+
   end type network
 
   interface network
@@ -32,29 +40,50 @@ module function network_cons(layers) result(res)
     end function network_cons
   end interface network
 
-  interface
+  interface forward
 
-    pure module subroutine backward(self, output)
-      !! Apply one backward pass through the network.
+    pure module subroutine forward_1d(self, input)
+      !! Apply a forward pass through the network.
+      !!
       !! This changes the state of layers on the network.
       !! Typically used only internally from the `train` method,
       !! but can be invoked by the user when creating custom optimizers.
+      !!
+      !! This specific subroutine is for 1-d input data.
       class(network), intent(in out) :: self
         !! Network instance
-      real, intent(in) :: output(:)
-        !! Output data
-    end subroutine backward
+      real, intent(in) :: input(:)
+        !! 1-d input data
+    end subroutine forward_1d
 
-    pure module subroutine forward(self, input)
+    pure module subroutine forward_3d(self, input)
       !! Apply a forward pass through the network.
+      !!
       !! This changes the state of layers on the network.
       !! Typically used only internally from the `train` method,
       !! but can be invoked by the user when creating custom optimizers.
+      !!
+      !! This specific subroutine is for 3-d input data.
       class(network), intent(in out) :: self
         !! Network instance
-      real, intent(in) :: input(:)
-        !! Input data
-    end subroutine forward
+      real, intent(in) :: input(:,:,:)
+        !! 3-d input data
+    end subroutine forward_3d
+
+  end interface forward
+
+  interface
+
+    pure module subroutine backward(self, output)
+      !! Apply one backward pass through the network.
+      !! This changes the state of layers on the network.
+      !! Typically used only internally from the `train` method,
+      !! but can be invoked by the user when creating custom optimizers.
+      class(network), intent(in out) :: self
+        !! Network instance
+      real, intent(in) :: output(:)
+        !! Output data
+    end subroutine backward
 
     module function output(self, input) result(res)
       !! Return the output of the network given the input array.

src/nf_network_submodule.f90

@@ -2,6 +2,7 @@
 
   use nf_dense_layer, only: dense_layer
   use nf_input1d_layer, only: input1d_layer
+  use nf_input3d_layer, only: input3d_layer
   use nf_layer, only: layer
   use nf_loss, only: quadratic_derivative
   use nf_optimizers, only: sgd
@@ -80,7 +81,7 @@ pure module subroutine backward(self, output)
   end subroutine backward
 
 
-  pure module subroutine forward(self, input)
+  pure module subroutine forward_1d(self, input)
     class(network), intent(in out) :: self
     real, intent(in) :: input(:)
     integer :: n
@@ -94,7 +95,24 @@ pure module subroutine forward(self, input)
       call self % layers(n) % forward(self % layers(n - 1))
     end do
 
-  end subroutine forward
+  end subroutine forward_1d
+
+
+  pure module subroutine forward_3d(self, input)
+    class(network), intent(in out) :: self
+    real, intent(in) :: input(:,:,:)
+    integer :: n
+
+    ! Set the input array into the input layer
+    select type(input_layer => self % layers(1) % p); type is(input3d_layer)
+      call input_layer % set(input)
+    end select
+
+    do n = 2, size(self % layers)
+      call self % layers(n) % forward(self % layers(n - 1))
+    end do
+
+  end subroutine forward_3d
 
 
   module function output(self, input) result(res)