Removed unused variables

Author: Vandenplas, Jeremie

src/nf/nf_conv1d_layer_submodule.f90

@@ -20,7 +20,6 @@ module function conv1d_layer_cons(filters, kernel_size, activation) result(res)
   end function conv1d_layer_cons
 
   module subroutine init(self, input_shape)
-    implicit none
     class(conv1d_layer), intent(in out) :: self
     integer, intent(in) :: input_shape(:)
 
@@ -54,16 +53,11 @@ module subroutine init(self, input_shape)
   end subroutine init
 
   pure module subroutine forward(self, input)
-    implicit none
     class(conv1d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:)
-    integer :: input_channels, input_width
     integer :: j, n
     integer :: iws, iwe
 
-    input_channels = size(input, dim=1)
-    input_width = size(input, dim=2)
-
     ! Loop over output positions.
     do j = 1, self % width
       ! Compute the input window corresponding to output index j.
@@ -85,14 +79,12 @@ pure module subroutine forward(self, input)
   end subroutine forward
 
   pure module subroutine backward(self, input, gradient)
-    implicit none
     class(conv1d_layer), intent(in out) :: self
     ! 'input' has shape: (channels, input_width)
     ! 'gradient' (dL/dy) has shape: (filters, output_width)
     real, intent(in) :: input(:,:)
     real, intent(in) :: gradient(:,:)
 
-    integer :: input_channels, input_width, output_width
     integer :: j, n, k
     integer :: iws, iwe
 
@@ -101,11 +93,6 @@ pure module subroutine backward(self, input, gradient)
     real :: db_local(self % filters)
     real :: dw_local(self % filters, self % channels, self % kernel_size)
 
-    ! Determine dimensions.
-    input_channels = size(input, dim=1)
-    input_width = size(input, dim=2)
-    output_width = self % width    ! Note: output_width = input_width - kernel_size + 1
-
     !--- Compute the local gradient gdz = (dL/dy) * sigma'(z) for each output.
     gdz = gradient * self % activation % eval_prime(self % z)
 
@@ -120,7 +107,7 @@ pure module subroutine backward(self, input, gradient)
     ! In the forward pass the window for output index j was:
     !   iws = j,  iwe = j + kernel_size - 1.
     do n = 1, self % filters
-      do j = 1, output_width
+      do j = 1, self % width
         iws = j
         iwe = j + self % kernel_size - 1
         do k = 1, self % channels

src/nf/nf_conv2d_layer_submodule.f90

@@ -62,7 +62,6 @@ end subroutine init
 
 
   pure module subroutine forward(self, input)
-    implicit none
     class(conv2d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:,:)
     integer :: input_width, input_height, input_channels
@@ -113,7 +112,6 @@ end subroutine forward
 
 
   pure module subroutine backward(self, input, gradient)
-    implicit none
     class(conv2d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:,:)
     real, intent(in) :: gradient(:,:,:)

src/nf/nf_locally_connected2d_layer_submodule.f90

@@ -8,7 +8,6 @@
 contains
 
   module function locally_connected2d_layer_cons(filters, kernel_size, activation) result(res)
-    implicit none
     integer, intent(in) :: filters
     integer, intent(in) :: kernel_size
     class(activation_function), intent(in) :: activation
@@ -21,7 +20,6 @@ module function locally_connected2d_layer_cons(filters, kernel_size, activation)
   end function locally_connected2d_layer_cons
 
   module subroutine init(self, input_shape)
-    implicit none
     class(locally_connected2d_layer), intent(in out) :: self
     integer, intent(in) :: input_shape(:)
 
@@ -52,16 +50,11 @@ module subroutine init(self, input_shape)
   end subroutine init
 
   pure module subroutine forward(self, input)
-    implicit none
     class(locally_connected2d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:)
-    integer :: input_channels, input_width
     integer :: j, n
     integer :: iws, iwe
 
-    input_channels = size(input, dim=1)
-    input_width    = size(input, dim=2)
-
     do j = 1, self % width
       iws = j
       iwe = j + self % kernel_size - 1
@@ -73,27 +66,21 @@ pure module subroutine forward(self, input)
   end subroutine forward
 
   pure module subroutine backward(self, input, gradient)
-    implicit none
     class(locally_connected2d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:)
     real, intent(in) :: gradient(:,:)
-    integer :: input_channels, input_width, output_width
     integer :: j, n, k
     integer :: iws, iwe
     real :: gdz(self % filters, self % width)
     real :: db_local(self % filters, self % width)
     real :: dw_local(self % filters, self % width, self % channels, self % kernel_size)
 
-    input_channels = size(input, dim=1)
-    input_width    = size(input, dim=2)
-    output_width   = self % width
-
-    do j = 1, output_width
+    do j = 1, self % width
        gdz(:, j) = gradient(:, j) * self % activation % eval_prime(self % z(:, j))
     end do
 
     do n = 1, self % filters
-       do j = 1, output_width
+       do j = 1, self % width
           db_local(n, j) = gdz(n, j)
        end do
     end do
@@ -102,7 +89,7 @@ pure module subroutine backward(self, input, gradient)
     self % gradient = 0.0
 
     do n = 1, self % filters
-       do j = 1, output_width
+       do j = 1, self % width
           iws = j
           iwe = j + self % kernel_size - 1
           do k = 1, self % channels

src/nf/nf_maxpool1d_layer_submodule.f90

@@ -5,7 +5,6 @@
 contains
 
   pure module function maxpool1d_layer_cons(pool_size, stride) result(res)
-    implicit none
     integer, intent(in) :: pool_size
     integer, intent(in) :: stride
     type(maxpool1d_layer) :: res
@@ -15,7 +14,6 @@ end function maxpool1d_layer_cons
 
 
   module subroutine init(self, input_shape)
-    implicit none
     class(maxpool1d_layer), intent(in out) :: self
     integer, intent(in) :: input_shape(:)
 
@@ -34,7 +32,6 @@ module subroutine init(self, input_shape)
   end subroutine init
 
   pure module subroutine forward(self, input)
-    implicit none
     class(maxpool1d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:)
     integer :: input_width
@@ -70,7 +67,6 @@ pure module subroutine forward(self, input)
   end subroutine forward
 
   pure module subroutine backward(self, input, gradient)
-    implicit none
     class(maxpool1d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:)
     real, intent(in) :: gradient(:,:)

src/nf/nf_maxpool2d_layer_submodule.f90

@@ -5,7 +5,6 @@
 contains
 
   pure module function maxpool2d_layer_cons(pool_size, stride) result(res)
-    implicit none
     integer, intent(in) :: pool_size
     integer, intent(in) :: stride
     type(maxpool2d_layer) :: res
@@ -15,7 +14,6 @@ end function maxpool2d_layer_cons
 
 
   module subroutine init(self, input_shape)
-    implicit none
     class(maxpool2d_layer), intent(in out) :: self
     integer, intent(in) :: input_shape(:)
 
@@ -39,7 +37,6 @@ end subroutine init
 
 
   pure module subroutine forward(self, input)
-    implicit none
     class(maxpool2d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:,:)
     integer :: input_width, input_height
@@ -86,7 +83,6 @@ end subroutine forward
 
 
   pure module subroutine backward(self, input, gradient)
-    implicit none
     class(maxpool2d_layer), intent(in out) :: self
     real, intent(in) :: input(:,:,:)
     real, intent(in) :: gradient(:,:,:)