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Removed unused variables #238

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Removed unused variables #238

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15 changes: 1 addition & 14 deletions src/nf/nf_conv1d_layer_submodule.f90
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Original file line number Diff line number Diff line change
Expand Up @@ -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(:)

Expand Down Expand Up @@ -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.
Expand All @@ -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

Expand All @@ -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)

Expand All @@ -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
Expand Down
2 changes: 0 additions & 2 deletions src/nf/nf_conv2d_layer_submodule.f90
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Expand Up @@ -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
Expand Down Expand Up @@ -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(:,:,:)
Expand Down
19 changes: 3 additions & 16 deletions src/nf/nf_locally_connected2d_layer_submodule.f90
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Expand Up @@ -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
Expand All @@ -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(:)

Expand Down Expand Up @@ -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
Expand All @@ -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
Expand All @@ -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
Expand Down
4 changes: 0 additions & 4 deletions src/nf/nf_maxpool1d_layer_submodule.f90
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Expand Up @@ -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
Expand All @@ -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(:)

Expand All @@ -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
Expand Down Expand Up @@ -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(:,:)
Expand Down
4 changes: 0 additions & 4 deletions src/nf/nf_maxpool2d_layer_submodule.f90
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Expand Up @@ -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
Expand All @@ -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(:)

Expand All @@ -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
Expand Down Expand Up @@ -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(:,:,:)
Expand Down