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Fixed compilation errors for Intel compilers #229

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Merged
merged 2 commits into from
Sep 4, 2025
Merged

Fixed compilation errors for Intel compilers #229

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1151e60
Fixed compilation errors for Intel compilers
Aug 31, 2025
0aa8ee4
Adapt CMakeLists for renamed modules
Aug 31, 2025
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4 changes: 2 additions & 2 deletions CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -56,8 +56,8 @@ add_library(neural-fortran
src/nf/nf_maxpool2d_layer.f90
src/nf/nf_maxpool2d_layer_submodule.f90
src/nf/nf_metrics.f90
src/nf/nf_multihead_attention.f90
src/nf/nf_multihead_attention_submodule.f90
src/nf/nf_multihead_attention_layer.f90
src/nf/nf_multihead_attention_layer_submodule.f90
src/nf/nf_network.f90
src/nf/nf_network_submodule.f90
src/nf/nf_optimizers.f90
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14 changes: 5 additions & 9 deletions src/nf/nf_cross_attention_layer.f90
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Expand Up @@ -20,22 +20,18 @@ module nf_cross_attention_layer
end type cross_attention_layer

interface cross_attention_layer
module function cross_attention_layer_cons(n_heads) result(res)
!! This function returns the `cross_attention_layer` instance.
integer, intent(in) :: sequence_length, model_dimension, n_heads
type(cross_attention_layer) :: res
end function cross_attention_layer_cons
module procedure cross_attention_layer_cons
end interface cross_attention_layer

contains
module function cross_attention_layer_cons(n_heads) result(res)
function cross_attention_layer_cons(n_heads) result(res)
!! This function returns the `cross_attention_layer` instance.
integer, intent(in) :: n_heads
type(cross_attention_layer) :: res
res % n_heads = n_heads
end function cross_attention_layer_cons

pure module subroutine backward(self, input, gradient)
pure subroutine backward(self, input, gradient)
!! Cross Attention Back propagation
class(cross_attention_layer), intent(in out) :: self
real, intent(in) :: input(:, :, :)
Expand All @@ -46,7 +42,7 @@ pure module subroutine backward(self, input, gradient)
self % gradient(2, :, :) = self % key_layer % gradient + self % value_layer % gradient
end subroutine backward

pure module subroutine forward(self, input)
pure subroutine forward(self, input)
!! Cross Attention Forward propagation
!! Input Shape (kind, sequence_length, model_dimension)
!! where kind is 1 for Query and 2 for Key-Value
Expand All @@ -56,7 +52,7 @@ pure module subroutine forward(self, input)
call self % common_forward(input(1, :, :), input(2, :, :), input(2, :, :))
end subroutine forward

module subroutine init(self, input_shape)
subroutine init(self, input_shape)
class(cross_attention_layer), intent(in out) :: self
integer, intent(in) :: input_shape(:)

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0 src/nf/nf_multihead_attention.f90 → src/nf/nf_multihead_attention_layer.f90
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0 src/nf/nf_multihead_attention_submodule.f90 → ...f_multihead_attention_layer_submodule.f90
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14 changes: 5 additions & 9 deletions src/nf/nf_self_attention_layer.f90
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Expand Up @@ -20,22 +20,18 @@ module nf_self_attention_layer
end type self_attention_layer

interface self_attention_layer
module function self_attention_layer_cons(n_heads) result(res)
!! This function returns the `self_attention_layer` instance.
integer, intent(in) :: n_heads
type(self_attention_layer) :: res
end function self_attention_layer_cons
module procedure self_attention_layer_cons
end interface self_attention_layer

contains
module function self_attention_layer_cons(n_heads) result(res)
function self_attention_layer_cons(n_heads) result(res)
!! This function returns the `self_attention_layer` instance.
integer, intent(in) :: n_heads
type(self_attention_layer) :: res
res % n_heads = n_heads
end function self_attention_layer_cons

pure module subroutine backward(self, input, gradient, attention_mask)
pure subroutine backward(self, input, gradient, attention_mask)
!! Self Attention back propagation
!! Returns sum of Query, Key and Value gradients
class(self_attention_layer), intent(in out) :: self
Expand All @@ -50,7 +46,7 @@ pure module subroutine backward(self, input, gradient, attention_mask)
+ self % value_layer % gradient
end subroutine backward

pure module subroutine forward(self, input)
pure subroutine forward(self, input)
!! Cross Attention forward propagation
!! Passes input three times into MultiHead Attention
!! Input Shape: (sequence_length, model_dimension)
Expand All @@ -60,7 +56,7 @@ pure module subroutine forward(self, input)
call self % common_forward(input, input, input)
end subroutine forward

module subroutine init(self, input_shape)
subroutine init(self, input_shape)
class(self_attention_layer), intent(in out) :: self
integer, intent(in) :: input_shape(:)

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