Fixed compilation errors for Intel compilers (#229)

* Fixed compilation errors for Intel compilers

* Adapt CMakeLists for renamed modules

---------

Co-authored-by: Vandenplas, Jeremie <jeremie.vandenplas@wur.nl>

Author: jvdp1

CMakeLists.txt

@@ -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

src/nf/nf_cross_attention_layer.f90

@@ -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(:, :, :)
@@ -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
@@ -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(:)
 

src/nf/nf_multihead_attention.f90 renamed to src/nf/nf_multihead_attention_layer.f90

@@ -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
@@ -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)
@@ -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(:)