Require passing only out_features to linear2d(); tidy up

Author: milancurcic

example/linear2d.f90

@@ -16,7 +16,7 @@ program linear2d_example
 
   net = network([ &
     input(3, 4), &
-    linear2d(3, 1), &
+    linear2d(1), &
     flatten() &
   ])
 

src/nf/nf_layer_constructors.f90

@@ -185,9 +185,14 @@ module function reshape(output_shape) result(res)
         !! Resulting layer instance
     end function reshape
 
-    module function linear2d(sequence_length, out_features) result(res)
-      integer, intent(in) :: sequence_length, out_features
+    module function linear2d(out_features) result(res)
+      !! Rank-2 (sequence_length, out_features) linear layer constructor.
+      !! sequence_length is determined at layer initialization, based on the
+      !! output shape of the previous layer.
+      integer, intent(in) :: out_features
+        !! Number of output features
       type(layer) :: res
+        !! Resulting layer instance
     end function linear2d
 
   end interface

src/nf/nf_layer_constructors_submodule.f90

@@ -150,13 +150,14 @@ module function reshape(output_shape) result(res)
 
   end function reshape
 
-  module function linear2d(sequence_length, out_features) result(res)
-    integer, intent(in) :: sequence_length, out_features
+
+  module function linear2d(out_features) result(res)
+    integer, intent(in) :: out_features
     type(layer) :: res
 
     res % name = 'linear2d'
-    res % layer_shape = [sequence_length, out_features]
     allocate(res % p, source=linear2d_layer(out_features))
+
   end function linear2d
 
 end submodule nf_layer_constructors_submodule

src/nf/nf_layer_submodule.f90

@@ -301,7 +301,7 @@ impure elemental module subroutine init(self, input)
       call this_layer % init(input % layer_shape)
     end select
 
-    ! The shape of conv2d, maxpool2d, or flatten layers is not known
+    ! The shape of linear2d, conv2d, maxpool2d, or flatten layers is not known
     ! until we receive an input layer.
     select type(this_layer => self % p)
       type is(conv2d_layer)
@@ -310,6 +310,8 @@ impure elemental module subroutine init(self, input)
         self % layer_shape = shape(this_layer % output)
       type is(flatten_layer)
         self % layer_shape = shape(this_layer % output)
+      type is(linear2d_layer)
+        self % layer_shape = shape(this_layer % output)
     end select
 
     self % input_layer_shape = input % layer_shape

src/nf/nf_linear2d_layer.f90

@@ -11,11 +11,11 @@ module nf_linear2d_layer
   type, extends(base_layer) :: linear2d_layer
     integer :: sequence_length, in_features, out_features, batch_size
 
-    real, allocatable :: weights(:, :)
+    real, allocatable :: weights(:,:)
     real, allocatable :: biases(:)
-    real, allocatable :: output(:, :)
-    real, allocatable :: gradient(:, :) ! input gradient
-    real, allocatable :: dw(:, :) ! weight gradients
+    real, allocatable :: output(:,:)
+    real, allocatable :: gradient(:,:) ! input gradient
+    real, allocatable :: dw(:,:) ! weight gradients
     real, allocatable :: db(:) ! bias gradients
 
   contains
@@ -40,13 +40,13 @@ end function linear2d_layer_cons
   interface
     pure module subroutine forward(self, input)
       class(linear2d_layer), intent(in out) :: self
-      real, intent(in) :: input(:, :)
+      real, intent(in) :: input(:,:)
     end subroutine forward
 
     pure module subroutine backward(self, input, gradient)
       class(linear2d_layer), intent(in out) :: self
-      real, intent(in) :: input(:, :)
-      real, intent(in) :: gradient(:, :)
+      real, intent(in) :: input(:,:)
+      real, intent(in) :: gradient(:,:)
     end subroutine backward
 
     module subroutine init(self, input_shape)

src/nf/nf_linear2d_layer_submodule.f90

@@ -10,6 +10,7 @@ module function linear2d_layer_cons(out_features) result(res)
     type(linear2d_layer) :: res
 
     res % out_features = out_features
+
   end function linear2d_layer_cons
 
 
@@ -34,6 +35,7 @@ module subroutine init(self, input_shape)
 
     allocate(self % dw(self % in_features, self % out_features))
     self % dw = 0
+
     allocate(self % db(self % out_features))
     self % db = 0