Add Input2d layer (#198)

* Add Input2d layer by redesigning the input parameters to input layer constructors

* input2d: add forwards and backwards for 2d, create separate `predict_batch` interface

* input2d: add output2d

* input2d: tests

* input2d: update cmake

* input2d: update readme

* Tidy up

* Bump version & update copyright year

* Tidy up

---------

Co-authored-by: Mikhail Voronov <[email protected]>

Author: milancurcic

CMakeLists.txt

@@ -30,6 +30,8 @@ add_library(neural-fortran
   src/nf/nf_flatten_layer_submodule.f90
   src/nf/nf_input1d_layer.f90
   src/nf/nf_input1d_layer_submodule.f90
+  src/nf/nf_input2d_layer.f90
+  src/nf/nf_input2d_layer_submodule.f90
   src/nf/nf_input3d_layer.f90
   src/nf/nf_input3d_layer_submodule.f90
   src/nf/nf_layer_constructors.f90

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2018-2024 neural-fortran contributors
+Copyright (c) 2018-2025 neural-fortran contributors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -29,7 +29,7 @@ Read the paper [here](https://arxiv.org/abs/1902.06714).
 
 | Layer type | Constructor name | Supported input layers | Rank of output array | Forward pass | Backward pass |
 |------------|------------------|------------------------|----------------------|--------------|---------------|
-| Input | `input` | n/a | 1, 3 | n/a | n/a |
+| Input | `input` | n/a | 1, 2, 3 | n/a | n/a |
 | Dense (fully-connected) | `dense` | `input1d`, `flatten` | 1 | ✅ | ✅ |
 | Convolutional (2-d) | `conv2d` | `input3d`, `conv2d`, `maxpool2d`, `reshape` | 3 | ✅ | ✅(*) |
 | Max-pooling (2-d) | `maxpool2d` | `input3d`, `conv2d`, `maxpool2d`, `reshape` | 3 | ✅ | ✅ |

fpm.toml

@@ -1,6 +1,6 @@
 name = "neural-fortran"
-version = "0.18.0"
+version = "0.19.0"
 license = "MIT"
 author = "Milan Curcic"
-maintainer = "[email protected]"
-copyright = "Copyright 2018-2024, neural-fortran contributors"
+maintainer = "[email protected]"
+copyright = "Copyright 2018-2025, neural-fortran contributors"

src/nf/nf_input2d_layer.f90

@@ -0,0 +1,48 @@
+module nf_input2d_layer
+
+  !! This module provides the `input2d_layer` type.
+
+  use nf_base_layer, only: base_layer
+  implicit none
+
+  private
+  public :: input2d_layer
+
+  type, extends(base_layer) :: input2d_layer
+    real, allocatable :: output(:,:)
+  contains
+    procedure :: init
+    procedure :: set
+  end type input2d_layer
+
+  interface input2d_layer
+    pure module function input2d_layer_cons(output_shape) result(res)
+      !! Create a new instance of the 2-d input layer.
+      !! Only used internally by the `layer % init` method.
+      integer, intent(in) :: output_shape(2)
+        !! Shape of the input layer
+      type(input2d_layer) :: res
+        !! 2-d input layer instance
+    end function input2d_layer_cons
+  end interface input2d_layer
+
+  interface
+
+    module subroutine init(self, input_shape)
+      !! Only here to satisfy the language rules
+      !! about deferred methods of abstract types.
+      !! This method does nothing for this type and should not be called.
+      class(input2d_layer), intent(in out) :: self
+      integer, intent(in) :: input_shape(:)
+    end subroutine init
+
+    pure module subroutine set(self, values)
+      class(input2d_layer), intent(in out) :: self
+        !! Layer instance
+      real, intent(in) :: values(:,:)
+        !! Values to set
+    end subroutine set
+
+  end interface
+
+end module nf_input2d_layer 

src/nf/nf_input2d_layer_submodule.f90

@@ -0,0 +1,23 @@
+submodule(nf_input2d_layer) nf_input2d_layer_submodule
+  implicit none
+contains
+
+  pure module function input2d_layer_cons(output_shape) result(res)
+    integer, intent(in) :: output_shape(2)
+    type(input2d_layer) :: res
+    allocate(res % output(output_shape(1), output_shape(2)))
+    res % output = 0
+  end function input2d_layer_cons
+
+  module subroutine init(self, input_shape)
+    class(input2d_layer), intent(in out) :: self
+    integer, intent(in) :: input_shape(:)
+  end subroutine init
+
+  pure module subroutine set(self, values)
+    class(input2d_layer), intent(in out) :: self
+    real, intent(in) :: values(:,:)
+    self % output = values
+  end subroutine set
+
+end submodule nf_input2d_layer_submodule 

src/nf/nf_layer.f90

@@ -35,12 +35,14 @@ module nf_layer
 
     ! Specific subroutines for different array ranks
     procedure, private :: backward_1d
+    procedure, private :: backward_2d
     procedure, private :: backward_3d
     procedure, private :: get_output_1d
+    procedure, private :: get_output_2d
     procedure, private :: get_output_3d
 
-    generic :: backward => backward_1d, backward_3d
-    generic :: get_output => get_output_1d, get_output_3d
+    generic :: backward => backward_1d, backward_2d, backward_3d
+    generic :: get_output => get_output_1d, get_output_2d, get_output_3d
 
   end type layer
 
@@ -59,6 +61,19 @@ pure module subroutine backward_1d(self, previous, gradient)
         !! Array of gradient values from the next layer
     end subroutine backward_1d
 
+    pure module subroutine backward_2d(self, previous, gradient)
+      !! Apply a backward pass on the layer.
+      !! This changes the internal state of the layer.
+      !! This is normally called internally by the `network % backward`
+      !! method.
+      class(layer), intent(in out) :: self
+        !! Layer instance
+      class(layer), intent(in) :: previous
+        !! Previous layer instance
+      real, intent(in) :: gradient(:, :)
+        !! Array of gradient values from the next layer
+    end subroutine backward_2d
+
     pure module subroutine backward_3d(self, previous, gradient)
       !! Apply a backward pass on the layer.
       !! This changes the internal state of the layer.
@@ -95,6 +110,14 @@ pure module subroutine get_output_1d(self, output)
         !! Output values from this layer
     end subroutine get_output_1d
 
+    pure module subroutine get_output_2d(self, output)
+      !! Returns the output values (activations) from this layer.
+      class(layer), intent(in) :: self
+        !! Layer instance
+      real, allocatable, intent(out) :: output(:,:)
+        !! Output values from this layer
+    end subroutine get_output_2d
+
     pure module subroutine get_output_3d(self, output)
       !! Returns the output values (activations) from a layer with a 3-d output
       !! (e.g. input3d, conv2d)

src/nf/nf_layer_constructors.f90

@@ -35,10 +35,10 @@ module function input1d(layer_size) result(res)
         !! Resulting layer instance
     end function input1d
 
-    module function input3d(layer_shape) result(res)
-      !! 3-d input layer constructor.
+    module function input2d(dim1, dim2) result(res)
+      !! 2-d input layer constructor.
       !!
-      !! This layer is for inputting 3-d data to the network.
+      !! This layer is for inputting 2-d data to the network.
       !! Currently, this layer must be followed by a conv2d layer.
       !! An input layer must be the first layer in the network.
       !!
@@ -50,10 +50,29 @@ module function input3d(layer_shape) result(res)
       !! ```
       !! use nf, only :: input, layer
       !! type(layer) :: input_layer
-      !! input_layer = input([28, 28, 1])
+      !! input_layer = input(28, 28)
+      !! ```
+      integer, intent(in) :: dim1, dim2
+        !! First and second dimension sizes
+      type(layer) :: res
+        !! Resulting layer instance
+    end function input2d
+
+    module function input3d(dim1, dim2, dim3) result(res)
+      !! 3-d input layer constructor.
+      !!
+      !! This is a specific function that is available
+      !! under a generic name `input`.
+      !!
+      !! Example:
+      !!
+      !! ```
+      !! use nf, only :: input, layer
+      !! type(layer) :: input_layer
+      !! input_layer = input(28, 28, 1)
       !! ```
-      integer, intent(in) :: layer_shape(3)
-        !! Shape of the input layer
+      integer, intent(in) :: dim1, dim2, dim3
+        !! First, second and third dimension sizes
       type(layer) :: res
         !! Resulting layer instance
     end function input3d

src/nf/nf_layer_constructors_submodule.f90

@@ -5,6 +5,7 @@
   use nf_dense_layer, only: dense_layer
   use nf_flatten_layer, only: flatten_layer
   use nf_input1d_layer, only: input1d_layer
+  use nf_input2d_layer, only: input2d_layer
   use nf_input3d_layer, only: input3d_layer
   use nf_maxpool2d_layer, only: maxpool2d_layer
   use nf_reshape_layer, only: reshape3d_layer
@@ -81,16 +82,28 @@ module function input1d(layer_size) result(res)
   end function input1d
 
 
-  module function input3d(layer_shape) result(res)
-    integer, intent(in) :: layer_shape(3)
+  module function input2d(dim1, dim2) result(res)
+    integer, intent(in) :: dim1, dim2
     type(layer) :: res
     res % name = 'input'
-    res % layer_shape = layer_shape
+    res % layer_shape = [dim1, dim2]
     res % input_layer_shape = [integer ::]
-    allocate(res % p, source=input3d_layer(layer_shape))
+    allocate(res % p, source=input2d_layer([dim1, dim2]))
+    res % initialized = .true.
+  end function input2d
+
+
+  module function input3d(dim1, dim2, dim3) result(res)
+    integer, intent(in) :: dim1, dim2, dim3
+    type(layer) :: res
+    res % name = 'input'
+    res % layer_shape = [dim1, dim2, dim3]
+    res % input_layer_shape = [integer ::]
+    allocate(res % p, source=input3d_layer([dim1, dim2, dim3]))
     res % initialized = .true.
   end function input3d
 
+
   module function maxpool2d(pool_size, stride) result(res)
     integer, intent(in) :: pool_size
     integer, intent(in), optional :: stride
@@ -119,6 +132,7 @@ module function maxpool2d(pool_size, stride) result(res)
 
   end function maxpool2d
 
+
   module function reshape(output_shape) result(res)
     integer, intent(in) :: output_shape(:)
     type(layer) :: res

src/nf/nf_layer_submodule.f90

@@ -5,6 +5,7 @@
   use nf_dense_layer, only: dense_layer
   use nf_flatten_layer, only: flatten_layer
   use nf_input1d_layer, only: input1d_layer
+  use nf_input2d_layer, only: input2d_layer
   use nf_input3d_layer, only: input3d_layer
   use nf_maxpool2d_layer, only: maxpool2d_layer
   use nf_reshape_layer, only: reshape3d_layer
@@ -51,6 +52,18 @@ pure module subroutine backward_1d(self, previous, gradient)
   end subroutine backward_1d
 
 
+  pure module subroutine backward_2d(self, previous, gradient)
+    implicit none
+    class(layer), intent(in out) :: self
+    class(layer), intent(in) :: previous
+    real, intent(in) :: gradient(:,:)
+
+    ! Backward pass from a 2-d layer downstream currently implemented
+    ! only for dense and flatten layers
+    ! CURRENTLY NO LAYERS, tbd: pull/197 and pull/199
+  end subroutine backward_2d
+
+
   pure module subroutine backward_3d(self, previous, gradient)
     implicit none
     class(layer), intent(in out) :: self
@@ -205,6 +218,23 @@ pure module subroutine get_output_1d(self, output)
   end subroutine get_output_1d
 
 
+  pure module subroutine get_output_2d(self, output)
+    implicit none
+    class(layer), intent(in) :: self
+    real, allocatable, intent(out) :: output(:,:)
+
+    select type(this_layer => self % p)
+
+      type is(input2d_layer)
+        allocate(output, source=this_layer % output)
+      class default
+        error stop '1-d output can only be read from an input1d, dense, or flatten layer.'
+
+    end select
+
+  end subroutine get_output_2d
+
+
   pure module subroutine get_output_3d(self, output)
     implicit none
     class(layer), intent(in) :: self
@@ -280,6 +310,8 @@ elemental module function get_num_params(self) result(num_params)
     select type (this_layer => self % p)
       type is (input1d_layer)
         num_params = 0
+      type is (input2d_layer)
+        num_params = 0
       type is (input3d_layer)
         num_params = 0
       type is (dense_layer)
@@ -305,6 +337,8 @@ module function get_params(self) result(params)
     select type (this_layer => self % p)
       type is (input1d_layer)
          ! No parameters to get.
+      type is (input2d_layer)
+         ! No parameters to get.
       type is (input3d_layer)
          ! No parameters to get.
       type is (dense_layer)
@@ -330,6 +364,8 @@ module function get_gradients(self) result(gradients)
     select type (this_layer => self % p)
       type is (input1d_layer)
         ! No gradients to get.
+      type is (input2d_layer)
+        ! No gradients to get.
       type is (input3d_layer)
         ! No gradients to get.
       type is (dense_layer)
@@ -373,6 +409,11 @@ module subroutine set_params(self, params)
         write(stderr, '(a)') 'Warning: calling set_params() ' &
           // 'on a zero-parameter layer; nothing to do.'
 
+      type is (input2d_layer)
+        ! No parameters to set.
+        write(stderr, '(a)') 'Warning: calling set_params() ' &
+          // 'on a zero-parameter layer; nothing to do.'
+
       type is (input3d_layer)
         ! No parameters to set.
         write(stderr, '(a)') 'Warning: calling set_params() ' &