Adding a generalized reshape function with new files

Author: Riccardo231

CMakeLists.txt

@@ -49,6 +49,8 @@ add_library(neural-fortran
   src/nf/nf_parallel.f90
   src/nf/nf_parallel_submodule.f90
   src/nf/nf_random.f90
+  src/nf/nf_reshape_generalized.f90
+  src/nf/nf_reshape_generalized_submodule.f90
   src/nf/nf_reshape_layer.f90
   src/nf/nf_reshape_layer_submodule.f90
   src/nf/io/nf_io_binary.f90

example/cnn_mnist_1d.f90

@@ -20,7 +20,7 @@ program cnn_mnist
 
     net = network([ &
       input(784), &
-      reshape([1,784]), &
+      reshape([1,28,28]), &
       locally_connected_1d(filters=8, kernel_size=2, activation=relu()), &
       dense(10, activation=softmax()) &
     ])

src/nf/nf_layer_constructors.f90

@@ -8,7 +8,7 @@ module nf_layer_constructors
   implicit none
 
   private
-  public :: conv2d, dense, flatten, input, locally_connected_1d, maxpool2d, reshape
+  public :: conv2d, dense, flatten, input, locally_connected_1d, maxpool2d, reshape, reshape_generalized
 
   interface input
 
@@ -193,6 +193,12 @@ module function reshape(output_shape) result(res)
         !! Resulting layer instance
     end function reshape
 
+    module function reshape_generalized(output_shape) result(res)
+      integer, intent(in) :: output_shape
+      type(layer) :: res
+
+    end function reshape_generalized
+
   end interface
 
 end module nf_layer_constructors

src/nf/nf_layer_constructors_submodule.f90

@@ -9,6 +9,7 @@
   use nf_locally_connected_1d_layer, only: locally_connected_1d_layer
   use nf_maxpool2d_layer, only: maxpool2d_layer
   use nf_reshape_layer, only: reshape3d_layer
+  use nf_reshape_layer_generalized, only: reshape_generalized_layer
   use nf_activation, only: activation_function, relu, sigmoid
 
   implicit none
@@ -160,4 +161,15 @@ module function reshape(output_shape) result(res)
 
   end function reshape
 
+  module function reshape_generalized(output_shape) result(res)
+    integer, intent(in) :: output_shape(:)
+    type(layer) :: res
+
+    res % name = 'reshape_generalized'
+    res % layer_shape = output_shape
+
+    allocate(res % p, source=reshape_generalized_layer(output_shape))
+  
+  end function reshape_generalized
+
 end submodule nf_layer_constructors_submodule

src/nf/nf_layer_submodule.f90

@@ -6,6 +6,7 @@
   use nf_flatten_layer, only: flatten_layer
   use nf_input1d_layer, only: input1d_layer
   use nf_input3d_layer, only: input3d_layer
+  use nf_locally_connected_1d_layer, only: locally_connected_1d_layer
   use nf_maxpool2d_layer, only: maxpool2d_layer
   use nf_reshape_layer, only: reshape3d_layer
   use nf_optimizers, only: optimizer_base_type

src/nf/nf_reshape_generalized.f90

@@ -0,0 +1,77 @@
+module nf_reshape_layer_generalized
+
+    !! This module provides the concrete reshape layer type.
+    !! It is used internally by the layer type.
+    !! It is not intended to be used directly by the user.
+  
+    use nf_base_layer, only: base_layer
+  
+    implicit none
+  
+    private
+    public :: reshape_generalized_layer
+  
+    type, extends(base_layer) :: reshape_generalized_layer
+  
+      !! Concrete implementation of a reshape layer type
+      !! It implements reshaping for arbitrary ranks.
+  
+      integer, allocatable :: input_shape(:)
+      integer, allocatable :: output_shape(:)
+      real, allocatable :: gradient(:)
+      real, allocatable :: output(:)
+  
+    contains
+  
+      procedure :: backward
+      procedure :: forward
+      procedure :: init
+  
+    end type reshape_generalized_layer
+  
+    interface reshape_generalized_layer
+      pure module function reshape_layer_cons(output_shape) result(res)
+        !! This function returns the `reshape_layer` instance.
+        integer, intent(in) :: output_shape(:)
+          !! The shape of the output
+        type(reshape_generalized_layer) :: res
+          !! reshape_layer instance
+      end function reshape_layer_cons
+    end interface reshape_generalized_layer
+  
+    interface
+  
+      pure module subroutine backward(self, input, gradient)
+        !! Apply the backward pass for the reshape layer.
+        !! This is just flattening to a rank-1 array.
+        class(reshape_generalized_layer), intent(in out) :: self
+          !! Dense layer instance
+        real, intent(in) :: input(:)
+          !! Input from the previous layer
+        real, intent(in) :: gradient(..)
+          !! Gradient from the next layer
+      end subroutine backward
+  
+      pure module subroutine forward(self, input)
+        !! Apply the forward pass for the reshape layer.
+        !! This is reshaping from input rank to output rank.
+        class(reshape_generalized_layer), intent(in out) :: self
+          !! Dense layer instance
+        real, intent(in) :: input(:)
+          !! Input from the previous layer
+      end subroutine forward
+  
+      module subroutine init(self, input_shape)
+        !! Initialize the layer data structures.
+        !!
+        !! This is a deferred procedure from the `base_layer` abstract type.
+        class(reshape_generalized_layer), intent(in out) :: self
+          !! Dense layer instance
+        integer, intent(in) :: input_shape(:)
+          !! Shape of the input layer
+      end subroutine init
+  
+    end interface
+  
+  end module nf_reshape_layer_generalized
+  

src/nf/nf_reshape_generalized_submodule.f90

@@ -0,0 +1,69 @@
+submodule(nf_reshape_layer_generalized) nf_reshape_layer_generalized_submodule
+
+  use nf_base_layer, only: base_layer
+
+  implicit none
+
+contains
+
+  pure module function reshape_layer_cons(output_shape) result(res)
+    integer, intent(in) :: output_shape(:)
+    type(reshape_generalized_layer) :: res
+    allocate(res % output_shape(size(output_shape)))
+    res % output_shape = output_shape
+  end function reshape_layer_cons
+
+  pure module subroutine backward(self, input, gradient)
+    class(reshape_generalized_layer), intent(in out) :: self
+    real, intent(in) :: input(:)
+    real, intent(in) :: gradient(..)  ! Assumed-rank gradient
+
+    ! Handle different ranks of gradient using SELECT RANK
+    select rank (gradient)
+      rank default
+        error stop "Unsupported gradient rank in reshape layer"
+      rank (0)
+        self % gradient = [gradient]
+      rank (1)
+        self % gradient = gradient
+      rank (2)
+        self % gradient = reshape(gradient, [size(gradient)])
+      rank (3)
+        self % gradient = reshape(gradient, [size(gradient)])
+    end select
+
+  end subroutine backward
+
+  pure module subroutine forward(self, input)
+    class(reshape_generalized_layer), intent(in out) :: self
+    real, intent(in) :: input(:)
+    integer :: i
+  
+    ! Ensure output is allocated
+    if (.not. allocated(self % output)) then
+        allocate(self % output(size(input)))  ! Flattened storage
+    end if
+
+    ! Copy elements manually (assuming Fortran column-major order)
+    do i = 1, size(input)
+        self % output(i) = input(i)
+    end do
+  end subroutine forward
+
+  module subroutine init(self, input_shape)
+    class(reshape_generalized_layer), intent(in out) :: self
+    integer, intent(in) :: input_shape(:)
+    
+    self % input_shape = input_shape
+    
+    ! Allocate gradient buffer based on input size
+    allocate(self % gradient(product(input_shape)))
+    self % gradient = 0
+    
+    ! Allocate output buffer based on output_shape
+    allocate(self % output(product(self % output_shape)))
+    self % output = 0
+  
+  end subroutine init
+
+end submodule nf_reshape_layer_generalized_submodule

src/nf/nf_reshape_layer_submodule.f90

@@ -48,6 +48,4 @@ module subroutine init(self, input_shape)
 
   end subroutine init
 
-  
-
 end submodule nf_reshape_layer_submodule