init_neural_operator Subroutine

  subroutine init_neural_operator(this, input_shape, verbose)
    !! Initialise neural operator layer
    implicit none

    ! Arguments
    class(neural_operator_layer_type), intent(inout) :: this
    !! Instance of the neural operator layer
    integer, dimension(:), intent(in) :: input_shape
    !! Input shape
    integer, optional, intent(in) :: verbose
    !! Verbosity level

    ! Local variables
    integer :: num_inputs
    !! Effective fan-in for initialisation
    integer :: verbose_ = 0


    !---------------------------------------------------------------------------
    ! Initialise optional arguments
    !---------------------------------------------------------------------------
    if(present(verbose)) verbose_ = verbose


    !---------------------------------------------------------------------------
    ! Initialise number of inputs
    !---------------------------------------------------------------------------
    if(.not.allocated(this%input_shape)) call this%set_shape(input_shape)
    this%num_inputs = this%input_shape(1)
    this%output_shape = [this%num_outputs]
    this%num_params = this%get_num_params()


    !---------------------------------------------------------------------------
    ! Allocate parameters
    !
    ! params(1): W        (n_out x n_in)  - local transform weights
    ! params(2): W_k      (n_out x 1)     - integral kernel coupling weights
    ! params(3): b        (n_out)         - bias  [only when use_bias=.true.]
    !---------------------------------------------------------------------------
    allocate(this%weight_shape(2,1))
    this%weight_shape(:,1) = [ this%num_outputs, this%num_inputs ]

    if(this%use_bias)then
       this%bias_shape = [ this%num_outputs ]
       allocate(this%params(3))
    else
       allocate(this%params(2))
    end if

    ! W: local transform  (n_out x n_in)
    call this%params(1)%allocate([this%weight_shape(:,1), 1])
    call this%params(1)%set_requires_grad(.true.)
    this%params(1)%fix_pointer = .true.
    this%params(1)%is_sample_dependent = .false.
    this%params(1)%is_temporary = .false.

    ! W_k: integral kernel coupling  (n_out x 1)
    call this%params(2)%allocate([this%num_outputs, 1, 1])
    call this%params(2)%set_requires_grad(.true.)
    this%params(2)%fix_pointer = .true.
    this%params(2)%is_sample_dependent = .false.
    this%params(2)%is_temporary = .false.

    num_inputs = this%num_inputs
    if(this%use_bias)then
       num_inputs = this%num_inputs + 1
       call this%params(3)%allocate([this%bias_shape, 1])
       call this%params(3)%set_requires_grad(.true.)
       this%params(3)%fix_pointer = .true.
       this%params(3)%is_sample_dependent = .false.
       this%params(3)%is_temporary = .false.
    end if


    !---------------------------------------------------------------------------
    ! Initialise W with kernel initialiser
    !---------------------------------------------------------------------------
    call this%kernel_init%initialise( &
         this%params(1)%val(:,1), &
         fan_in = num_inputs, fan_out = this%num_outputs, &
         spacing = [ this%num_outputs ] &
    )

    !---------------------------------------------------------------------------
    ! Initialise W_k with kernel initialiser (smaller scale), treating it as
    ! a rank-1 integral correction so fan_in=1
    !---------------------------------------------------------------------------
    call this%kernel_init%initialise( &
         this%params(2)%val(:,1), &
         fan_in = num_inputs, fan_out = this%num_outputs, &
         spacing = [ this%num_outputs ] &
    )

    !---------------------------------------------------------------------------
    ! Initialise bias if used
    !---------------------------------------------------------------------------
    if(this%use_bias)then
       call this%bias_init%initialise( &
            this%params(3)%val(:,1), &
            fan_in = num_inputs, fan_out = this%num_outputs &
       )
    end if


    !---------------------------------------------------------------------------
    ! Allocate output and pre-activation arrays
    !---------------------------------------------------------------------------
    if(allocated(this%output)) deallocate(this%output)
    allocate(this%output(1,1))
    if(this%z(1)%allocated) call this%z(1)%deallocate()

  end subroutine init_neural_operator