minimise_adagrad Subroutine

  pure subroutine minimise_adagrad(this, param, gradient)
    !! Apply gradients to parameters to minimise loss using Adagrad optimiser
    implicit none

    ! Arguments
    class(adagrad_optimiser_type), intent(inout) :: this
    !! Instance of the Adagrad optimiser
    real(real32), dimension(:), intent(inout) :: param
    !! Parameters
    real(real32), dimension(:), intent(inout) :: gradient
    !! Gradients

    real(real32) :: learning_rate
    !! Learning rate


    ! Decay learning rate and update iteration
    learning_rate = this%lr_decay%get_lr(this%learning_rate, this%iter)

    ! Apply regularisation
    if(this%regularisation) &
         call this%regulariser%regularise( param, gradient, learning_rate )

    this%sum_squares = this%sum_squares + gradient ** 2._real32

    ! Update parameters
    param = param - learning_rate * gradient / &
         (sqrt(this%sum_squares + this%epsilon))
  end subroutine minimise_adagrad