diff --git a/DESCRIPTION b/DESCRIPTION index 9ba0dd9d..0d66cdb9 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -93,6 +93,7 @@ Collate: 'AcqFunctionStochasticEI.R' 'AcqOptimizer.R' 'mlr_acqoptimizers.R' + 'AcqOptimizerCmaes.R' 'AcqOptimizerDirect.R' 'AcqOptimizerLbfgsb.R' 'AcqOptimizerLocalSearch.R' diff --git a/NAMESPACE b/NAMESPACE index 4c4fdb41..bfb0279e 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -23,6 +23,7 @@ export(AcqFunctionSmsEgo) export(AcqFunctionStochasticCB) export(AcqFunctionStochasticEI) export(AcqOptimizer) +export(AcqOptimizerCmaes) export(AcqOptimizerDirect) export(AcqOptimizerLbfgsb) export(AcqOptimizerLocalSearch) diff --git a/R/AcqOptimizerCmaes.R b/R/AcqOptimizerCmaes.R new file mode 100644 index 00000000..c5130b81 --- /dev/null +++ b/R/AcqOptimizerCmaes.R @@ -0,0 +1,147 @@ +#' @title CMA-ES Acquisition Function Optimizer +#' +#' @include AcqOptimizer.R mlr_acqoptimizers.R +#' +#' @description +#' CMA-ES acquisition function optimizer. +#' Calls `cmaes()` from \CRANpkg{libcmaesr}. +#' The default algorithm is `"abipop"` with unlimited restarts and a budget of `100 * D^2` function evaluations, where `D` is the dimension of the search space. +#' For the meaning of the control parameters, see `libcmaesr::cmaes_control()`. +#' +#' @section Termination Parameters: +#' The following termination parameters can be used. +#' +#' \describe{ +#' \item{`max_fevals`}{`integer(1)`\cr +#' Maximum number of function evaluations. +#' Deactivate with `NA`. +#' Default is `100 * D^2`, where `D` is the dimension of the search space.} +#' \item{`max_iter`}{`integer(1)`\cr +#' Maximum number of iterations. +#' Deactivate with `NA`.} +#' \item{`ftarget`}{`numeric(1)`\cr +#' Target function value. +#' Deactivate with `NA`.} +#' \item{`f_tolerance`}{`numeric(1)`\cr +#' Function tolerance. +#' Deactivate with `NA`.} +#' \item{`x_tolerance`}{`numeric(1)`\cr +#' Parameter tolerance. +#' Deactivate with `NA`.} +#' } +#' +#' @export +#' @examples +#' if (requireNamespace("libcmaesr")) { +#' acqo("cmaes") +#' } +AcqOptimizerCmaes = R6Class("AcqOptimizerCmaes", + inherit = AcqOptimizer, + public = list( + + #' @description + #' Creates a new instance of this [R6][R6::R6Class] class. + #' + #' @param acq_function (`NULL` | [AcqFunction]). + initialize = function(acq_function = NULL) { + self$acq_function = assert_r6(acq_function, "AcqFunction", null.ok = TRUE) + param_set = ps( + algo = p_fct(init = "abipop", levels = c( + "cmaes", + "ipop", + "bipop", + "acmaes", + "aipop", + "abipop", + "sepcmaes", + "sepipop", + "sepbipop", + "sepacmaes", + "sepaipop", + "sepabipop", + "vdcma", + "vdipopcma", + "vdbipopcma")), + lambda = p_int(lower = 1L, default = NA_integer_, special_vals = list(NA_integer_)), + sigma = p_dbl(default = NA_real_, special_vals = list(NA_real_)), + max_restarts = p_int(lower = 1L, special_vals = list(NA), init = 1e5L), + tpa = p_int(default = NA_integer_, special_vals = list(NA_integer_)), + tpa_dsigma = p_dbl(default = NA_real_, special_vals = list(NA_real_)), + seed = p_int(default = NA_integer_, special_vals = list(NA_integer_)), + quiet = p_lgl(default = FALSE), + # internal termination criteria + max_fevals = p_int(lower = 1L, special_vals = list(NA_integer_)), + max_iter = p_int(lower = 1L, default = NA_integer_, special_vals = list(NA_integer_)), + ftarget = p_dbl(default = NA_real_, special_vals = list(NA_real_)), + f_tolerance = p_dbl(default = NA_real_, special_vals = list(NA_real_)), + x_tolerance = p_dbl(default = NA_real_, special_vals = list(NA_real_)), + catch_errors = p_lgl(init = TRUE) + ) + private$.param_set = param_set + }, + + #' @description + #' Optimize the acquisition function. + #' + #' @return [data.table::data.table()] with 1 row per candidate. + optimize = function() { + pv = self$param_set$values + + if (is.null(pv$max_fevals)) { + pv$max_fevals = 100 * self$acq_function$domain$length^2 + } + + fun = get_private(self$acq_function)$.fun + constants = self$acq_function$constants$values + direction = self$acq_function$codomain$direction + + control = invoke(libcmaesr::cmaes_control, maximize = direction == -1L, .args = pv[names(pv) %in% formalArgs(libcmaesr::cmaes_control)]) + + wrapper = function(xmat) { + xdt = set_names(as.data.table(xmat), self$acq_function$domain$ids()) + mlr3misc::invoke(fun, xdt = xdt, .args = constants)[[1]] + } + + lower = self$acq_function$domain$lower + upper = self$acq_function$domain$upper + x0 = as.numeric(self$acq_function$archive$best()[, self$acq_function$domain$ids(), with = FALSE]) + + # add saveguard_epsilon to x0 + saveguard_epsilon = 1e-5 + x0[x0 < lower] = x0[x0 < lower] + saveguard_epsilon + x0[x0 > upper] = x0[x0 > upper] - saveguard_epsilon + + optimize = function() { + libcmaesr::cmaes( + objective = wrapper, + x0 = x0, + lower = lower, + upper = upper, + batch = TRUE, + control = control) + } + + if (pv$catch_errors) { + tryCatch({ + res = optimize() + }, error = function(error_condition) { + lg$warn(error_condition$message) + stop(set_class(list(message = error_condition$message, call = NULL), classes = c("acq_optimizer_error", "mbo_error", "error", "condition"))) + }) + } else { + res = optimize() + } + as.data.table(as.list(set_names(c(res$x, res$y * direction), c(self$acq_function$domain$ids(), self$acq_function$codomain$ids())))) + } + ), + + active = list( + #' @template field_print_id + print_id = function(rhs) { + assert_ro_binding(rhs) + "(OptimizerBatchCmaes)" + } + ) +) + +mlr_acqoptimizers$add("cmaes", AcqOptimizerCmaes) diff --git a/man/AcqOptimizerCmaes.Rd b/man/AcqOptimizerCmaes.Rd new file mode 100644 index 00000000..276fc26f --- /dev/null +++ b/man/AcqOptimizerCmaes.Rd @@ -0,0 +1,116 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/AcqOptimizerCmaes.R +\name{AcqOptimizerCmaes} +\alias{AcqOptimizerCmaes} +\title{CMA-ES Acquisition Function Optimizer} +\description{ +CMA-ES acquisition function optimizer. +Calls \code{cmaes()} from \CRANpkg{libcmaesr}. +The default algorithm is \code{"abipop"} with unlimited restarts and a budget of \code{100 * D^2} function evaluations, where \code{D} is the dimension of the search space. +For the meaning of the control parameters, see \code{libcmaesr::cmaes_control()}. +} +\section{Termination Parameters}{ + +The following termination parameters can be used. + +\describe{ +\item{\code{max_fevals}}{\code{integer(1)}\cr +Maximum number of function evaluations. +Deactivate with \code{NA}. +Default is \code{100 * D^2}, where \code{D} is the dimension of the search space.} +\item{\code{max_iter}}{\code{integer(1)}\cr +Maximum number of iterations. +Deactivate with \code{NA}.} +\item{\code{ftarget}}{\code{numeric(1)}\cr +Target function value. +Deactivate with \code{NA}.} +\item{\code{f_tolerance}}{\code{numeric(1)}\cr +Function tolerance. +Deactivate with \code{NA}.} +\item{\code{x_tolerance}}{\code{numeric(1)}\cr +Parameter tolerance. +Deactivate with \code{NA}.} +} +} + +\examples{ +if (requireNamespace("libcmaesr")) { + acqo("cmaes") +} +} +\section{Super class}{ +\code{\link[mlr3mbo:AcqOptimizer]{mlr3mbo::AcqOptimizer}} -> \code{AcqOptimizerCmaes} +} +\section{Active bindings}{ +\if{html}{\out{
}} +\describe{ +\item{\code{print_id}}{(\code{character})\cr +Id used when printing.} +} +\if{html}{\out{
}} +} +\section{Methods}{ +\subsection{Public methods}{ +\itemize{ +\item \href{#method-AcqOptimizerCmaes-new}{\code{AcqOptimizerCmaes$new()}} +\item \href{#method-AcqOptimizerCmaes-optimize}{\code{AcqOptimizerCmaes$optimize()}} +\item \href{#method-AcqOptimizerCmaes-clone}{\code{AcqOptimizerCmaes$clone()}} +} +} +\if{html}{\out{ +
Inherited methods + +
+}} +\if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AcqOptimizerCmaes-new}{}}} +\subsection{Method \code{new()}}{ +Creates a new instance of this \link[R6:R6Class]{R6} class. +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{AcqOptimizerCmaes$new(acq_function = NULL)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{acq_function}}{(\code{NULL} | \link{AcqFunction}).} +} +\if{html}{\out{
}} +} +} +\if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AcqOptimizerCmaes-optimize}{}}} +\subsection{Method \code{optimize()}}{ +Optimize the acquisition function. +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{AcqOptimizerCmaes$optimize()}\if{html}{\out{
}} +} + +\subsection{Returns}{ +\code{\link[data.table:data.table]{data.table::data.table()}} with 1 row per candidate. +} +} +\if{html}{\out{
}} +\if{html}{\out{}} +\if{latex}{\out{\hypertarget{method-AcqOptimizerCmaes-clone}{}}} +\subsection{Method \code{clone()}}{ +The objects of this class are cloneable with this method. +\subsection{Usage}{ +\if{html}{\out{
}}\preformatted{AcqOptimizerCmaes$clone(deep = FALSE)}\if{html}{\out{
}} +} + +\subsection{Arguments}{ +\if{html}{\out{
}} +\describe{ +\item{\code{deep}}{Whether to make a deep clone.} +} +\if{html}{\out{
}} +} +} +} diff --git a/tests/testthat/test_AcqOptimizerCmaes.R b/tests/testthat/test_AcqOptimizerCmaes.R new file mode 100644 index 00000000..3a1e9baf --- /dev/null +++ b/tests/testthat/test_AcqOptimizerCmaes.R @@ -0,0 +1,45 @@ +test_that("AcqOptimizerCmaes works", { + instance = oi(OBJ_1D, terminator = trm("evals", n_evals = 5L)) + design = generate_design_grid(instance$search_space, resolution = 4L)$data + instance$eval_batch(design) + + surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive) + acqfun = acqf("ei", surrogate = surrogate) + acqopt = AcqOptimizerCmaes$new(acq_function = acqfun) + acqopt$param_set$set_values(max_fevals = 100L) + acqfun$surrogate$update() + acqfun$update() + expect_data_table(acqopt$optimize(), nrows = 1L) + expect_list(acqopt$state) +}) + +test_that("AcqOptimizerCmaes works with 2D", { + instance = oi(OBJ_2D, terminator = trm("evals", n_evals = 5L)) + design = generate_design_grid(instance$search_space, resolution = 4L)$data + instance$eval_batch(design) + + surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive) + acqfun = acqf("ei", surrogate = surrogate) + acqopt = AcqOptimizerCmaes$new(acq_function = acqfun) + acqopt$param_set$set_values(max_fevals = 100L) + acqfun$surrogate$update() + acqfun$update() + expect_data_table(acqopt$optimize(), nrows = 1L) + expect_list(acqopt$state) + expect_list(acqopt$state) +}) + +test_that("AcqOptimizerCmaes works with instance", { + instance = oi(OBJ_1D, terminator = trm("evals", n_evals = 10L)) + design = generate_design_grid(instance$search_space, resolution = 4L)$data + instance$eval_batch(design) + + surrogate = srlrn(REGR_KM_DETERM, archive = instance$archive) + acqfun = acqf("ei", surrogate = surrogate) + acqopt = AcqOptimizerCmaes$new(acq_function = acqfun) + acqopt$param_set$set_values(max_fevals = 100L) + + optimizer = opt("mbo", acq_optimizer = acqopt, acq_function = acqfun, surrogate = surrogate) + expect_data_table(optimizer$optimize(instance), nrow = 1L) +}) +