quick cleanup

R/OMLRunParList_Class.R

@@ -28,7 +28,8 @@ makeOMLRunParList = function(mlr.lrn, component = NA_character_) {
   assertClass(mlr.lrn, "Learner")
   assertString(component, na.ok = TRUE)
 
-  if (testClass(mlr.lrn, "TuneWrapper")) mlr.lrn = removeAllHyperPars(mlr.lrn)
+  # FIXME: TuneWrapper contains opt.pars slot. Should we use this here?
+  # if (testClass(mlr.lrn, "TuneWrapper")) mlr.lrn = removeAllHyperPars(mlr.lrn) # looked like a bug
 
   ps = getParamSet(mlr.lrn)
   par.vals = mlr::getHyperPars(mlr.lrn)
@@ -161,8 +162,6 @@ stringToParam = function(par, x) {
     unserialize(charToRaw(x))
 }
 
-
-
 #' @export
 as.data.frame.OMLRunParList = function(x, ...) {
   as.data.frame(convertOMLRunParListToTable(x))

R/chunkOMLlist.R

@@ -24,6 +24,7 @@ chunkOMLlist = function(listfun, ..., total.limit = 100000, chunk.limit = 1000)
   offset = seq(0, total.limit - 1, by = chunk.limit)
   res = vector("list", length(offset))
   for (i in seq_along(offset)) {
+    # use try() to get results until error occurs (we don't know how many results there are in total)
     tmp = try(do.call(listfun, args = c(list(offset = offset[i], limit = chunk.limit), args)))
     if (!(is.error(tmp) || nrow(tmp) == 0)) {
       res[[i]] = tmp

R/convertMlrLearnerToOMLFlow.R

@@ -21,7 +21,7 @@ convertMlrLearnerToOMLFlow = function(lrn, name = paste0("mlr.", lrn$id), descri
   assertClass(lrn, "Learner")
   assertString(name)
 
-  #lrn = removeDefaultsFromParamValues(lrn)
+  # FIXME: for preproc wrappers not all par.vals are deleted due to a mlr bug, see https://github.com/mlr-org/mlr/issues/2218 . However, this is good for us as the uploaded learner at least contains this info.
   lrn = removeAllHyperPars(lrn)
 
   if (is.null(description))
@@ -134,7 +134,7 @@ removeAllHyperPars = function(lrn) {
 # pars
 makeFlowParameterList = function(lrn) {
   par.list = makeFlowParameterListForMlrLearner(lrn)
-  par.list = append(par.list, makeFlowParameterListFor())
+  par.list = append(par.list, makeFlowParameterListForSeed())
   return(par.list)
 }
 
@@ -157,7 +157,7 @@ makeFlowParameterListForMlrLearner = function(lrn) {
 # @title Helper to create parameters for random numbers generator.
 #
 # @return [list] of OMLFlowParameter objects.
-makeFlowParameterListFor = function() {
+makeFlowParameterListForSeed = function() {
   # now handle random numbers generator seeding
   seed.pars = setNames(c(1, RNGkind()), c("openml.seed", "openml.kind", "openml.normal.kind"))
   lapply(seq_along(seed.pars), function(x) {
@@ -167,15 +167,3 @@ makeFlowParameterListFor = function() {
       default.value = seed.pars[x]
   )})
 }
-
-# removeDefaultsFromParamValues = function(lrn) {
-#   par.defaults = getDefaults(getParamSet(lrn))
-#   par.vals = lrn$par.vals
-#   par.ind = vlapply(names(par.vals), function(x) !isTRUE(all.equal(par.defaults[[x]] , par.vals[[x]])))
-#   lrn$par.vals = par.vals[par.ind]
-#
-#   if (!is.null(lrn$next.learner))
-#     lrn$next.learner = removeDefaultsFromParamValues(lrn$next.learner)
-#
-#   return(lrn)
-# }