#' @import BBmisc
#' @import checkmate
#' @import mlr
#' @import ParamHelpers
#' @import parallelMap
#' @import utils
NULL
mlr.predictLearner.ModelMultiplexer = NULL
.onLoad = function(libname, pkgname) {
mlrWrappers <<- mlrWrappers.gen()
mlrLearners <<- mlrLearners.gen()
mlrLightweight <<- mlrLightweight.gen()
mlrLightweightNoJava <<- mlrLightweightNoJava.gen()
mlr.predictLearner.ModelMultiplexer <<- mlr:::predictLearner.ModelMultiplexer
timeoutMessage <<- determineTimeoutMessage()
# this is necessary for some linux kernels to prevent segfaults.
# if the JVM is already running, it is too late, however, and we just hope
# the user knows what he's doing.
options(java.parameters = c("-Xss2560k", "-Xmx1g"))
# there is a limit on how many DLLs can be loaded; make sure mlrMBO
# is loaded before the others; same with irace
requirePackages("mlrMBO", why = "optMBO", default.method = "load", stop = FALSE,
suppress.warnings = TRUE)
requirePackages("irace", why = "optMBO", default.method = "load", stop = FALSE,
suppress.warnings = TRUE)
# load the LAPACK DLL
eigen(matrix(1:4, nrow=2))
# load RcppZiggurat, if available
try(RcppZiggurat::zrnorm(1), silent = TRUE)
options(rf.cores=0) # randomForestSRC is bad and should feel bad
options(mc.cores=1)
}
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