Nothing
allow_partial_matching = list(
warnPartialMatchArgs = FALSE,
warnPartialMatchAttr = FALSE,
warnPartialMatchDollar = FALSE
)
set_encapsulation = function(learners, encapsulate) {
assert_choice(encapsulate, c(NA_character_, "none", "evaluate", "callr", "try"))
if (!is.na(encapsulate)) {
lapply(learners, function(learner) {
fallback = if (encapsulate != "none") default_fallback(learner)
learner$encapsulate(encapsulate, fallback)
})
}
learners
}
future_map = function(n, FUN, ..., MoreArgs = list()) {
if (getOption("mlr3.debug", FALSE)) {
lg$info("Running experiments sequentially in debug mode with %i iterations", n)
mapply(FUN, ..., MoreArgs = MoreArgs, SIMPLIFY = FALSE, USE.NAMES = FALSE)
} else {
is_sequential = inherits(plan(), "sequential")
scheduling = if (!is_sequential && isTRUE(getOption("mlr3.exec_random", TRUE))) structure(TRUE, ordering = "random") else TRUE
chunk_size = getOption("mlr3.exec_chunk_size", 1)
chunk_bins = getOption("mlr3.exec_chunk_bins")
if (!is.null(chunk_bins)) {
chunk_size = ceiling(n / chunk_bins)
}
stdout = if (is_sequential) NA else TRUE
MoreArgs = c(MoreArgs, list(is_sequential = is_sequential))
lg$debug("Running resample() via future with %i iterations", n)
future.apply::future_mapply(
FUN, ..., MoreArgs = MoreArgs, SIMPLIFY = FALSE, USE.NAMES = FALSE,
future.globals = FALSE, future.packages = "mlr3", future.seed = TRUE,
future.scheduling = scheduling, future.chunk.size = chunk_size, future.stdout = stdout
)
}
}
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