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(v2.1.1.9253) parallel computing
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@ -1589,6 +1589,28 @@ readRDS_AMR <- function(file, refhook = NULL) {
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readRDS(con, refhook = refhook)
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}
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get_n_cores <- function(max_cores = Inf) {
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if (pkg_is_available("parallelly", min_version = "0.8.0", also_load = FALSE)) {
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available_cores <- import_fn("availableCores", "parallelly")
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n_cores <- min(available_cores(), na.rm = TRUE)
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} else {
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# `parallel` is part of base R since 2.14.0, but detectCores() is not very precise on exotic systems like Docker and quota-set Linux environments
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n_cores <- parallel::detectCores()[1]
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if (is.na(n_cores)) {
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n_cores <- 1
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}
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}
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max_cores <- floor(max_cores)
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if (max_cores == 0) {
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n_cores <- 1
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} else if (max_cores < 0) {
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n_cores <- max(1, n_cores - abs(max_cores))
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} else if (max_cores > 0) {
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n_cores <- min(n_cores, max_cores)
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}
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n_cores
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}
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# Faster data.table implementations ----
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match <- function(x, table, ...) {
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