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debugging unusual training and validation sizes in within population CVs
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jeffersonfparil committed Jun 25, 2024
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Expand Up @@ -2355,6 +2355,7 @@ fn_estimate_memory_footprint = function(X, n_models=7, n_folds=10, n_reps=10,
size_total = size_X * n_models * n_folds * n_reps * memory_multiplier
n_threads = floor(as.numeric(gsub(" bytes", "", size_RAM / (size_X * memory_multiplier))))
if (verbose) {
print(paste0("Dimensions of X: = ", paste(dim(X), collapse=" x ")))
print(paste0("Size of X: = ", format(size_X, units="b")))
print(paste0("n_models = ", n_models, "; n_folds = ", n_folds, "; n_reps = ", n_reps))
print(paste0("Total memory requested = ",
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