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rdllmlr3

Error in UUIDgenerate() : Too many DLL modules. in mlr3 pakcage

I using the mlr3 package for autotuning ML models (mlr3pipelines graph, to be more correct).

It is very hard to reproduce the problem because the error occurs occasionally. The same code sometimes returns an error and sometimes doesn't.

Here is the code snippet

learners_l = list(
  ranger = lrn("classif.ranger", predict_type = "prob", id = "ranger"),
  log_reg = lrn("classif.log_reg", predict_type = "prob", id = "log_reg")
)

# create complete grapg
graph = po("removeconstants", ratio = 0.05) %>>%
  po("branch", options = c("nop_prep", "yeojohnson", "pca", "ica"), id = "prep_branch") %>>%
  gunion(list(po("nop", id = "nop_prep"), po("yeojohnson"), po("pca", scale. = TRUE), po("ica"))) %>>%
  po("unbranch", id = "prep_unbranch") %>>%
  learners_l %>>%
  po("classifavg", innum = length(learners))
graph_learner = as_learner(graph)
search_space = ps(
  prep_branch.selection = p_fct(levels = c("nop_prep", "yeojohnson", "pca", "ica")),
  pca.rank. = p_int(2, 6, depends = prep_branch.selection == "pca"),
  ica.n.comp = p_int(2, 6, depends = prep_branch.selection == "ica"),
  yeojohnson.standardize = p_lgl(depends = prep_branch.selection == "yeojohnson"),
  ranger.ranger.mtry.ratio = p_dbl(0.2, 1),
  ranger.ranger.max.depth = p_int(2, 6)
)
at_classif = auto_tuner(
  method = "random_search",
  learner = graph_learner,
  resampling = rsmp("cv", folds = 3),
  measure = msr("classif.acc"),
  search_space = search_space,
  term_evals = 20
)
at_classif$train(task_classif)

You can use any task you want. The error I get is:

INFO  [15:05:33.610] [bbotk] Starting to optimize 6 parameter(s) with '<OptimizerRandomSearch>' and '<TerminatorEvals> [n_evals=20, k=0]' 
INFO  [15:05:33.653] [bbotk] Evaluating 1 configuration(s) 
Error in UUIDgenerate() : Too many DLL modules.
Solution

  • There is a fixed buffer for loading RNG functions in uuid which will fail if there are too many DLLs loaded already. A simple work-around is to run

    library(uuid)
UUIDgenerate()

    before other packages which will force the loading of the RNG functions early.

    (#12 now tracks the underlying issue and should be fixed in uuid 1.0-3).