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Connector between mlr3 and batchtools

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mlr-org/mlr3batchmark

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r-cmd-checkCRAN statusStackOverflowMattermost

A connector betweenmlr3 andbatchtools. This allows to runlarge-scale benchmark experiments on scheduled high-performancecomputing clusters.

The package comes with two core functions for switching betweenmlr3andbatchtools to perform a benchmark:

  • After creating adesign object (as required formlr3’sbenchmark() function), instead ofbenchmark() callbatchmark()which populates anExperimentRegistry for the computational jobsof the benchmark. You are now in the world ofbatchtools where youcan selectively submit jobs with different resources, monitor theprogress or resubmit as needed.
  • After the computations are finished, collect the results withreduceResultsBatchmark() to return tomlr3. The resulting objectis a regularBenchmarkResult.

Example

library("mlr3")library("batchtools")library("mlr3batchmark")tasks= tsks(c("iris","sonar"))learners= lrns(c("classif.featureless","classif.rpart"))resamplings= rsmp("cv",folds=3)design= benchmark_grid(tasks=tasks,learners=learners,resamplings=resamplings)reg= makeExperimentRegistry(NA)
## No readable configuration file found## Created registry in '/tmp/Rtmp8DlMZQ/registry704553adf7a88' using cluster functions 'Interactive'
ids= batchmark(design,reg=reg)
## Adding algorithm 'run_learner'## Adding problem 'b39ef23a66b1f1ee'## Exporting new objects: '5ec484de3f93431b' ...## Exporting new objects: '7c35d835f3dfae37' ...## Exporting new objects: '70dd22724e5c724d' ...## Adding 6 experiments ('b39ef23a66b1f1ee'[1] x 'run_learner'[2] x repls[3]) ...## Adding problem '76c4fc7a533d41b7'## Exporting new objects: 'b209de197d6cbe75' ...## Adding 6 experiments ('76c4fc7a533d41b7'[1] x 'run_learner'[2] x repls[3]) ...
submitJobs()
## Submitting 12 jobs in 12 chunks using cluster functions 'Interactive' ...
getStatus()
## Status for 12 jobs at 2023-11-13 19:32:20:##   Submitted    : 12 (100.0%)##   -- Queued    :  0 (  0.0%)##   -- Started   : 12 (100.0%)##   ---- Running :  0 (  0.0%)##   ---- Done    : 12 (100.0%)##   ---- Error   :  0 (  0.0%)##   ---- Expired :  0 (  0.0%)
reduceResultsBatchmark()
## <BenchmarkResult> of 12 rows with 4 resampling runs##  nr task_id          learner_id resampling_id iters warnings errors##   1    iris classif.featureless            cv     3        0      0##   2    iris       classif.rpart            cv     3        0      0##   3   sonar classif.featureless            cv     3        0      0##   4   sonar       classif.rpart            cv     3        0      0

Resources

  • TheLarge-Scale Benchmarking chapter of themlr3book

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