Open
Description
The problem
I'm having trouble with tuning k-means clustering in parallel. Everything works as expected when running sequentially, but in parallel the following warning is returned:
Warning: All models failed. See the `.notes` column.
No error is thrown so the code continues running, but the returned data frame is empty.
Reproducible example
library(doParallel)
#> Loading required package: foreach
#> Loading required package: iterators
#> Loading required package: parallel
library(tidyverse)
#> Warning: package 'tidyverse' was built under R version 4.3.3
#> Warning: package 'ggplot2' was built under R version 4.3.3
#> Warning: package 'tidyr' was built under R version 4.3.3
#> Warning: package 'readr' was built under R version 4.3.3
#> Warning: package 'dplyr' was built under R version 4.3.3
#> Warning: package 'stringr' was built under R version 4.3.3
#> Warning: package 'lubridate' was built under R version 4.3.3
library(tidymodels)
#> Warning: package 'dials' was built under R version 4.3.3
#> Warning: package 'scales' was built under R version 4.3.3
#> Warning: package 'parsnip' was built under R version 4.3.3
#> Warning: package 'recipes' was built under R version 4.3.3
#> Warning: package 'workflows' was built under R version 4.3.3
library(tidyclust)
#> Warning: package 'tidyclust' was built under R version 4.3.3
#>
#> Attaching package: 'tidyclust'
#> The following objects are masked from 'package:parsnip':
#>
#> knit_engine_docs, list_md_problems
library(tune)
my_parallel <- parallel::makePSOCKcluster(parallel::detectCores(logical = FALSE))
doParallel::registerDoParallel(my_parallel)
set.seed(123)
penguin_data <- modeldata::penguins %>% drop_na()
data_form <- ~bill_length_mm + bill_depth_mm
penguin_recipe <- recipe(data_form, data = penguin_data) %>%
step_normalize(all_predictors())
kmeans_spec <- k_means(num_clusters = tune(),
engine = 'stats',
mode = 'partition')
kmeans_wkfl <- workflow() %>%
add_recipe(penguin_recipe) %>%
add_model(kmeans_spec)
cl_resamples <- vfold_cv(penguin_data, v = 2)
cl_grid <- tibble(num_clusters = 1:10)
tuning_result <- tune_cluster(kmeans_wkfl,
resamples = cl_resamples,
grid = cl_grid,
metrics = cluster_metric_set(sse_within_total))
#> Warning: All models failed. See the `.notes` column.tuning_result$.notes
#> [[1]]
#> NULL
#>
#> [[2]]
#> NULLCreated on 2024-04-26 with reprex v2.1.0
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
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#> os Windows 11 x64 (build 22631)
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate English_United States.utf8
#> ctype English_United States.utf8
#> tz America/New_York
#> date 2024-04-26
#> pandoc 3.1.7 @ C:/Users/Kbark/AppData/Local/Pandoc/ (via rmarkdown)
#>
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#>
#> ──────────────────────────────────────────────────────────────────────────────Metadata
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