parsnip could not locate an implementation for boost_tree regression model specifications using the catboost engine.

[vidarsumo]

The problem

I'm unable to tune catboost (and lightgbm) in parallel using tune_race_anova. Both work sequentially. I've had this problem before but then I solved it with parsnip::set_dependency.
I get the same error when using tune_grid(). However, if I install development version of parsinp then tune_grid() works in parallel but tune_race_anova still fails with the same message.

I've tried to add catboost and treesnip to the pkgs argument in control_race without success.

This also seems to be connected to Windows as I was able to run this using docker.

Reproducible example

library(tidymodels)
library(catboost)
library(treesnip)

data_use_tbl <- mtcars %>% 
  as_tibble()

resamples <- data_use_tbl %>% vfold_cv()

rec <- recipe(mpg ~ ., data = data_use_tbl)

boost_spec <- boost_tree(
  mode = "regression",
  trees = tune(),
  learn_rate = tune()
) %>% 
  set_engine("catboost", allow_writing_files = FALSE)

wflw <- workflow() %>% 
  add_recipe(rec) %>% 
  add_model(boost_spec)


set.seed(124)

parsnip::set_dependency("boost_tree", eng = "catboost", pkg = "catboost", mode = "regression")
parsnip::set_dependency("boost_tree", eng = "catboost", pkg = "treesnip", mode = "regression")

doParallel::registerDoParallel()

tune_results <- finetune::tune_race_anova(
  object     = wflw,
  resamples  = resamples,
  grid       = 30,
  control    = finetune::control_race(allow_par = TRUE, verbose = TRUE)
)
#> Warning: All models failed. Run `show_notes(.Last.tune.result)` for more
#> information.
#> Error in `test_parameters_gls()`:
#> ! There were no valid metrics for the ANOVA model.
#> Backtrace:
#>     ▆
#>  1. ├─finetune::tune_race_anova(...)
#>  2. └─finetune:::tune_race_anova.workflow(...)
#>  3.   └─finetune:::tune_race_anova_workflow(...)
#>  4.     └─finetune:::test_parameters_gls(res, control$alpha)
#>  5.       └─rlang::abort("There were no valid metrics for the ANOVA model.")

foreach::registerDoSEQ()
gc()
#>           used  (Mb) gc trigger  (Mb) max used  (Mb)
#> Ncells 2640292 141.1    4318425 230.7  4318425 230.7
#> Vcells 4517022  34.5   10146329  77.5  7006457  53.5

^{Created on 2023-08-31 with reprex v2.0.2}

────────────────────────────────────────────────────────────────────────
Error:
! parsnip could not locate an implementation for `boost_tree` regression
  model specifications using the `catboost` engine.
> sessioninfo::session_info()
─ Session info ────────────────────────────────────────────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.3.1 (2023-06-16 ucrt)
 os       Windows 10 x64 (build 19045)
 system   x86_64, mingw32
 ui       RStudio
 language (EN)
 collate  Icelandic_Iceland.utf8
 ctype    Icelandic_Iceland.utf8
 tz       Atlantic/Reykjavik
 date     2023-08-31
 rstudio  2023.06.1+524 Mountain Hydrangea (desktop)
 pandoc   NA

─ Packages ────────────────────────────────────────────────────────────────────────────────────────────────────────
 package      * version    date (UTC) lib source
 backports      1.4.1      2021-12-13 [1] CRAN (R 4.2.0)
 broom        * 1.0.5      2023-06-09 [1] CRAN (R 4.3.0)
 cachem         1.0.8      2023-05-01 [1] CRAN (R 4.3.0)
 callr          3.7.3      2022-11-02 [1] CRAN (R 4.2.2)
 catboost     * 1.2.1      2023-08-31 [1] url (https://github.com/catboost/catboost/releases/download/v1.2.1/catboost-R-Windows-1.2.1.tgz)
 class          7.3-22     2023-05-03 [2] CRAN (R 4.3.1)
 cli            3.6.1      2023-03-23 [1] CRAN (R 4.2.3)
 codetools      0.2-19     2023-02-01 [2] CRAN (R 4.3.1)
 colorspace     2.1-0      2023-01-23 [1] CRAN (R 4.2.2)
 crayon         1.5.2      2022-09-29 [1] CRAN (R 4.2.2)
 data.table     1.14.8     2023-02-17 [1] CRAN (R 4.2.3)
 devtools     * 2.4.5      2022-10-11 [1] CRAN (R 4.2.2)
 dials        * 1.2.0      2023-04-03 [1] CRAN (R 4.2.3)
 DiceDesign     1.9        2021-02-13 [1] CRAN (R 4.2.0)
 digest         0.6.33     2023-07-07 [1] CRAN (R 4.3.1)
 doParallel     1.0.17     2022-02-07 [1] CRAN (R 4.2.0)
 dplyr        * 1.1.2      2023-04-20 [1] CRAN (R 4.2.3)
 ellipsis       0.3.2      2021-04-29 [1] CRAN (R 4.2.0)
 fansi          1.0.4      2023-01-22 [1] CRAN (R 4.2.2)
 fastmap        1.1.1      2023-02-24 [1] CRAN (R 4.2.3)
 foreach        1.5.2      2022-02-02 [1] CRAN (R 4.2.0)
 fs             1.6.3      2023-07-20 [1] CRAN (R 4.3.1)
 furrr          0.3.1      2022-08-15 [1] CRAN (R 4.2.2)
 future         1.33.0     2023-07-01 [1] CRAN (R 4.3.1)
 future.apply   1.11.0     2023-05-21 [1] CRAN (R 4.3.0)
 generics       0.1.3      2022-07-05 [1] CRAN (R 4.2.2)
 ggplot2      * 3.4.3      2023-08-14 [1] CRAN (R 4.3.1)
 globals        0.16.2     2022-11-21 [1] CRAN (R 4.2.2)
 glue           1.6.2      2022-02-24 [1] CRAN (R 4.2.0)
 gower          1.0.1      2022-12-22 [1] CRAN (R 4.2.2)
 GPfit          1.0-8      2019-02-08 [1] CRAN (R 4.2.0)
 gtable         0.3.4      2023-08-21 [1] CRAN (R 4.3.1)
 hardhat        1.3.0      2023-03-30 [1] CRAN (R 4.2.3)
 htmltools      0.5.6      2023-08-10 [1] CRAN (R 4.3.1)
 htmlwidgets    1.6.2      2023-03-17 [1] CRAN (R 4.2.3)
 httpuv         1.6.11     2023-05-11 [1] CRAN (R 4.3.0)
 infer        * 1.0.4      2022-12-02 [1] CRAN (R 4.2.2)
 ipred          0.9-14     2023-03-09 [1] CRAN (R 4.2.3)
 iterators      1.0.14     2022-02-05 [1] CRAN (R 4.2.0)
 jsonlite       1.8.7      2023-06-29 [1] CRAN (R 4.3.1)
 later          1.3.1      2023-05-02 [1] CRAN (R 4.3.0)
 lattice        0.21-8     2023-04-05 [2] CRAN (R 4.3.1)
 lava           1.7.2.1    2023-02-27 [1] CRAN (R 4.2.3)
 lhs            1.1.6      2022-12-17 [1] CRAN (R 4.2.2)
 lifecycle      1.0.3      2022-10-07 [1] CRAN (R 4.2.2)
 listenv        0.9.0      2022-12-16 [1] CRAN (R 4.2.2)
 lubridate      1.9.2      2023-02-10 [1] CRAN (R 4.2.2)
 magrittr       2.0.3      2022-03-30 [1] CRAN (R 4.2.0)
 MASS           7.3-60     2023-05-04 [2] CRAN (R 4.3.1)
 Matrix         1.6-1      2023-08-14 [1] CRAN (R 4.3.1)
 memoise        2.0.1      2021-11-26 [1] CRAN (R 4.2.0)
 mime           0.12       2021-09-28 [1] CRAN (R 4.2.0)
 miniUI         0.1.1.1    2018-05-18 [1] CRAN (R 4.2.0)
 modeldata    * 1.2.0      2023-08-09 [1] CRAN (R 4.3.1)
 munsell        0.5.0      2018-06-12 [1] CRAN (R 4.2.0)
 nnet           7.3-19     2023-05-03 [2] CRAN (R 4.3.1)
 parallelly     1.36.0     2023-05-26 [1] CRAN (R 4.3.0)
 parsnip      * 1.1.1      2023-08-17 [1] CRAN (R 4.3.1)
 pillar         1.9.0      2023-03-22 [1] CRAN (R 4.2.3)
 pkgbuild       1.4.2      2023-06-26 [1] CRAN (R 4.3.1)
 pkgconfig      2.0.3      2019-09-22 [1] CRAN (R 4.2.0)
 pkgload        1.3.2.1    2023-07-08 [1] CRAN (R 4.3.1)
 prettyunits    1.1.1      2020-01-24 [1] CRAN (R 4.2.0)
 processx       3.8.2      2023-06-30 [1] CRAN (R 4.3.1)
 prodlim        2023.08.28 2023-08-28 [1] CRAN (R 4.3.1)
 profvis        0.3.8      2023-05-02 [1] CRAN (R 4.3.0)
 promises       1.2.1      2023-08-10 [1] CRAN (R 4.3.1)
 ps             1.7.5      2023-04-18 [1] CRAN (R 4.2.3)
 purrr        * 1.0.2      2023-08-10 [1] CRAN (R 4.3.1)
 R6             2.5.1      2021-08-19 [1] CRAN (R 4.2.0)
 Rcpp           1.0.11     2023-07-06 [1] CRAN (R 4.3.1)
 recipes      * 1.0.8      2023-08-25 [1] CRAN (R 4.3.1)
 remotes        2.4.2.1    2023-07-18 [1] CRAN (R 4.3.0)
 rlang          1.1.1      2023-04-28 [1] CRAN (R 4.3.0)
 rpart          4.1.19     2022-10-21 [2] CRAN (R 4.3.1)
 rsample      * 1.2.0      2023-08-23 [1] CRAN (R 4.3.1)
 rstudioapi     0.15.0     2023-07-07 [1] CRAN (R 4.3.1)
 scales       * 1.2.1      2022-08-20 [1] CRAN (R 4.2.2)
 sessioninfo    1.2.2      2021-12-06 [1] CRAN (R 4.2.0)
 shiny          1.7.5      2023-08-12 [1] CRAN (R 4.3.1)
 stringi        1.7.12     2023-01-11 [1] CRAN (R 4.2.2)
 stringr        1.5.0      2022-12-02 [1] CRAN (R 4.2.2)
 survival       3.5-5      2023-03-12 [2] CRAN (R 4.3.1)
 tibble       * 3.2.1      2023-03-20 [1] CRAN (R 4.2.3)
 tidymodels   * 1.1.1      2023-08-24 [1] CRAN (R 4.3.1)
 tidyr        * 1.3.0      2023-01-24 [1] CRAN (R 4.2.2)
 tidyselect     1.2.0      2022-10-10 [1] CRAN (R 4.2.2)
 timechange     0.2.0      2023-01-11 [1] CRAN (R 4.2.2)
 timeDate       4022.108   2023-01-07 [1] CRAN (R 4.2.2)
 treesnip     * 0.1.0.9000 2022-05-04 [1] Github (curso-r/treesnip@58d4d47)
 tune         * 1.1.2      2023-08-23 [1] CRAN (R 4.3.1)
 urlchecker     1.0.1      2021-11-30 [1] CRAN (R 4.2.0)
 usethis      * 2.2.2      2023-07-06 [1] CRAN (R 4.3.1)
 utf8           1.2.3      2023-01-31 [1] CRAN (R 4.2.2)
 vctrs          0.6.3      2023-06-14 [1] CRAN (R 4.3.0)
 withr          2.5.0      2022-03-03 [1] CRAN (R 4.2.0)
 workflows    * 1.1.3      2023-02-22 [1] CRAN (R 4.2.3)
 workflowsets * 1.0.1      2023-04-06 [1] CRAN (R 4.2.3)
 xtable         1.8-4      2019-04-21 [1] CRAN (R 4.2.0)
 yardstick    * 1.2.0      2023-04-21 [1] CRAN (R 4.2.3)

 [1] C:/Users/vidar/AppData/Local/R/win-library/4.3
 [2] C:/Program Files/R/R-4.3.1/library

───────────────────────────────────────────────────────────────────────────────────────────────────────────────────

[simonpcouch]

Thanks for the issue!

This issue seems better fit for the treesnip package, where there are a number of similar issues: curso-r/treesnip#69, curso-r/treesnip#68. We've created a follow-up package to treesnip, bonsai, and we absolutely plan on introducing support for catboost if/when the package makes it to CRAN!

You may have better luck building your own custom model specification for this use case.

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