Update

Author: sebffischer

paper/benchmark/benchmark.R

@@ -4,6 +4,20 @@ library(mlr3misc)
 setup = function(reg_path, python_path, work_dir) {
 
   print_setup_info(reg_path, python_path, work_dir)
+  
+  
+  if (file.exists(reg_path)) {
+    msg <- sprintf("Registry already exists at path %s. Delete the folder it to run the benchmark again.", reg_path)
+    if (!interactive()) {
+      stop(msg)
+    }
+    answer <- readline(sprintf("Registry already exists at path %s. Delete it to run the benchmark again? (y/n)", reg_path))
+     if (answer == "y") {
+       unlink(reg_path, recursive = TRUE)
+     } else {
+       stop(msg)
+     }
+  }
 
   reg = makeExperimentRegistry(
     file.dir = reg_path,

paper/benchmark/linux-cpu.R

@@ -1,17 +1,12 @@
 library(here)
 
-source(here("benchmark", "benchmark.R"))
-
 set.seed(42)
+source(here("benchmark", "benchmark.R"))
 
 # Change this when not running this in the docker image
 # Below is the correct python path for the CPU docker image.
 PYTHON_PATH = "/opt/venv/bin/python"
 
-if (dir.exists(here("benchmark", "registry-linux-gpu"))) {
-  stop("Registry benchmark/registry-linux-cpu already exists. Delete the folder to run the benchmark again.")
-}
-
 setup(
   here("benchmark", "registry-linux-cpu"),
   PYTHON_PATH,

paper/benchmark/linux-gpu-optimizer.R

@@ -26,9 +26,6 @@ problem_design = expand.grid(
   stringsAsFactors = FALSE
 )
 
-if (dir.exists(here("benchmark", "registry-linux-gpu-optimizer"))) {
-  stop("Registry benchmark/registry-linux-gpu-optimizer already exists. Delete the folder to run the benchmark again.")
-}
 
 setup(
   here("benchmark", "registry-linux-gpu-optimizer"),

paper/benchmark/linux-gpu.R

@@ -26,10 +26,6 @@ problem_design = expand.grid(
   stringsAsFactors = FALSE
 )
 
-if (dir.exists(here("benchmark", "registry-linux-gpu"))) {
-  stop("Registry benchmark/registry-linux-gpu already exists. Delete the folder to run the benchmark again.")
-}
-
 setup(
   here("benchmark", "registry-linux-gpu"),
   PYTHON_PATH,

paper/benchmark/result-linux-cpu.rds

@@ -7,7 +7,7 @@ Sys.time()
 ```
 
 ```
-## [1] "2026-01-29 17:27:24 CET"
+## [1] "2026-01-30 10:49:44 UTC"
 ```
 
 ``` r
@@ -71,7 +71,7 @@ mnist
 
 ```
 ## 
-## ── <TaskClassif> (70000x2): MNIST Digit Classification ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+## ── <TaskClassif> (70000x2): MNIST Digit Classification ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 ## • Target: label
 ## • Target classes: 1 (11%), 7 (10%), 3 (10%), 2 (10%), 9 (10%), 0 (10%), 6 (10%), 8 (10%), 4 (10%), 5 (9%)
 ## • Properties: multiclass
@@ -137,7 +137,7 @@ mlp$model$network
 ```
 ## An `nn_module` containing 100,710 parameters.
 ## 
-## ── Modules ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+## ── Modules ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 ## • 0: <nn_linear> #78,500 parameters
 ## • 1: <nn_relu> #0 parameters
 ## • 2: <nn_dropout> #0 parameters
@@ -154,7 +154,7 @@ head(mlp$model$callbacks$history, n = 2)
 ```
 ##    epoch train.classif.logloss
 ##    <num>                 <num>
-## 1:     1              4.266896
+## 1:     1              4.266895
 ## 2:     2              1.296983
 ```
 
@@ -165,7 +165,7 @@ pred$score(msr("classif.ce"))
 
 ```
 ## classif.ce 
-##       0.19
+##       0.21
 ```
 
 ``` r
@@ -354,7 +354,7 @@ task
 
 ```
 ## 
-## ── <TaskRegr> (32x11): Motor Trends ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+## ── <TaskRegr> (32x11): Motor Trends ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 ## • Target: mpg
 ## • Properties: -
 ## • Features (10):
@@ -484,7 +484,7 @@ task
 
 ```
 ## 
-## ── <TaskClassif> (25000x2) ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+## ── <TaskClassif> (25000x2) ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 ## • Target: class
 ## • Target classes: cat (positive class, 50%), dog (50%)
 ## • Properties: twoclass
@@ -525,7 +525,7 @@ learner$model$classif.resnet18$model$callbacks$history
 ##    epoch valid.classif.acc
 ##    <num>             <num>
 ## 1:     1         0.4179104
-## 2:     2         0.4626866
+## 2:     2         0.4477612
 ## 3:     3         0.8955224
 ## 4:     4         0.8955224
 ## 5:     5         0.9253731
@@ -540,7 +540,7 @@ task
 
 ```
 ## 
-## ── <TaskClassif> (32701x5): Melanoma Classification ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
+## ── <TaskClassif> (32701x5): Melanoma Classification ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 ## • Target: outcome
 ## • Target classes: malignant (positive class, 2%), benign (98%)
 ## • Properties: twoclass, groups
@@ -642,7 +642,7 @@ Sys.time()
 ```
 
 ```
-## [1] "2026-01-29 17:36:21 CET"
+## [1] "2026-01-30 11:04:48 UTC"
 ```
 
 ``` r
@@ -651,27 +651,32 @@ sessionInfo()
 
 ```
 ## R version 4.5.1 (2025-06-13)
-## Platform: aarch64-apple-darwin20
-## Running under: macOS Sequoia 15.2
+## Platform: x86_64-pc-linux-gnu
+## Running under: Ubuntu 24.04.3 LTS
 ## 
 ## Matrix products: default
-## BLAS:   /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRblas.0.dylib 
-## LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1
+## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
+## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
 ## 
 ## locale:
-## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
+##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
+##  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
+##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
+##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
+## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
 ## 
-## time zone: Europe/Berlin
-## tzcode source: internal
+## time zone: Etc/UTC
+## tzcode source: system (glibc)
 ## 
 ## attached base packages:
-## [1] stats     graphics  grDevices datasets  utils     methods   base     
+## [1] stats     graphics  grDevices utils     datasets  methods   base     
 ## 
 ## other attached packages:
-##  [1] ggplot2_4.0.0       mlr3viz_0.10.1.9000 torchdatasets_0.3.1
-##  [4] mlr3tuning_1.4.0    paradox_1.0.1       mlr3torch_0.3.2    
-##  [7] torch_0.16.3        future_1.67.0       mlr3pipelines_0.9.0
-## [10] mlr3_1.2.0         
+##  [1] ggplot2_4.0.0        mlr3viz_0.10.1.9000  torchdatasets_0.3.1 
+##  [4] mlr3tuning_1.4.0     paradox_1.0.1        mlr3torch_0.3.2-9000
+##  [7] torch_0.16.3         future_1.67.0        mlr3pipelines_0.9.0 
+## [10] mlr3_1.2.0          
 ## 
 ## loaded via a namespace (and not attached):
 ##  [1] gtable_0.3.6         xfun_0.54            processx_3.8.6      
@@ -692,8 +697,8 @@ sessionInfo()
 ## [46] jpeg_0.1-11          bit_4.6.0            evaluate_1.0.5      
 ## [49] knitr_1.50           torchvision_0.8.0    viridisLite_0.4.2   
 ## [52] mlr3misc_0.19.0      rlang_1.1.6          Rcpp_1.1.0          
-## [55] zeallot_0.2.0        glue_1.8.0           renv_1.1.5          
-## [58] palmerpenguins_0.1.1 coro_1.1.0           jsonlite_2.0.0      
-## [61] lgr_0.5.0            R6_2.6.1             fs_1.6.6
+## [55] zeallot_0.2.0        glue_1.8.0           palmerpenguins_0.1.1
+## [58] coro_1.1.0           jsonlite_2.0.0       lgr_0.5.0           
+## [61] R6_2.6.1             fs_1.6.6
 ```