Resampling with `store_models = TRUE` is slow

```r
library(mlr3learners)

task = tsk("pima")
learner = lrn("classif.ranger", num.trees = 5000)
resampling = rsmp("cv", folds = 10)

system.time(resample(task, learner, resampling))
 
#    user  system elapsed 
#  25.037   1.413  24.330 

system.time(resample(task, learner, resampling, store_models = TRUE))

#    user  system elapsed 
#  27.560   1.701  27.138 
```

Saving the models take 3 seconds longer. While tuning with `store_models` it took almost 8 seconds longer. The ranger models get quite large ~60MB.  The 3 seconds get lost when creating this `data.table`: 

https://github.com/mlr-org/mlr3/blob/2c8734a853c01b9fe9002e3b81c947419ea8b0f0/R/resample.R#L121-L131

Profiling of this part

![image](https://github.com/user-attachments/assets/624efb8e-a1e0-4d35-ba6b-c5d8ddd6edc4)



	data = data.table(
	task = list(task),
	learner = grid$learner,
	learner_state = map(res, "learner_state"),
	resampling = list(resampling),
	iteration = seq_len(n),
	prediction = map(res, "prediction"),
	uhash = UUIDgenerate(),
	param_values = map(res, "param_values"),
	learner_hash = map_chr(res, "learner_hash")
	)

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Resampling with `store_models = TRUE` is slow #1222

Metadata

Assignees

Labels

Type

Projects

Milestone

Relationships

Development

Resampling with store_models = TRUE is slow #1222

Description