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rstudio / bundle

Prepare objects for serialization with a consistent interface
https://rstudio.github.io/bundle/
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support mlr3 #13

Open simonpcouch opened 2 years ago

simonpcouch commented 2 years ago

Some work on the mlr3 branch already.

simonpcouch commented 2 years ago

After spending more time with this, I think our best approach here will to wait for more machinery from mlr3 folks before implementing anything more principled. Prediction in a new session works fine, so this shouldn't be a pain point!

library(mlr3)

task <- tsk("mtcars")
fit <- lrn("regr.rpart")

# train a model of this learner for a subset of the task
fit$train(task, row_ids = 1:26)

callr::r(
  function(fit) {
    library(mlr3)

    predict(fit, mtcars[27:32,])
  },
  args = list(fit = fit)
)
#> [1] 27.71429 16.87368 16.87368 16.87368 16.87368 16.87368

Created on 2022-07-18 by the reprex package (v2.0.1)

simonpcouch commented 2 years ago

Look for the fitted model object slot, these should wrap like caret or parsnip.

sebffischer commented 1 year ago

I have started a discussion in mlr3 about serialization here: https://github.com/mlr-org/mlr3/issues/891 If we implement something like this, adding a bundle method for mlr3 Learners should be straightforward! :)