Nothing
test_that("bundling + unbundling tidymodels stacks", {
skip_if_not_installed("stacks")
skip_if_not_installed("parsnip")
skip_if_not_installed("workflows")
skip_if_not_installed("kernlab")
library(stacks)
test_data <- stacks::tree_frogs_reg_test
# define a function to fit a model -------------------------------------------
fit_model <- function() {
set.seed(1)
mod <-
stacks() %>%
add_candidates(reg_res_lr) %>%
add_candidates(reg_res_svm) %>%
blend_predictions(times = 10) %>%
fit_members()
}
# pass fit fn to a new session, fit, bundle, return bundle -------------------
mod_bundle <-
callr::r(
function(fit_model) {
library(stacks)
mod <- fit_model()
bundle::bundle(mod)
},
args = list(fit_model = fit_model)
)
# pass the bundle to a new session, unbundle it, return predictions ----------
mod_unbundled_preds <-
callr::r(
function(mod_bundle, test_data) {
library(stacks)
mod_unbundled <- bundle::unbundle(mod_bundle)
predict(mod_unbundled, test_data)
},
args = list(
mod_bundle = mod_bundle,
test_data = test_data
)
)
# pass fit fn to a new session, fit, butcher, bundle, return bundle ----------
mod_butchered_bundle <-
callr::r(
function(fit_model) {
library(stacks)
mod <- fit_model()
bundle::bundle(butcher::butcher(mod))
},
args = list(fit_model = fit_model)
)
# pass the bundle to a new session, unbundle it, return predictions ----------
mod_butchered_unbundled_preds <-
callr::r(
function(mod_butchered_bundle, test_data) {
library(stacks)
mod_butchered_unbundled <- bundle::unbundle(mod_butchered_bundle)
predict(mod_butchered_unbundled, test_data)
},
args = list(
mod_butchered_bundle = mod_butchered_bundle,
test_data = test_data
)
)
# run expectations -----------------------------------------------------------
mod_fit <- fit_model()
mod_preds <- predict(mod_fit, test_data)
# check classes
expect_s3_class(mod_bundle, "bundled_model_stack")
expect_s3_class(unbundle(mod_bundle), "model_stack")
# ensure that the situater function didn't bring along the whole model
expect_false("x" %in% names(environment(mod_bundle$situate)))
# pass silly dots
expect_error(bundle(mod_fit, boop = "bop"), class = "rlib_error_dots")
# compare predictions
expect_equal(mod_preds, mod_unbundled_preds)
expect_equal(mod_preds, mod_butchered_unbundled_preds)
})
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