"backup callback works with standalone tuner"
"default configuration callback works with logscale"
"default configuration callback errors with trafo"
"Cannot evaluate default hyperparameter values"
"default configuration callback works without transformation and with logscale"
"default configuration callback errors without transformation and with logscale and trafo"
"default configuration callback errors with extra trafo"
"default configuration callback errors with old parameter set api"
"batch default configuration callback  works"
"batch default configuration callback  works with logscale"
"batch default configuration callback  errors with trafo"
"batch default configuration callback  works without transformation and with logscale"
"batch default configuration callback  errors without transformation and with logscale and trafo"
"batch default configuration callback  errors with extra trafo"
"batch default configuration callback  errors with old parameter set api"

default configuration callback errors with old parameter set api

test_that("ti_async function creates a TuningInstanceAsyncSingleCrit", {
learner = lrn("classif.rpart", cp = to_tune()),
test_that("ti_async function creates a TuningInstanceAsyncMultiCrit", {
test_that("ti_async interface is equal to TuningInstanceAsyncSingleCrit", {
ti_args[ti_args == "measures"] = "measure"
test_that("ti_async interface is equal to TuningInstanceAsyncMultiCrit", {

"ti_async function creates a TuningInstanceAsyncSingleCrit"
"ti_async function creates a TuningInstanceAsyncMultiCrit"
"ti_async interface is equal to TuningInstanceAsyncSingleCrit"
"ti_async interface is equal to TuningInstanceAsyncMultiCrit"

ti_async function creates a TuningInstanceAsyncSingleCrit

ti_async function creates a TuningInstanceAsyncMultiCrit