Add more internal measure unit tests

[be-marc]

Write more unit tests that check the *_internal_measure() functions for catboost, lightgbm and xgboost. See

mlr3automl/tests/testthat/test_LearnerClassifAutoCatboost.R

Lines 32 to 63 in 6afb23d

	test_that("internal eval metric is found", {
	skip_on_cran()
	skip_if_not_installed("rush")
	flush_redis()
	rush_plan(n_workers = 2)
	task = tsk("penguins")
	learner = lrn("classif.auto_catboost",
	small_data_size = 1,
	resampling = rsmp("holdout"),
	measure = msr("classif.ce"),
	terminator = trm("evals", n_evals = 6),
	store_benchmark_result = TRUE,
	store_models = TRUE
	)
	learner$train(task)
	expect_equal(learner$instance$archive$benchmark_result$resample_result(1)$learners[[1]]$model$catboost$param_vals$eval_metric, "Accuracy")
	learner = lrn("classif.auto_catboost",
	small_data_size = 1,
	resampling = rsmp("holdout"),
	measure = msr("classif.mbrier"),
	terminator = trm("evals", n_evals = 6),
	store_benchmark_result = TRUE,
	store_models = TRUE
	)
	expect_error(learner$train(task), "No suitable catboost eval metric found")
	})

and https://github.com/mlr-org/mlr3automl/blob/main/R/internal_measure.R