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make lightgbm raw classification predictions backward and forward compatible #42

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Jul 19, 2022
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make lightgbm raw classification predictions backward and forward compatible #42

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1 change: 1 addition & 0 deletions NAMESPACE
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Original file line number Diff line number Diff line change
Expand Up @@ -28,3 +28,4 @@ importFrom(rlang,new_quosure)
importFrom(stats,predict)
importFrom(tibble,as_tibble)
importFrom(tibble,tibble)
importFrom(utils,packageVersion)
8 changes: 8 additions & 0 deletions R/0_imports.R
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Expand Up @@ -4,6 +4,7 @@
#' @importFrom parsnip multi_predict set_mode set_engine fit
#' @importFrom parsnip decision_tree boost_tree rand_forest
#' @importFrom stats predict
#' @importFrom utils packageVersion

# ------------------------------------------------------------------------------

Expand All @@ -24,4 +25,11 @@ utils::globalVariables(
)
)

# ------------------------------------------------------------------------------

# lightgbm had significant breaking changes following release v3.3.2.
# this function is used by patches that make bonsai backward-compatible with
# older lightgbm versions
using_newer_lightgbm_version <- function(){
utils::packageVersion("lightgbm") > package_version("3.3.2")
}
6 changes: 5 additions & 1 deletion R/lightgbm.R
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Expand Up @@ -311,7 +311,11 @@ predict_lightgbm_classification_class <- function(object, new_data, ...) {
#' @export
#' @rdname lightgbm_helpers
predict_lightgbm_classification_raw <- function(object, new_data, ...) {
p <- stats::predict(object$fit, prepare_df_lgbm(new_data), rawscore = TRUE, ...)
if (using_newer_lightgbm_version()) {
p <- stats::predict(object$fit, prepare_df_lgbm(new_data), type = "raw", ...)
} else {
p <- stats::predict(object$fit, prepare_df_lgbm(new_data), rawscore = TRUE, ...)
}
reshape_lightgbm_multiclass_preds(preds = p, num_rows = nrow(new_data))
}

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10 changes: 10 additions & 0 deletions tests/testthat/test-lightgbm.R
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Expand Up @@ -141,8 +141,13 @@ test_that("boost_tree with lightgbm",{
expect_error_free({
pars_preds_4 <-
predict(pars_fit_4, penguins, type = "prob")
pars_preds_raw_4 <-
predict(pars_fit_4, penguins, type = "raw")
})

expect_equal(nrow(pars_preds_raw_4), nrow(penguins))
expect_equal(ncol(pars_preds_raw_4), 3)

pars_preds_4_mtx <- as.matrix(pars_preds_4)
dimnames(pars_preds_4_mtx) <- NULL

Expand Down Expand Up @@ -202,8 +207,13 @@ test_that("boost_tree with lightgbm",{
expect_error_free({
pars_preds_6 <-
predict(pars_fit_6, penguins, type = "prob")
pars_preds_raw_6 <-
predict(pars_fit_6, penguins, type = "raw")
})

expect_equal(length(pars_preds_raw_6), nrow(penguins))
expect_false(identical(pars_preds_6, pars_preds_raw_6))

pars_preds_6_b <- pars_preds_6$.pred_male

peng_y_b <- peng$sex
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