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Preserve order of saved updaters config. (#9355)

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- Save the updater sequence as an array instead of object.
- Warn only once.

The compatibility is kept, but we should be able to break it as the config is not loaded
in pickle model and it's declared to be not stable.
This commit is contained in:
Jiaming Yuan
2023-07-05 20:20:07 +08:00
committed by GitHub
parent b572a39919
commit 41c6813496
6 changed files with 112 additions and 71 deletions
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34
R-package/tests/testthat/test_model_compatibility.R
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@@ -76,32 +76,20 @@ test_that("Models from previous versions of XGBoost can be loaded", {
name <- m[3]
is_rds <- endsWith(model_file, '.rds')
is_json <- endsWith(model_file, '.json')
cpp_warning <- capture.output({
# Expect an R warning when a model is loaded from RDS and it was generated by version < 1.1.x
if (is_rds && compareVersion(model_xgb_ver, '1.1.1.1') < 0) {
# Expect an R warning when a model is loaded from RDS and it was generated by version < 1.1.x
if (is_rds && compareVersion(model_xgb_ver, '1.1.1.1') < 0) {
booster <- readRDS(model_file)
expect_warning(predict(booster, newdata = pred_data))
booster <- readRDS(model_file)
expect_warning(run_booster_check(booster, name))
} else {
if (is_rds) {
booster <- readRDS(model_file)
expect_warning(predict(booster, newdata = pred_data))
booster <- readRDS(model_file)
expect_warning(run_booster_check(booster, name))
} else {
if (is_rds) {
booster <- readRDS(model_file)
} else {
booster <- xgb.load(model_file)
}
predict(booster, newdata = pred_data)
run_booster_check(booster, name)
booster <- xgb.load(model_file)
}
})
cpp_warning <- paste0(cpp_warning, collapse = ' ')
if (is_rds && compareVersion(model_xgb_ver, '1.1.1.1') >= 0) {
# Expect a C++ warning when a model is loaded from RDS and it was generated by old XGBoost`
m <- grepl(paste0('.*If you are loading a serialized model ',
'\\(like pickle in Python, RDS in R\\).*',
'for more details about differences between ',
'saving model and serializing.*'), cpp_warning, perl = TRUE)
expect_true(length(m) > 0 && all(m))
predict(booster, newdata = pred_data)
run_booster_check(booster, name)
}
})
})