Attempts to unload LightGBM packages so you can remove objects cleanly without having to restart R. This is useful for instance if an object becomes stuck for no apparent reason and you do not want to restart R to fix the lost object.
lgb.unloader(restore = TRUE, wipe = FALSE, envir = .GlobalEnv)
restore | Whether to reload |
---|---|
wipe | Whether to wipe all |
envir | The environment to perform wiping on if |
NULL invisibly.
# \donttest{ data(agaricus.train, package = "lightgbm") train <- agaricus.train dtrain <- lgb.Dataset(train$data, label = train$label) data(agaricus.test, package = "lightgbm") test <- agaricus.test dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label) params <- list(objective = "regression", metric = "l2") valids <- list(test = dtest) model <- lgb.train( params = params , data = dtrain , nrounds = 5L , valids = valids , min_data = 1L , learning_rate = 1.0 )#> [LightGBM] [Warning] Auto-choosing row-wise multi-threading, the overhead of testing was 0.000952 seconds. #> You can set `force_row_wise=true` to remove the overhead. #> And if memory is not enough, you can set `force_col_wise=true`. #> [LightGBM] [Info] Total Bins 232 #> [LightGBM] [Info] Number of data points in the train set: 6513, number of used features: 116 #> [LightGBM] [Info] Start training from score 0.482113 #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [1] "[1]: test's l2:6.44165e-17" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [1] "[2]: test's l2:1.97215e-31" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [1] "[3]: test's l2:0" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [LightGBM] [Warning] Stopped training because there are no more leaves that meet the split requirements #> [1] "[4]: test's l2:0" #> [LightGBM] [Warning] No further splits with positive gain, best gain: -inf #> [LightGBM] [Warning] Stopped training because there are no more leaves that meet the split requirements #> [1] "[5]: test's l2:0"lgb.unloader(restore = FALSE, wipe = FALSE, envir = .GlobalEnv) rm(model, dtrain, dtest) # Not needed if wipe = TRUE gc() # Not needed if wipe = TRUE#> used (Mb) gc trigger (Mb) max used (Mb) #> Ncells 1909104 102 3792771 202.6 2509982 134.1 #> Vcells 3789250 29 8388608 64.0 7858591 60.0