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Commita659f16

Browse files
authored
Fix lightgbm regression (#339)
1 parent0df498e commita659f16

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4 files changed

+26
-14
lines changed

4 files changed

+26
-14
lines changed

‎pgml-extension/pgml_rust/Cargo.toml‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -18,7 +18,7 @@ pg_test = []
1818
[dependencies]
1919
pgx = {git="https://github.com/postgresml/pgx.git",branch="master" }
2020
xgboost = {git="https://github.com/postgresml/rust-xgboost.git" }
21-
smartcore = {git="https://github.com/smartcorelib/smartcore.git",branch="main",features = ["serde","ndarray-bindings"] }
21+
smartcore = {git="https://github.com/smartcorelib/smartcore.git",branch="development",features = ["serde","ndarray-bindings"] }
2222
once_cell ="1"
2323
rand ="0.8"
2424
ndarray = {version ="0.15.6",features = ["serde","blas"] }

‎pgml-extension/pgml_rust/src/engines/lightgbm.rs‎

Lines changed: 22 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -9,29 +9,36 @@ use serde_json::json;
99
pubfnlightgbm_train(task:Task,dataset:&Dataset,hyperparams:&Hyperparams) ->LightgbmBox{
1010
let x_train = dataset.x_train();
1111
let y_train = dataset.y_train();
12-
let objective =match task{
13-
Task::regression =>"regression",
12+
letmut hyperparams = hyperparams.clone();
13+
match task{
14+
Task::regression =>{
15+
hyperparams.insert(
16+
"objective".to_string(),
17+
serde_json::Value::from("regression"),
18+
);
19+
}
1420
Task::classification =>{
1521
let distinct_labels = dataset.distinct_labels();
1622

1723
if distinct_labels >2{
18-
"multiclass"
24+
hyperparams.insert(
25+
"objective".to_string(),
26+
serde_json::Value::from("multiclass"),
27+
);
28+
hyperparams.insert(
29+
"num_class".to_string(),
30+
serde_json::Value::from(dataset.distinct_labels()),
31+
);// [0, num_class)
1932
}else{
20-
"binary"
33+
hyperparams.insert("objective".to_string(), serde_json::Value::from("binary"));
2134
}
2235
}
2336
};
2437

2538
let dataset =
2639
lightgbm::Dataset::from_vec(x_train, y_train, dataset.num_featuresasi32).unwrap();
2740

28-
let bst = lightgbm::Booster::train(
29-
dataset,
30-
&json!{{
31-
"objective": objective,
32-
}},
33-
)
34-
.unwrap();
41+
let bst = lightgbm::Booster::train(dataset,&json!{hyperparams}).unwrap();
3542

3643
LightgbmBox::new(bst)
3744
}
@@ -67,10 +74,12 @@ pub fn lightgbm_test(estimator: &LightgbmBox, dataset: &Dataset) -> Vec<f32> {
6774
let x_test = dataset.x_test();
6875
let num_features = dataset.num_features;
6976

70-
estimator.predict(&x_test, num_featuresasi32).unwrap()
77+
let y_hat = estimator.predict(&x_test, num_featuresasi32).unwrap();
78+
let y_hat:Vec<f32> = y_hat.into_iter().map(|y| yasf32).collect();
79+
y_hat
7180
}
7281

7382
/// Predict a novel datapoint using the LightGBM estimator.
7483
pubfnlightgbm_predict(estimator:&LightgbmBox,x:&[f32]) ->f32{
75-
estimator.predict(&x, x.len()asi32).unwrap()[0]
84+
estimator.predict(&x, x.len()asi32).unwrap()[0]asf32
7685
}

‎pgml-extension/pgml_rust/src/engines/xgboost.rs‎

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -38,6 +38,7 @@ pub fn xgboost_train(
3838
Task::regression => xgboost::parameters::learning::Objective::RegLinear,
3939
Task::classification =>{
4040
xgboost::parameters::learning::Objective::MultiSoftmax(dataset.distinct_labels())
41+
// [0, num_class)
4142
}
4243
})
4344
.build()

‎pgml-extension/pgml_rust/src/orm/snapshot.rs‎

Lines changed: 2 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -396,11 +396,13 @@ impl Snapshot {
396396
}
397397
}
398398
});
399+
399400
let num_test_rows =ifself.test_size >1.0{
400401
self.test_sizeasusize
401402
}else{
402403
(num_rowsasf32*self.test_size).round()asusize
403404
};
405+
404406
let num_train_rows = num_rows - num_test_rows;
405407
if num_train_rows ==0{
406408
error!(

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