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Added backward compatibility fix for XGBoost models #829

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Merged
merged 1 commit into from
Sep 22, 2022
Merged

Added backward compatibility fix for XGBoost models #829

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3 changes: 2 additions & 1 deletion .../src/main/scala/ml/combust/mleap/xgboost/runtime/bundle/ops/XGBoostClassificationOp.scala
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Expand Up @@ -37,7 +37,8 @@ class XGBoostClassificationOp extends MleapOp[XGBoostClassification, XGBoostClas

val numClasses = model.value("num_classes").getInt
val numFeatures = model.value("num_features").getInt
val treeLimit = model.value("tree_limit").getInt
val treeLimit = model.getValue("tree_limit")
.map(_.getInt).getOrElse(0)

val impl = if(numClasses == 2) {
XGBoostBinaryClassificationModel(booster, numFeatures, treeLimit)
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3 changes: 2 additions & 1 deletion .../scala/ml/combust/mleap/xgboost/runtime/bundle/ops/XGBoostPredictorClassificationOp.scala
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Expand Up @@ -33,7 +33,8 @@ class XGBoostPredictorClassificationOp extends MleapOp[XGBoostPredictorClassific

val numClasses = model.value("num_classes").getInt
val numFeatures = model.value("num_features").getInt
val treeLimit = model.value("tree_limit").getInt
val treeLimit = model.getValue("tree_limit")
.map(_.getInt).getOrElse(0)

val impl = if(numClasses == 2) {
XGBoostPredictorBinaryClassificationModel(predictor, numFeatures, treeLimit)
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3 changes: 2 additions & 1 deletion ...main/scala/ml/combust/mleap/xgboost/runtime/bundle/ops/XGBoostPredictorRegressionOp.scala
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Expand Up @@ -27,7 +27,8 @@ class XGBoostPredictorRegressionOp extends MleapOp[XGBoostPredictorRegression, X
val predictor = new Predictor(Files.newInputStream(context.file("xgboost.model")))

val numFeatures = model.value("num_features").getInt
val treeLimit = model.value("tree_limit").getInt
val treeLimit = model.getValue("tree_limit")
.map(_.getInt).getOrElse(0)

XGBoostPredictorRegressionModel(
predictor,
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3 changes: 2 additions & 1 deletion ...time/src/main/scala/ml/combust/mleap/xgboost/runtime/bundle/ops/XGBoostRegressionOp.scala
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Expand Up @@ -35,7 +35,8 @@ class XGBoostRegressionOp extends MleapOp[XGBoostRegression, XGBoostRegressionMo
(implicit context: BundleContext[MleapContext]): XGBoostRegressionModel = {
val bytes = Files.readAllBytes(context.file("xgboost.model"))
val booster = XGBoost.loadModel(new ByteArrayInputStream(bytes))
val treeLimit = model.value("tree_limit").getInt
val treeLimit = model.getValue("tree_limit")
.map(_.getInt).getOrElse(0)

XGBoostRegressionModel(booster,
numFeatures = model.value("num_features").getInt,
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4 changes: 2 additions & 2 deletions ...ark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/mleap/XGBoostClassificationModelOp.scala
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Expand Up @@ -49,9 +49,9 @@ class XGBoostClassificationModelOp extends SimpleSparkOp[XGBoostClassificationMo
SXGBoost.loadModel(in)
}).tried.get

val xgb = new XGBoostClassificationModel("", model.value("num_classes").getInt, booster).
setTreeLimit(model.value("tree_limit").getInt)
val xgb = new XGBoostClassificationModel("", model.value("num_classes").getInt, booster)

model.getValue("tree_limit").map(o => xgb.setTreeLimit(o.getInt))
model.getValue("thresholds").map(o => xgb.setThresholds(o.getDoubleList.toArray))
model.getValue("missing").map(o => xgb.setMissing(o.getFloat))
model.getValue("allow_non_zero_for_missing").map(o => xgb.setAllowNonZeroForMissing(o.getBoolean))
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4 changes: 2 additions & 2 deletions ...t-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/mleap/XGBoostRegressionModelOp.scala
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Expand Up @@ -43,9 +43,9 @@ class XGBoostRegressionModelOp extends SimpleSparkOp[XGBoostRegressionModel] {
SXGBoost.loadModel(in)
}).tried.get

val xgb = new XGBoostRegressionModel("", booster).
setTreeLimit(model.value("tree_limit").getInt)
val xgb = new XGBoostRegressionModel("", booster)

model.getValue("tree_limit").map(o => xgb.setTreeLimit(o.getInt))
model.getValue("missing").map(o => xgb.setMissing(o.getFloat))
model.getValue("allow_non_zero_for_missing").map(o => xgb.setAllowNonZeroForMissing(o.getBoolean))
model.getValue("infer_batch_size").map(o => xgb.setInferBatchSize(o.getInt))
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