[breakinig] [jvm-packages] change DeviceQuantileDmatrix into QuantileDMatrix (#8461)
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@@ -20,7 +20,7 @@ import scala.collection.JavaConverters._
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import ml.dmlc.xgboost4j.gpu.java.CudfColumnBatch
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import ml.dmlc.xgboost4j.java.nvidia.spark.GpuColumnBatch
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import ml.dmlc.xgboost4j.scala.{Booster, DMatrix, DeviceQuantileDMatrix}
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import ml.dmlc.xgboost4j.scala.{Booster, DMatrix, QuantileDMatrix}
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import ml.dmlc.xgboost4j.scala.spark.params.XGBoostEstimatorCommon
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import ml.dmlc.xgboost4j.scala.spark.{PreXGBoost, PreXGBoostProvider, Watches, XGBoost, XGBoostClassificationModel, XGBoostClassifier, XGBoostExecutionParams, XGBoostRegressionModel, XGBoostRegressor}
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import org.apache.commons.logging.LogFactory
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@@ -532,7 +532,7 @@ object GpuPreXGBoost extends PreXGBoostProvider {
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}
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/**
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* Build DeviceQuantileDMatrix based on GpuColumnBatches
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* Build QuantileDMatrix based on GpuColumnBatches
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*
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* @param iter a sequence of GpuColumnBatch
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* @param indices indicate the feature, label, weight, base margin column ids.
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@@ -546,7 +546,7 @@ object GpuPreXGBoost extends PreXGBoostProvider {
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missing: Float,
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maxBin: Int): DMatrix = {
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val rapidsIterator = new RapidsIterator(iter, indices)
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new DeviceQuantileDMatrix(rapidsIterator, missing, maxBin, 1)
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new QuantileDMatrix(rapidsIterator, missing, maxBin, 1)
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}
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// zip all the Columnar RDDs into one RDD containing named column data batch.
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