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[jvm-packages] Add DeviceQuantileDMatrix to Scala binding (#7459)

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This commit is contained in:
Bobby Wang
2021-11-24 20:23:18 +08:00
committed by GitHub
parent 619c450a49
commit 24be04e848
4 changed files with 226 additions and 3 deletions
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2
jvm-packages/xgboost4j-gpu/src/main/java/ml/dmlc/xgboost4j/gpu/java/CudfColumn.java
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@@ -27,7 +27,7 @@ import ml.dmlc.xgboost4j.java.Column;
* This class is composing of base data with Apache Arrow format from Cudf ColumnVector.
* It will be used to generate the cuda array interface.
*/
class CudfColumn extends Column {
public class CudfColumn extends Column {
private final long dataPtr; // gpu data buffer address
private final long shape; // row count

79
jvm-packages/xgboost4j-gpu/src/test/scala/ml/dmlc/xgboost4j/scala/DeviceQuantileDMatrixSuite.scala Normal file
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@@ -0,0 +1,79 @@
/*
Copyright (c) 2021 by Contributors
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package ml.dmlc.xgboost4j.scala
import scala.collection.mutable.ArrayBuffer
import ai.rapids.cudf.Table
import org.scalatest.FunSuite
import ml.dmlc.xgboost4j.gpu.java.CudfColumnBatch
class DeviceQuantileDMatrixSuite extends FunSuite {
test("DeviceQuantileDMatrix test") {
val label1 = Array[java.lang.Float](25f, 21f, 22f, 20f, 24f)
val weight1 = Array[java.lang.Float](1.3f, 2.31f, 0.32f, 3.3f, 1.34f)
val baseMargin1 = Array[java.lang.Float](1.2f, 0.2f, 1.3f, 2.4f, 3.5f)
val label2 = Array[java.lang.Float](9f, 5f, 4f, 10f, 12f)
val weight2 = Array[java.lang.Float](3.0f, 1.3f, 3.2f, 0.3f, 1.34f)
val baseMargin2 = Array[java.lang.Float](0.2f, 2.5f, 3.1f, 4.4f, 2.2f)
withResource(new Table.TestBuilder()
.column(1.2f, null.asInstanceOf[java.lang.Float], 5.2f, 7.2f, 9.2f)
.column(0.2f, 0.4f, 0.6f, 2.6f, 0.10f.asInstanceOf[java.lang.Float])
.build) { X_0 =>
withResource(new Table.TestBuilder().column(label1: _*).build) { y_0 =>
withResource(new Table.TestBuilder().column(weight1: _*).build) { w_0 =>
withResource(new Table.TestBuilder().column(baseMargin1: _*).build) { m_0 =>
withResource(new Table.TestBuilder()
.column(11.2f, 11.2f, 15.2f, 17.2f, 19.2f.asInstanceOf[java.lang.Float])
.column(1.2f, 1.4f, null.asInstanceOf[java.lang.Float], 12.6f, 10.10f).build)
{ X_1 =>
withResource(new Table.TestBuilder().column(label2: _*).build) { y_1 =>
withResource(new Table.TestBuilder().column(weight2: _*).build) { w_1 =>
withResource(new Table.TestBuilder().column(baseMargin2: _*).build) { m_1 =>
val batches = new ArrayBuffer[CudfColumnBatch]()
batches += new CudfColumnBatch(X_0, y_0, w_0, m_0)
batches += new CudfColumnBatch(X_1, y_1, w_1, m_1)
val dmatrix = new DeviceQuantileDMatrix(batches.toIterator, 0.0f, 8, 1)
assert(dmatrix.getLabel.sameElements(label1 ++ label2))
assert(dmatrix.getWeight.sameElements(weight1 ++ weight2))
assert(dmatrix.getBaseMargin.sameElements(baseMargin1 ++ baseMargin2))
}
}
}
}
}
}
}
}
}
/** Executes the provided code block and then closes the resource */
private def withResource[T <: AutoCloseable, V](r: T)(block: T => V): V = {
try {
block(r)
} finally {
r.close()
}
}
}