[xgboost] Fix eval dataset issues

NVIDIA · Oct 21, 2024 · 84bc7b1 · 84bc7b1
1 parent 1c36fb9
commit 84bc7b1
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Showing 6 changed files with 24 additions and 55 deletions.
diff --git a/examples/XGBoost-Examples/agaricus/notebooks/scala/agaricus-gpu.ipynb b/examples/XGBoost-Examples/agaricus/notebooks/scala/agaricus-gpu.ipynb
@@ -316,23 +316,13 @@
     "## Benchmark and train\n",
     "The object `benchmark` is used to compute the elapsed time of some operations.\n",
     "\n",
-    "Training with evaluation sets is also supported in 2 ways, the same as CPU version's behavior:\n",
+    "Training with evaluation dataset is also supported, the same as CPU version's behavior:\n",
     "\n",
-    "* Call API `setEvalSets` after initializing an XGBoostClassifier\n",
+    "* Call API `setEvalDataset` after initializing an XGBoostClassifier\n",
     "\n",
     "```scala\n",
-    "xgbClassifier.setEvalSets(Map(\"eval\" -> evalSet))\n",
-    "\n",
-    "```\n",
-    "\n",
-    "* Use parameter `eval_sets` when initializing an XGBoostClassifier\n",
-    "\n",
-    "```scala\n",
-    "val paramMapWithEval = paramMap + (\"eval_sets\" -> Map(\"eval\" -> evalSet))\n",
-    "val xgbClassifierWithEval = new XGBoostClassifier(paramMapWithEval)\n",
-    "```\n",
-    "\n",
-    "Here chooses the API way to set evaluation sets."
+    "xgbClassifier.setEvalDataset(evalSet)\n",
+    "```"
    ]
   },
   {
@@ -352,7 +342,7 @@
     }
    ],
    "source": [
-    "xgbClassifier.setEvalSets(Map(\"eval\" -> evalSet))"
+    "xgbClassifier.setEvalDataset(evalSet)"
    ]
   },
   {

diff --git a/examples/XGBoost-Examples/agaricus/scala/src/com/nvidia/spark/examples/agaricus/Main.scala b/examples/XGBoost-Examples/agaricus/scala/src/com/nvidia/spark/examples/agaricus/Main.scala
@@ -64,13 +64,14 @@ object Main {
       // build XGBoost classifier
       val paramMap = xgboostArgs.xgboostParams(Map(
         "objective" -> "binary:logistic",
-        "eval_sets" -> datasets(1).map(ds => Map("eval" -> ds)).getOrElse(Map.empty)
       ))
       val xgbClassifier = new XGBoostClassifier(paramMap)
         .setLabelCol(labelName)
         // === diff ===
         .setFeaturesCol(featureCols)
 
+      datasets(1).foreach(_ => xgbClassifier.setEvalDataset(_))
+
       println("\n------ Training ------")
       val (model, _) = benchmark.time("train") {
         xgbClassifier.fit(datasets(0).get)

diff --git a/examples/XGBoost-Examples/mortgage/notebooks/scala/mortgage-gpu.ipynb b/examples/XGBoost-Examples/mortgage/notebooks/scala/mortgage-gpu.ipynb
@@ -304,23 +304,13 @@
     "## Benchmark and train\n",
     "The object `benchmark` is used to compute the elapsed time of some operations.\n",
     "\n",
-    "Training with evaluation sets is also supported in 2 ways, the same as CPU version's behavior:\n",
+    "Training with evaluation dataset is also supported, the same as CPU version's behavior:\n",
     "\n",
-    "* Call API `setEvalSets` after initializing an XGBoostClassifier\n",
+    "* Call API `setEvalDataset` after initializing an XGBoostClassifier\n",
     "\n",
     "```scala\n",
-    "xgbClassifier.setEvalSets(Map(\"eval\" -> evalSet))\n",
-    "\n",
-    "```\n",
-    "\n",
-    "* Use parameter `eval_sets` when initializing an XGBoostClassifier\n",
-    "\n",
-    "```scala\n",
-    "val paramMapWithEval = paramMap + (\"eval_sets\" -> Map(\"eval\" -> evalSet))\n",
-    "val xgbClassifierWithEval = new XGBoostClassifier(paramMapWithEval)\n",
-    "```\n",
-    "\n",
-    "Here chooses the API way to set evaluation sets."
+    "xgbClassifier.setEvalDataset(evalSet)\n",
+    "```"
    ]
   },
   {
@@ -340,7 +330,7 @@
     }
    ],
    "source": [
-    "xgbClassifier.setEvalSets(Map(\"eval\" -> evalSet))"
+    "xgbClassifier.setEvalDataset(evalSet)"
    ]
   },
   {

diff --git a/examples/XGBoost-Examples/mortgage/scala/src/com/nvidia/spark/examples/mortgage/Main.scala b/examples/XGBoost-Examples/mortgage/scala/src/com/nvidia/spark/examples/mortgage/Main.scala
@@ -52,14 +52,13 @@ object Main extends Mortgage {
 
       val xgbClassificationModel = if (appArgs.isToTrain) {
         // build XGBoost classifier
-        val xgbParamFinal = appArgs.xgboostParams(commParamMap +
-          // Add train-eval dataset if specified
-          ("eval_sets" -> datasets(1).map(ds => Map("eval" -> ds)).getOrElse(Map.empty))
-        )
+        val xgbParamFinal = appArgs.xgboostParams(commParamMap)
         val xgbClassifier = new XGBoostClassifier(xgbParamFinal)
           .setLabelCol(labelColName)
           .setFeaturesCol(featureNames)
 
+        datasets(1).foreach(_ => xgbClassifier.setEvalDataset(_))
+
         // Start training
         println("\n------ Training ------")
         // Shall we not log the time if it is abnormal, which is usually caused by training failure

diff --git a/examples/XGBoost-Examples/taxi/notebooks/scala/taxi-gpu.ipynb b/examples/XGBoost-Examples/taxi/notebooks/scala/taxi-gpu.ipynb
@@ -320,23 +320,13 @@
     "## Benchmark and train\n",
     "The object `benchmark` is used to compute the elapsed time of some operations.\n",
     "\n",
-    "Training with evaluation sets is also supported in 2 ways, the same as CPU version's behavior:\n",
+    "Training with evaluation dataset is also supported, the same as CPU version's behavior:\n",
     "\n",
-    "* Call API `setEvalSets` after initializing an XGBoostRegressor\n",
+    "* Call API `setEvalDataset` after initializing an XGBoostClassifier\n",
     "\n",
     "```scala\n",
-    "xgbRegressor.setEvalSets(Map(\"eval\" -> evalSet))\n",
-    "\n",
-    "```\n",
-    "\n",
-    "* Use parameter `eval_sets` when initializing an XGBoostRegressor\n",
-    "\n",
-    "```scala\n",
-    "val paramMapWithEval = paramMap + (\"eval_sets\" -> Map(\"eval\" -> evalSet))\n",
-    "val xgbRegressorWithEval = new XGBoostRegressor(paramMapWithEval)\n",
-    "```\n",
-    "\n",
-    "Here chooses the API way to set evaluation sets."
+    "xgbClassifier.setEvalDataset(evalSet)\n",
+    "```"
    ]
   },
   {
@@ -356,7 +346,7 @@
     }
    ],
    "source": [
-    "xgbRegressor.setEvalSets(Map(\"eval\" -> evalSet))"
+    "xgbRegressor.setEvalDataset(evalSet)"
    ]
   },
   {
@@ -609,4 +599,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}
diff --git a/examples/XGBoost-Examples/taxi/scala/src/com/nvidia/spark/examples/taxi/Main.scala b/examples/XGBoost-Examples/taxi/scala/src/com/nvidia/spark/examples/taxi/Main.scala
@@ -58,14 +58,13 @@ object Main extends Taxi {
 
     val xgbRegressionModel = if (xgboostArgs.isToTrain) {
       // build XGBoost XGBoostRegressor
-      val xgbParamFinal = xgboostArgs.xgboostParams(commParamMap +
-        // Add train-eval dataset if specified
-        ("eval_sets" -> datasets(1).map(ds => Map("test" -> ds)).getOrElse(Map.empty))
-      )
+      val xgbParamFinal = xgboostArgs.xgboostParams(commParamMap)
       val xgbRegressor = new XGBoostRegressor(xgbParamFinal)
         .setLabelCol(labelColName)
         .setFeaturesCol(featureNames)
 
+      datasets(1).foreach(_ => xgbRegressor.setEvalDataset(_))
+
       println("\n------ Training ------")
       // Shall we not log the time if it is abnormal, which is usually caused by training failure
       val (model, _) = benchmark.time("train") {