Remove the deprecated gpu_hist. (#11549)

Author: trivialfis

include/xgboost/context.h

@@ -162,14 +162,6 @@ struct Context : public XGBoostParameter<Context> {
   bool fail_on_invalid_gpu_id{false};
   bool validate_parameters{false};
 
-  /**
-   * @brief Configure the parameter `device'. Deprecated, will remove once `gpu_id` is
-   *        removed.
-   *
-   * @param require_gpu Whether GPU is explicitly required by the user through other
-   *                    configurations.
-   */
-  void ConfigureGpuId(bool require_gpu);
   /**
    * @brief Returns the automatically chosen number of threads based on the `nthread`
    *        parameter and the system settting.

include/xgboost/gbm.h

@@ -158,10 +158,6 @@ class GradientBooster : public Model, public Configurable {
                             common::Span<int32_t const> trees,
                             std::vector<bst_feature_t>* features,
                             std::vector<float>* scores) const = 0;
-  /**
-   * @brief Whether the current booster uses GPU.
-   */
-  [[nodiscard]] virtual bool UseGPU() const = 0;
   /*!
    * \brief create a gradient booster from given name
    * \param name name of gradient booster

jvm-packages/xgboost4j-spark-gpu/src/main/scala/ml/dmlc/xgboost4j/scala/spark/GpuXGBoostPlugin.scala

@@ -102,7 +102,7 @@ class GpuXGBoostPlugin extends XGBoostPlugin {
   private[spark] def validate[T <: XGBoostEstimator[T, M], M <: XGBoostModel[M]](
       estimator: XGBoostEstimator[T, M],
       dataset: Dataset[_]): Unit = {
-    require(estimator.getTreeMethod == "gpu_hist" || estimator.getDevice != "cpu",
+    require(estimator.getDevice != "cpu",
       "Using Spark-Rapids to accelerate XGBoost must set device=cuda")
   }
 

jvm-packages/xgboost4j-spark-gpu/src/test/scala/ml/dmlc/xgboost4j/scala/spark/GpuXGBoostPluginSuite.scala

@@ -129,10 +129,6 @@ class GpuXGBoostPluginSuite extends GpuTestSuite {
 
       classifier.setDevice("gpu")
       plugin.validate(classifier, df)
-
-      classifier.setDevice("cpu")
-      classifier.setTreeMethod("gpu_hist")
-      plugin.validate(classifier, df)
     }
   }
 

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostEstimator.scala

@@ -374,7 +374,7 @@ private[spark] trait XGBoostEstimator[
 
   private[spark] def getRuntimeParameters(isLocal: Boolean,
       configs: Map[String, AnyRef] = Map.empty): RuntimeParams = {
-    val runOnGpu = if (getDevice != "cpu" || getTreeMethod == "gpu_hist") true else false
+    val runOnGpu = if (getDevice != "cpu") true else false
     RuntimeParams(
       getNumWorkers,
       getNumRound,

jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/params/TreeBoosterParams.scala

@@ -231,7 +231,7 @@ private[spark] trait TreeBoosterParams extends Params {
 
 private[spark] object BoosterParams {
 
-  val supportedTreeMethods = HashSet("auto", "exact", "approx", "hist", "gpu_hist")
+  val supportedTreeMethods = HashSet("auto", "exact", "approx", "hist")
 
   val supportedUpdaters = HashSet("grow_colmaker", "grow_histmaker", "grow_quantile_histmaker",
     "grow_gpu_hist", "grow_gpu_approx", "sync", "refresh", "prune")

jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostEstimatorSuite.scala

@@ -133,16 +133,6 @@ class XGBoostEstimatorSuite extends AnyFunSuite with PerTest with TmpFolderPerSu
       Map("device" -> "cuda")).setNumWorkers(1).setNumRound(1)
       .getRuntimeParameters(true)
     assert(runtimeParams.runOnGpu)
-
-    runtimeParams = new XGBoostClassifier(
-      Map("device" -> "cpu", "tree_method" -> "gpu_hist")).setNumWorkers(1).setNumRound(1)
-      .getRuntimeParameters(true)
-    assert(runtimeParams.runOnGpu)
-
-    runtimeParams = new XGBoostClassifier(
-      Map("device" -> "cuda", "tree_method" -> "gpu_hist")).setNumWorkers(1).setNumRound(1)
-      .getRuntimeParameters(true)
-    assert(runtimeParams.runOnGpu)
   }
 
   test("missing value exception for sparse vector") {

python-package/xgboost/sklearn.py

@@ -85,7 +85,7 @@ def _check_rf_callback(
 
 def _can_use_qdm(tree_method: Optional[str], device: Optional[str]) -> bool:
     not_sycl = (device is None) or (not device.startswith("sycl"))
-    return tree_method in ("hist", "gpu_hist", None, "auto") and not_sycl
+    return tree_method in ("hist", None, "auto") and not_sycl
 
 
 class _SklObjWProto(Protocol):

python-package/xgboost/spark/core.py

@@ -503,10 +503,8 @@ def _validate_params(self) -> None:
     def _run_on_gpu(self) -> bool:
         """If train or transform on the gpu according to the parameters"""
 
-        return (
-            use_cuda(self.getOrDefault(self.device))
-            or self.getOrDefault(self.use_gpu)
-            or self.getOrDefault(self.getParam("tree_method")) == "gpu_hist"
+        return use_cuda(self.getOrDefault(self.device)) or self.getOrDefault(
+            self.use_gpu
         )
 
     def _col_is_defined_not_empty(self, param: "Param[str]") -> bool:

src/context.cc

@@ -234,12 +234,6 @@ void Context::Init(Args const& kwargs) {
   }
 }
 
-void Context::ConfigureGpuId(bool require_gpu) {
-  if (this->IsCPU() && require_gpu) {
-    this->UpdateAllowUnknown(Args{{kDevice, DeviceSym::CUDA()}});
-  }
-}
-
 void Context::SetDeviceOrdinal(Args const& kwargs) {
   auto gpu_id_it = std::find_if(kwargs.cbegin(), kwargs.cend(),
                                 [](auto const& p) { return p.first == "gpu_id"; });