Sycl implementation for objective functions (#9846)

---------

Co-authored-by: Dmitry Razdoburdin <>

src/objective/multiclass_obj.cu

@@ -21,6 +21,8 @@
 #include "../common/math.h"
 #include "../common/transform.h"
 
+#include "multiclass_param.h"
+
 namespace xgboost {
 namespace obj {
 
@@ -28,15 +30,6 @@ namespace obj {
 DMLC_REGISTRY_FILE_TAG(multiclass_obj_gpu);
 #endif  // defined(XGBOOST_USE_CUDA)
 
-struct SoftmaxMultiClassParam : public XGBoostParameter<SoftmaxMultiClassParam> {
-  int num_class;
-  // declare parameters
-  DMLC_DECLARE_PARAMETER(SoftmaxMultiClassParam) {
-    DMLC_DECLARE_FIELD(num_class).set_lower_bound(1)
-        .describe("Number of output class in the multi-class classification.");
-  }
-};
-
 class SoftmaxMultiClassObj : public ObjFunction {
  public:
   explicit SoftmaxMultiClassObj(bool output_prob)

src/objective/multiclass_param.h

@@ -0,0 +1,25 @@
+/*!
+ * Copyright 2015-2023 by Contributors
+ * \file multiclass_param.h
+ * \brief Definition of multi-class classification parameters.
+ */
+#ifndef XGBOOST_OBJECTIVE_MULTICLASS_PARAM_H_
+#define XGBOOST_OBJECTIVE_MULTICLASS_PARAM_H_
+
+#include "xgboost/parameter.h"
+
+namespace xgboost {
+namespace obj {
+
+struct SoftmaxMultiClassParam : public XGBoostParameter<SoftmaxMultiClassParam> {
+  int num_class;
+  // declare parameters
+  DMLC_DECLARE_PARAMETER(SoftmaxMultiClassParam) {
+    DMLC_DECLARE_FIELD(num_class).set_lower_bound(1)
+        .describe("Number of output class in the multi-class classification.");
+  }
+};
+
+}  // namespace obj
+}  // namespace xgboost
+#endif  // XGBOOST_OBJECTIVE_MULTICLASS_PARAM_H_

src/objective/objective.cc

@@ -18,7 +18,11 @@ DMLC_REGISTRY_ENABLE(::xgboost::ObjFunctionReg);
 namespace xgboost {
 // implement factory functions
 ObjFunction* ObjFunction::Create(const std::string& name, Context const* ctx) {
-  auto *e = ::dmlc::Registry< ::xgboost::ObjFunctionReg>::Get()->Find(name);
+  std::string obj_name = name;
+  if (ctx->IsSycl()) {
+    obj_name = GetSyclImplementationName(obj_name);
+  }
+  auto *e = ::dmlc::Registry< ::xgboost::ObjFunctionReg>::Get()->Find(obj_name);
   if (e == nullptr) {
     std::stringstream ss;
     for (const auto& entry : ::dmlc::Registry< ::xgboost::ObjFunctionReg>::List()) {
@@ -32,6 +36,22 @@ ObjFunction* ObjFunction::Create(const std::string& name, Context const* ctx) {
   return pobj;
 }
 
+/* If the objective function has sycl-specific implementation,
+ * returns the specific implementation name.
+ * Otherwise return the orginal name without modifications.
+ */
+std::string ObjFunction::GetSyclImplementationName(const std::string& name) {
+  const std::string sycl_postfix = "_sycl";
+  auto *e = ::dmlc::Registry< ::xgboost::ObjFunctionReg>::Get()->Find(name + sycl_postfix);
+  if (e != nullptr) {
+    // Function has specific sycl implementation
+    return name + sycl_postfix;
+  } else {
+    // Function hasn't specific sycl implementation
+    return name;
+  }
+}
+
 void ObjFunction::InitEstimation(MetaInfo const&, linalg::Tensor<float, 1>* base_score) const {
   CHECK(base_score);
   base_score->Reshape(1);

src/objective/regression_obj.cu

@@ -35,6 +35,8 @@
 #include "xgboost/span.h"
 #include "xgboost/tree_model.h"  // RegTree
 
+#include "regression_param.h"
+
 #if defined(XGBOOST_USE_CUDA)
 #include "../common/cuda_context.cuh"  // for CUDAContext
 #include "../common/device_helpers.cuh"
@@ -53,14 +55,7 @@ void CheckRegInputs(MetaInfo const& info, HostDeviceVector<bst_float> const& pre
 DMLC_REGISTRY_FILE_TAG(regression_obj_gpu);
 #endif  // defined(XGBOOST_USE_CUDA)
 
-struct RegLossParam : public XGBoostParameter<RegLossParam> {
-  float scale_pos_weight;
-  // declare parameters
-  DMLC_DECLARE_PARAMETER(RegLossParam) {
-    DMLC_DECLARE_FIELD(scale_pos_weight).set_default(1.0f).set_lower_bound(0.0f)
-      .describe("Scale the weight of positive examples by this factor");
-  }
-};
+
 
 template<typename Loss>
 class RegLossObj : public FitIntercept {

src/objective/regression_param.h

@@ -0,0 +1,25 @@
+/*!
+ * Copyright 2015-2023 by Contributors
+ * \file multiclass_param.h
+ * \brief Definition of single-value regression and classification parameters.
+ */
+#ifndef XGBOOST_OBJECTIVE_REGRESSION_PARAM_H_
+#define XGBOOST_OBJECTIVE_REGRESSION_PARAM_H_
+
+#include "xgboost/parameter.h"
+
+namespace xgboost {
+namespace obj {
+
+struct RegLossParam : public XGBoostParameter<RegLossParam> {
+  float scale_pos_weight;
+  // declare parameters
+  DMLC_DECLARE_PARAMETER(RegLossParam) {
+    DMLC_DECLARE_FIELD(scale_pos_weight).set_default(1.0f).set_lower_bound(0.0f)
+      .describe("Scale the weight of positive examples by this factor");
+  }
+};
+
+}  // namespace obj
+}  // namespace xgboost
+#endif  // XGBOOST_OBJECTIVE_REGRESSION_PARAM_H_