Predict on Ellpack. (#5327)

* Unify GPU prediction node.
* Add `PageExists`.
* Dispatch prediction on input data for GPU Predictor.

tests/cpp/predictor/test_predictor.cc

@@ -2,13 +2,16 @@
  * Copyright 2020 by Contributors
  */
 
-#include <cstddef>
 #include <gtest/gtest.h>
 #include <xgboost/predictor.h>
 #include <xgboost/data.h>
+#include <xgboost/host_device_vector.h>
+#include <xgboost/generic_parameters.h>
+
+#include "test_predictor.h"
 
 #include "../helpers.h"
-#include "xgboost/generic_parameters.h"
+#include "../../../src/common/io.h"
 
 namespace xgboost {
 TEST(Predictor, PredictionCache) {
@@ -30,4 +33,52 @@ TEST(Predictor, PredictionCache) {
   add_cache();
   EXPECT_ANY_THROW(container.Entry(m));
 }
+
+// Only run this test when CUDA is enabled.
+void TestTrainingPrediction(size_t rows, std::string tree_method) {
+  size_t constexpr kCols = 16;
+  size_t constexpr kClasses = 3;
+  size_t constexpr kIters = 3;
+
+  std::unique_ptr<Learner> learner;
+  auto train = [&](std::string predictor, HostDeviceVector<float>* out) {
+    auto pp_m = CreateDMatrix(rows, kCols, 0);
+    auto p_m = *pp_m;
+
+    auto &h_label = p_m->Info().labels_.HostVector();
+    h_label.resize(rows);
+
+    for (size_t i = 0; i < rows; ++i) {
+      h_label[i] = i % kClasses;
+    }
+
+    learner.reset(Learner::Create({}));
+    learner->SetParam("tree_method", tree_method);
+    learner->SetParam("objective", "multi:softprob");
+    learner->SetParam("predictor", predictor);
+    learner->SetParam("num_feature", std::to_string(kCols));
+    learner->SetParam("num_class", std::to_string(kClasses));
+    learner->Configure();
+
+    for (size_t i = 0; i < kIters; ++i) {
+      learner->UpdateOneIter(i, p_m);
+    }
+    learner->Predict(p_m, false, out);
+    delete pp_m;
+  };
+  // Alternate the predictor, CPU predictor can not use ellpack while GPU predictor can
+  // not use CPU histogram index.  So it's guaranteed one of the following is not
+  // predicting from histogram index.  Note: As of writing only GPU supports predicting
+  // from gradient index, the test is written for future portability.
+  HostDeviceVector<float> predictions_0;
+  train("cpu_predictor", &predictions_0);
+
+  HostDeviceVector<float> predictions_1;
+  train("gpu_predictor", &predictions_1);
+
+  for (size_t i = 0; i < rows; ++i) {
+    EXPECT_NEAR(predictions_1.ConstHostVector()[i],
+                predictions_0.ConstHostVector()[i], kRtEps);
+  }
+}
 }  // namespace xgboost